{
  "generated": "2026-08-10",
  "snapshot": {
    "date": "2026-08-10",
    "retrieved_at_utc": "2026-08-09T18:13:56Z",
    "raw_capture_sha256": "5029a1dd0e77fab6b0ed8f2665fa4d4fb26e48d151d7fa68e6a0d3c2dc200f87",
    "raw_capture_sha256_covers": "The raw API capture shared by both hubs of this survey. That artifact is not yet published, so this digest is a commitment rather than a check you can run today; the verifiable hash of this hub's served entries file is entries_sha256 in /api/snapshot.json.",
    "method_version": "supervised beta (v3.3 taxonomy)"
  },
  "disclaimer": "Inclusion is not endorsement. Not an audit. Entry descriptions are unreviewed editorial drafts.",
  "ordering": "category (alphabetically by category id), then full_name case-insensitively — never quality. `order` and the numeric part of `id` encode display position only. The taxonomy-code sequence /api/categories.json and /themes/ present (A1, A2 … S4) is a different sequence and does not govern `order`.",
  "terms": "These endpoints render the same facts as the pages. Quoting with attribution is permitted; redistributing the endpoints as a dataset is not, while the licensing review is open.",
  "terms_url": "https://ai-academic.org/license/",
  "sibling_hub": {
    "name": "AI Founder Hub",
    "url": "https://ai-founderhub.com/",
    "note": "The other hub of this survey: the entries in its four shared lanes and its cross-hub dual campaigns are published on both hubs — 68 shared entries, each under its own hub’s category and task. Everything else about the repository is identical across hubs, except campaigns[], which carries only the campaigns that admitted the entry on that hub and may be shorter on one side."
  },
  "fields": {
    "_note": "Paths are dotted and scoped. A key with no prefix is an entry field ON AN ENTRY RECORD, as served by /api/entries.json and the per-entry endpoints. The payload envelope — generated, count, source, taxonomy_version, ingested_definition, snapshot.*, and the /api/snapshot.json keys — is documented at the end of this glossary and is never part of a record. category.*, task.* and campaign.* are fields of /api/categories.json; axes.* fields are documented in /api/tags.json.",
    "id": "Hub-local record id (AHK-NNNN). It encodes display position and is not a cross-hub key. Use github_repo_id. The numeric part is `order` plus a fixed offset of 8 on this hub — AHK-0001 to AHK-0008 are retired placeholder records and are never re-minted — so int(id[-4:]) === order does not hold; int(id[-4:]) - 8 === order does, on every record here.",
    "order": "Display position within this hub’s category-then-name ordering. Not a rank. Served by the collection endpoint only; the per-entry endpoint omits it because a single record has no position to report.",
    "slug": "URL key, owner--name. Stable here, but mutable upstream.",
    "url": "The entry’s page on this hub. One page per record.",
    "full_name": "owner/name at the snapshot. For a renamed repository this is the current name; requested_name holds what the campaign recorded.",
    "github_repo_id": "The numeric repository id — the stable cross-hub join key. null for entries whose repository did not resolve; those have no id-keyed endpoint and are addressed by slug. When it is null the entry cannot be joined across hubs on the numeric id: fall back to slug, which both hubs generate identically from the campaign’s recorded owner/name and which is stable for as long as the entry stays unavailable. All four null-id entries here are on both hubs and all four slugs match. Do not fall back to full_name casing, and never to repo_url — it is null by definition for these.",
    "repo_url": "The repository page. null when the repository did not resolve at the snapshot; the entry stays on the map as a dated event. Never synthesise it from full_name for an unavailable entry: the address does not resolve. The entry page prints that address for a human as plain text, never as a link, with the date it returned 404.",
    "requested_name": "The name the campaign recorded, kept when the repository has since been renamed. null when it matches full_name.",
    "archived": "True when the repository is archived upstream, as reported by its own archived flag at the snapshot. Equivalent to status_state === \"archived\", stated explicitly so it does not have to be back-inferred.",
    "successor_slug": "The slug of the entry that carries the maintained line of this work, where the admitting campaign’s ledger records the move. null on every entry without a recorded succession — including name-twin pairs whose ledger says nothing about a move, which are never joined by name similarity.",
    "category": "The category id this entry is placed under on this hub. Joins to categories[].id in /api/categories.json. Hub-local: the same repository sits under a different category on the sibling hub.",
    "task": "The task id within that category. Joins to categories[].tasks[].id in /api/categories.json.",
    "description": "This site’s own one-line description of the entry. Curator paraphrase informed by project documentation; no project text is reproduced. See description_status.",
    "description_status": "Always \"editorial draft\": descriptions are the curators’ own words and have not cleared external review.",
    "tags": "Reserved tag ids carried by this entry. The vocabulary is registered and unpopulated, so this is [] on every record today. When it populates, values are tag SLUGS (artifact-literature-corpus), the form the /tag/ routes use — not the namespaced ids (artifact:literature-corpus). Both are served on every tag object in /api/tags.json, so the join key is unambiguous before the first value lands.",
    "on_both_hubs": "true when this repository is also an entry on the sibling hub of this survey, under that hub’s own category and task. The generating rule: on_both_hubs is computed by slug intersection of the two hubs’ catalogs at build and frozen in the repo, and it holds without exception that on_both_hubs === category.shared || any(campaigns[].campaign_placed_on_both_hubs). Those two sets are disjoint here: 47 shared-lane + 21 dual-campaign = 68.",
    "campaigns": "One object per campaign that admitted this entry on this hub. An entry may carry more than one, and a shared entry may carry a different number on the sibling hub.",
    "campaigns[].name": "The sealed campaign record’s identifier, dated by its own name prefix.",
    "campaigns[].campaign_placed_on_both_hubs": "true when the admitting CAMPAIGN is placed on both hubs. Renamed from `dual`, which was read as \"this entry is on both hubs\" and is not that: 21 entries carry it, 68 are on both hubs.",
    "campaigns[].claim": "The campaign’s coverage claim, verbatim and never upgraded. It describes the campaign’s coverage, not the repository.",
    "campaigns[].date": "The campaign’s own date, from its name prefix.",
    "campaigns[].claim_ref": "The campaign name the claim is quoted from — the sealed record’s identifier.",
    "campaigns[].scout_citations": "How many rows of that campaign’s ledger cite this repository. A count of evidence, not a score.",
    "metrics": "The snapshot metrics container on an entry. Every value inside it was observed at one dated capture; null means the value was not returned, never zero.",
    "metrics.stars": "The repository’s star count at the snapshot. A popularity figure recorded because it was in the capture. It is not used to order anything on this site and is not a quality signal.",
    "metrics.forks": "The fork count at the snapshot. Null when the repository did not resolve.",
    "metrics.watchers": "The watcher count at the snapshot. A count only: this site never publishes watcher identities.",
    "metrics.language": "The primary language GitHub reported at the snapshot, or null when it detected none.",
    "metrics.license_spdx": "The SPDX identifier GitHub reported at the snapshot. Three states, and the entry page renders three labels: an SPDX id prints as-is; \"NOASSERTION\" prints as \"License present, not classified\" (GitHub’s NOASSERTION — the repository asserts terms the API cannot classify); null prints as \"No license found\". \"NOASSERTION\" is a sentinel, not an SPDX identifier: validate against the SPDX list only after excluding it. The two are not one absence: a repository whose licence file cannot be classified has terms to read, and one with no licence file has none. An entry whose repository did not resolve at the snapshot carries null here and renders no licence row at all. Not a licence review.",
    "metrics.created_at": "Repository creation timestamp as reported at the snapshot.",
    "metrics.pushed_at": "Timestamp of the last push as reported at the snapshot. Not a maintenance judgment.",
    "metrics.topics": "The repository’s own declared topics at the snapshot, quoted as found.",
    "metrics.snapshot_date": "The label date of the snapshot the metrics came from. The retrieval instant is snapshot.retrieved_at_utc, which is a day earlier.",
    "metrics.http_status": "The status the repository returned at the snapshot: 200, or 404 for an entry that did not resolve.",
    "status_state": "Closed enum: \"live\", \"archived\", \"unavailable\". \"unavailable\" means the repository did not resolve at the snapshot.",
    "category.id": "The category id. The join target for an entry’s `category`.",
    "category.code": "The taxonomy code (A1, S1 …). Stable: the numbering skips codes retired by earlier drafts.",
    "category.title": "The category’s name in taxonomy v3.3.",
    "category.url": "The category’s page on this hub.",
    "category.shared": "true for the four lanes both hubs publish. Every shared-lane entry is on both hubs; see on_both_hubs, which is the larger set.",
    "category.status": "Closed enum on a CATEGORY: \"landed\" or \"planned\". Not the same field as an entry’s status_state.",
    "category.campaign_count": "How many campaigns are placed on this category on this hub, ingested or not.",
    "category.entry_count": "How many of this hub’s entries are filed under this category.",
    "category.tasks": "The category’s tasks, in display order. Tasks are anchored sections of the category page, not routes.",
    "task.id": "The task id within its category. The join target for an entry’s `task`.",
    "task.title": "The task’s name as this hub displays it.",
    "task.url": "The task’s address: the category page plus the task’s anchor.",
    "task.canonical_task": "The task’s identifier in the shared taxonomy both hubs draw from — the cross-hub crosswalk key. Equal to the local task id where the lane is shared.",
    "task.planned": "true when a task is in the taxonomy but no campaign has run on it. planned_grounding names the internal crosswalk row that grounds it, or is null when the only grounding cites unpublished material.",
    "task.planned_grounding": "The internal crosswalk row that grounds a planned task. Lab identifiers are withheld, because a lab number names an institution.",
    "task.entry_count": "How many of this hub’s entries are filed under this task.",
    "task.campaigns": "The campaigns placed on this task, oldest first.",
    "campaign.name": "The sealed campaign record’s identifier.",
    "campaign.date": "The campaign’s own date, from its name prefix. Same value as campaigns[].date on an entry.",
    "campaign.run_type": "The campaign’s own designation for how it searched, plus run_type_qualifier where it recorded one. A self-applied label, not an assessment by this site.",
    "campaign.run_type_qualifier": "A pre-standard campaign’s own coverage ceiling, quoted from the sealed record. null where the campaign recorded none.",
    "campaign.ledger_rows": "Rows in the campaign’s sealed evidence ledger. null where the record states none.",
    "campaign.screening_rows": "Rows the campaign screened before admitting any. null where the record states none.",
    "campaign.github_repo_count": "How many distinct repositories the campaign’s ledger names, as the campaign recorded it.",
    "campaign.ingested": "The campaign’s admitted ledger rows were extracted for this site. A campaign can be ingested and have admitted no repositories.",
    "campaign.entries_admitted_on_hub": "How many entries on this hub the campaign admitted, recounted from the entries rather than read off the ingested flag. An agent that reads `ingested` and stops overcounts: on this hub 11 campaigns are ingested and 10 admitted anything.",
    "campaign.claim": "The campaign’s coverage claim, verbatim and never upgraded — the same text campaigns[].claim carries on an entry. It describes the campaign’s coverage, not any repository under it.",
    "category.blurb": "What the category covers, in the same words the category page and /themes/ render. The four shared lanes carry the same blurb on both hubs, byte for byte.",
    "task.blurb": "What the task covers. null on every task here: a task is a heading and a count on this hub, and no surface carries prose for one — an absence stated rather than a key an agent has to discover is missing.",
    "generated": "When the payload was generated: the snapshot date on the entry endpoints, the campaign map’s own generation date on /api/categories.json and /api/snapshot.json.",
    "count": "How many records this payload carries — entries, categories or tags, depending on the endpoint. Not a survey-wide figure.",
    "source": "The extraction the campaign map came from, named with its upstream revision.",
    "taxonomy_version": "The taxonomy release these categories, tasks and placements belong to. Category codes are stable across releases; the numbering skips retired codes.",
    "ingested_definition": "The site’s own definition of `ingested`, served beside the flag so the flag cannot be read as a yield.",
    "snapshot": "The capture envelope. It describes the dated capture the metrics came from, and is identical on every payload this hub serves; it says nothing about the record it sits beside.",
    "snapshot.date": "The label date of the snapshot, local. The capture ran the day before — see snapshot.retrieved_at_utc, and note that every human-facing snapshot reference on this site prints both.",
    "snapshot.retrieved_at_utc": "The instant the capture ran, in UTC.",
    "snapshot.raw_capture_sha256": "The digest of the raw API capture the whole survey was built from, shared by both hubs. That artifact is not published, so this is a commitment rather than a check you can run today. The hash you CAN verify is entries_sha256 in /api/snapshot.json, which covers the exact bytes served at /api/entries.json. Renamed from `sha256`, which read as an integrity hash of the payload it sits in and never was one.",
    "snapshot.raw_capture_sha256_covers": "What that digest covers, in one sentence, served beside it so the distinction travels with the field rather than living two documents away.",
    "snapshot.method_version": "The method release in force at the capture. A version string, not a maturity claim.",
    "entries_sha256": "The sha256 of the exact bytes this hub serves at /api/entries.json, computed at build over the served string. The one hash a reader can check today. /api/snapshot.json only.",
    "entries_sha256_covers": "The URL entries_sha256 covers, so a verifier does not have to guess which bytes to hash.",
    "snapshot_hash_note": "One sentence separating the two hashes, carried in the data so the distinction does not live only on the pages.",
    "survey_tally": "The survey-wide figures the pages print — campaigns, ledger and screening rows, cohort size — plus this hub’s own entry count. Survey-wide except `entries`, which is hub-local.",
    "denominators": "How the survey-wide extraction count reconciles with this hub: how many of the extracted campaigns are placed here, and how many of those admitted anything.",
    "counts": "This hub’s own counts, recounted from the served entries at build. Every figure here can be recomputed from entries[].",
    "endpoints": "The addresses of this hub’s machine layer. The two per-entry patterns are written as literal placeholders, not as encoded URLs."
  },
  "count": 91,
  "entries": [
    {
      "id": "AHK-0009",
      "slug": "augurlabs--augur",
      "url": "https://ai-academic.org/registry/augurlabs--augur/",
      "github_repo_id": 78134122,
      "full_name": "augurlabs/augur",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/augurlabs/augur",
      "archived": false,
      "on_both_hubs": true,
      "category": "analysis-measurement",
      "task": "measure-platforms-longitudinally",
      "campaigns": [
        {
          "name": "2026-08-03__platform-ecosystem-longitudinal-measurement",
          "date": "2026-08-03",
          "claim": "High-coverage, effort-bounded map as of 2026-08-03 (AWAITING_INDEPENDENT_QA, action ceiling reached before two low-yield passes): supports a platform-native append-only panel design contract, but forbids treating current API values as history, absence as deletion, inactivity as exit, or namespaces as people.",
          "claim_ref": "2026-08-03__platform-ecosystem-longitudinal-measurement",
          "scout_citations": 1,
          "campaign_placed_on_both_hubs": true
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 692,
        "forks": 1005,
        "watchers": 20,
        "language": "Go",
        "license_spdx": "MIT",
        "created_at": "2017-01-05T17:34:54Z",
        "pushed_at": "2026-08-04T20:55:57Z",
        "topics": [
          "alt-metrics",
          "chaoss",
          "data-collection",
          "data-modeling",
          "data-visualization",
          "defined-metrics",
          "facade",
          "git",
          "github",
          "hacktoberfest2020",
          "linux",
          "linux-foundation",
          "metrics",
          "open-source",
          "opensource",
          "oss-governance",
          "research",
          "software",
          "sustainability"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "Open-source community-metrics platform from the CHAOSS ecosystem; the platform-measurement campaign kept it as a historical schema comparator.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 1
    },
    {
      "id": "AHK-0010",
      "slug": "aveloxis--aveloxis",
      "url": "https://ai-academic.org/registry/aveloxis--aveloxis/",
      "github_repo_id": 1207367567,
      "full_name": "aveloxis/aveloxis",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/aveloxis/aveloxis",
      "archived": false,
      "on_both_hubs": true,
      "category": "analysis-measurement",
      "task": "measure-platforms-longitudinally",
      "campaigns": [
        {
          "name": "2026-08-03__platform-ecosystem-longitudinal-measurement",
          "date": "2026-08-03",
          "claim": "High-coverage, effort-bounded map as of 2026-08-03 (AWAITING_INDEPENDENT_QA, action ceiling reached before two low-yield passes): supports a platform-native append-only panel design contract, but forbids treating current API values as history, absence as deletion, inactivity as exit, or namespaces as people.",
          "claim_ref": "2026-08-03__platform-ecosystem-longitudinal-measurement",
          "scout_citations": 1,
          "campaign_placed_on_both_hubs": true
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 15,
        "forks": 7,
        "watchers": 1,
        "language": "Go",
        "license_spdx": "MIT",
        "created_at": "2026-04-10T21:34:35Z",
        "pushed_at": "2026-08-07T14:08:29Z",
        "topics": [
          "ai",
          "artificial-intelligence",
          "augur",
          "augur-alternative",
          "chaoss",
          "chaoss-metrics",
          "community-health",
          "metrics",
          "open-source",
          "open-source-health",
          "oss-metrics",
          "social-computing",
          "software-analytics",
          "work"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "A community-metrics platform in Go; the platform-measurement ledger records it as the current form of the Augur lineage.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 2
    },
    {
      "id": "AHK-0011",
      "slug": "bohrdata--hfcommunity",
      "url": "https://ai-academic.org/registry/bohrdata--hfcommunity/",
      "github_repo_id": null,
      "full_name": "bohrdata/hfcommunity",
      "requested_name": null,
      "successor_slug": "som-research--hfcommunity",
      "repo_url": null,
      "archived": false,
      "on_both_hubs": true,
      "category": "analysis-measurement",
      "task": "measure-platforms-longitudinally",
      "campaigns": [
        {
          "name": "2026-08-03__platform-ecosystem-longitudinal-measurement",
          "date": "2026-08-03",
          "claim": "High-coverage, effort-bounded map as of 2026-08-03 (AWAITING_INDEPENDENT_QA, action ceiling reached before two low-yield passes): supports a platform-native append-only panel design contract, but forbids treating current API values as history, absence as deletion, inactivity as exit, or namespaces as people.",
          "claim_ref": "2026-08-03__platform-ecosystem-longitudinal-measurement",
          "scout_citations": 1,
          "campaign_placed_on_both_hubs": true
        }
      ],
      "status_state": "unavailable",
      "metrics": {
        "stars": null,
        "forks": null,
        "watchers": null,
        "language": null,
        "license_spdx": null,
        "created_at": null,
        "pushed_at": null,
        "topics": [],
        "http_status": 404,
        "snapshot_date": "2026-08-10"
      },
      "description": "A dataset project about a model-hub community. This namespace did not resolve at the 2026-08-10 snapshot (HTTP 404); the entry stays as a dated event, and the work's current home is listed separately.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 3
    },
    {
      "id": "AHK-0012",
      "slug": "chaoss--community",
      "url": "https://ai-academic.org/registry/chaoss--community/",
      "github_repo_id": 105695709,
      "full_name": "chaoss/community",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/chaoss/community",
      "archived": false,
      "on_both_hubs": true,
      "category": "analysis-measurement",
      "task": "measure-platforms-longitudinally",
      "campaigns": [
        {
          "name": "2026-08-03__platform-ecosystem-longitudinal-measurement",
          "date": "2026-08-03",
          "claim": "High-coverage, effort-bounded map as of 2026-08-03 (AWAITING_INDEPENDENT_QA, action ceiling reached before two low-yield passes): supports a platform-native append-only panel design contract, but forbids treating current API values as history, absence as deletion, inactivity as exit, or namespaces as people.",
          "claim_ref": "2026-08-03__platform-ecosystem-longitudinal-measurement",
          "scout_citations": 1,
          "campaign_placed_on_both_hubs": true
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 106,
        "forks": 190,
        "watchers": 18,
        "language": "JavaScript",
        "license_spdx": "MIT",
        "created_at": "2017-10-03T19:46:52Z",
        "pushed_at": "2026-08-07T13:18:45Z",
        "topics": [
          "chaoss",
          "community",
          "handbook",
          "mentorship",
          "project-governance"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "The CHAOSS community handbook: metric definitions and governance for open-source health measurement. Admitted for its metric-definition receipts and ethics conventions.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 4
    },
    {
      "id": "AHK-0013",
      "slug": "chaoss--grimoirelab-perceval",
      "url": "https://ai-academic.org/registry/chaoss--grimoirelab-perceval/",
      "github_repo_id": 47415120,
      "full_name": "chaoss/grimoirelab-perceval",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/chaoss/grimoirelab-perceval",
      "archived": false,
      "on_both_hubs": true,
      "category": "analysis-measurement",
      "task": "measure-platforms-longitudinally",
      "campaigns": [
        {
          "name": "2026-08-03__platform-ecosystem-longitudinal-measurement",
          "date": "2026-08-03",
          "claim": "High-coverage, effort-bounded map as of 2026-08-03 (AWAITING_INDEPENDENT_QA, action ceiling reached before two low-yield passes): supports a platform-native append-only panel design contract, but forbids treating current API values as history, absence as deletion, inactivity as exit, or namespaces as people.",
          "claim_ref": "2026-08-03__platform-ecosystem-longitudinal-measurement",
          "scout_citations": 1,
          "campaign_placed_on_both_hubs": true
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 324,
        "forks": 187,
        "watchers": 26,
        "language": "Python",
        "license_spdx": "GPL-3.0",
        "created_at": "2015-12-04T16:20:11Z",
        "pushed_at": "2026-08-07T16:17:47Z",
        "topics": [
          "data-fetching",
          "data-mining",
          "data-sources",
          "grimoirelab",
          "hacktoberfest",
          "perceval",
          "python",
          "software-analytics"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "Data-fetching component of GrimoireLab; pulls raw activity from many development platforms. Cited for its raw-versus-enriched data architecture.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 5
    },
    {
      "id": "AHK-0014",
      "slug": "chaoss--grimoirelab-sortinghat",
      "url": "https://ai-academic.org/registry/chaoss--grimoirelab-sortinghat/",
      "github_repo_id": 24677113,
      "full_name": "chaoss/grimoirelab-sortinghat",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/chaoss/grimoirelab-sortinghat",
      "archived": false,
      "on_both_hubs": true,
      "category": "analysis-measurement",
      "task": "measure-platforms-longitudinally",
      "campaigns": [
        {
          "name": "2026-08-03__platform-ecosystem-longitudinal-measurement",
          "date": "2026-08-03",
          "claim": "High-coverage, effort-bounded map as of 2026-08-03 (AWAITING_INDEPENDENT_QA, action ceiling reached before two low-yield passes): supports a platform-native append-only panel design contract, but forbids treating current API values as history, absence as deletion, inactivity as exit, or namespaces as people.",
          "claim_ref": "2026-08-03__platform-ecosystem-longitudinal-measurement",
          "scout_citations": 1,
          "campaign_placed_on_both_hubs": true
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 58,
        "forks": 89,
        "watchers": 12,
        "language": "Python",
        "license_spdx": "GPL-3.0",
        "created_at": "2014-10-01T12:12:30Z",
        "pushed_at": "2026-08-05T18:14:35Z",
        "topics": [],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "GrimoireLab's identity-management component. Cited alongside Perceval for architecture, with the campaign explicitly declining its identity-resolution features.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 6
    },
    {
      "id": "AHK-0015",
      "slug": "ecosyste-ms--repos",
      "url": "https://ai-academic.org/registry/ecosyste-ms--repos/",
      "github_repo_id": 495869944,
      "full_name": "ecosyste-ms/repos",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/ecosyste-ms/repos",
      "archived": false,
      "on_both_hubs": true,
      "category": "analysis-measurement",
      "task": "measure-platforms-longitudinally",
      "campaigns": [
        {
          "name": "2026-08-03__platform-ecosystem-longitudinal-measurement",
          "date": "2026-08-03",
          "claim": "High-coverage, effort-bounded map as of 2026-08-03 (AWAITING_INDEPENDENT_QA, action ceiling reached before two low-yield passes): supports a platform-native append-only panel design contract, but forbids treating current API values as history, absence as deletion, inactivity as exit, or namespaces as people.",
          "claim_ref": "2026-08-03__platform-ecosystem-longitudinal-measurement",
          "scout_citations": 1,
          "campaign_placed_on_both_hubs": true
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 72,
        "forks": 15,
        "watchers": 3,
        "language": "Ruby",
        "license_spdx": "AGPL-3.0",
        "created_at": "2022-05-24T14:55:25Z",
        "pushed_at": "2026-08-06T10:17:40Z",
        "topics": [],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "An open dataset service indexing package registries and repositories; cited for schema and coverage diagnostics, with any data merge deferred pending terms and provenance.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 7
    },
    {
      "id": "AHK-0016",
      "slug": "ghtorrent--ghtorrent-org",
      "url": "https://ai-academic.org/registry/ghtorrent--ghtorrent-org/",
      "github_repo_id": 8377696,
      "full_name": "ghtorrent/ghtorrent.org",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/ghtorrent/ghtorrent.org",
      "archived": false,
      "on_both_hubs": true,
      "category": "analysis-measurement",
      "task": "measure-platforms-longitudinally",
      "campaigns": [
        {
          "name": "2026-08-03__platform-ecosystem-longitudinal-measurement",
          "date": "2026-08-03",
          "claim": "High-coverage, effort-bounded map as of 2026-08-03 (AWAITING_INDEPENDENT_QA, action ceiling reached before two low-yield passes): supports a platform-native append-only panel design contract, but forbids treating current API values as history, absence as deletion, inactivity as exit, or namespaces as people.",
          "claim_ref": "2026-08-03__platform-ecosystem-longitudinal-measurement",
          "scout_citations": 1,
          "campaign_placed_on_both_hubs": true
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 158,
        "forks": 637,
        "watchers": 16,
        "language": "Ruby",
        "license_spdx": null,
        "created_at": "2013-02-23T16:03:24Z",
        "pushed_at": "2024-07-09T02:36:57Z",
        "topics": [
          "ghtorrent",
          "website"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "Site of the retired GHTorrent research dataset; kept as immutable historical evidence rather than a live backbone.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 8
    },
    {
      "id": "AHK-0017",
      "slug": "nasif-imtiaz-ohi--bodegha",
      "url": "https://ai-academic.org/registry/nasif-imtiaz-ohi--bodegha/",
      "github_repo_id": null,
      "full_name": "Nasif-Imtiaz-Ohi/BoDeGHa",
      "requested_name": null,
      "successor_slug": "sgl-umons--bodegha",
      "repo_url": null,
      "archived": false,
      "on_both_hubs": true,
      "category": "analysis-measurement",
      "task": "measure-platforms-longitudinally",
      "campaigns": [
        {
          "name": "2026-08-03__platform-ecosystem-longitudinal-measurement",
          "date": "2026-08-03",
          "claim": "High-coverage, effort-bounded map as of 2026-08-03 (AWAITING_INDEPENDENT_QA, action ceiling reached before two low-yield passes): supports a platform-native append-only panel design contract, but forbids treating current API values as history, absence as deletion, inactivity as exit, or namespaces as people.",
          "claim_ref": "2026-08-03__platform-ecosystem-longitudinal-measurement",
          "scout_citations": 1,
          "campaign_placed_on_both_hubs": true
        }
      ],
      "status_state": "unavailable",
      "metrics": {
        "stars": null,
        "forks": null,
        "watchers": null,
        "language": null,
        "license_spdx": null,
        "created_at": null,
        "pushed_at": null,
        "topics": [],
        "http_status": 404,
        "snapshot_date": "2026-08-10"
      },
      "description": "Original namespace of a bot-detection classifier for GitHub accounts. This namespace did not resolve at the 2026-08-10 snapshot (HTTP 404); the entry stays as a dated event, and the maintained line is listed under its current address.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 9
    },
    {
      "id": "AHK-0018",
      "slug": "package-url--purl-spec",
      "url": "https://ai-academic.org/registry/package-url--purl-spec/",
      "github_repo_id": 110339177,
      "full_name": "package-url/purl-spec",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/package-url/purl-spec",
      "archived": false,
      "on_both_hubs": true,
      "category": "analysis-measurement",
      "task": "measure-platforms-longitudinally",
      "campaigns": [
        {
          "name": "2026-08-03__platform-ecosystem-longitudinal-measurement",
          "date": "2026-08-03",
          "claim": "High-coverage, effort-bounded map as of 2026-08-03 (AWAITING_INDEPENDENT_QA, action ceiling reached before two low-yield passes): supports a platform-native append-only panel design contract, but forbids treating current API values as history, absence as deletion, inactivity as exit, or namespaces as people.",
          "claim_ref": "2026-08-03__platform-ecosystem-longitudinal-measurement",
          "scout_citations": 1,
          "campaign_placed_on_both_hubs": true
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 1090,
        "forks": 238,
        "watchers": 34,
        "language": "Python",
        "license_spdx": "NOASSERTION",
        "created_at": "2017-11-11T11:12:46Z",
        "pushed_at": "2026-08-07T18:20:05Z",
        "topics": [
          "cyclonedx",
          "dependencies",
          "package",
          "package-management",
          "package-url",
          "purl",
          "sbom",
          "spdx",
          "url"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "The package-URL specification: canonical coordinates for software packages across ecosystems. Adopted by the campaign for dependency identity.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 10
    },
    {
      "id": "AHK-0019",
      "slug": "reporeapers--github-repo-dataset",
      "url": "https://ai-academic.org/registry/reporeapers--github-repo-dataset/",
      "github_repo_id": null,
      "full_name": "RepoReapers/github-repo-dataset",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": null,
      "archived": false,
      "on_both_hubs": true,
      "category": "analysis-measurement",
      "task": "measure-platforms-longitudinally",
      "campaigns": [
        {
          "name": "2026-08-03__platform-ecosystem-longitudinal-measurement",
          "date": "2026-08-03",
          "claim": "High-coverage, effort-bounded map as of 2026-08-03 (AWAITING_INDEPENDENT_QA, action ceiling reached before two low-yield passes): supports a platform-native append-only panel design contract, but forbids treating current API values as history, absence as deletion, inactivity as exit, or namespaces as people.",
          "claim_ref": "2026-08-03__platform-ecosystem-longitudinal-measurement",
          "scout_citations": 1,
          "campaign_placed_on_both_hubs": true
        }
      ],
      "status_state": "unavailable",
      "metrics": {
        "stars": null,
        "forks": null,
        "watchers": null,
        "language": null,
        "license_spdx": null,
        "created_at": null,
        "pushed_at": null,
        "topics": [],
        "http_status": 404,
        "snapshot_date": "2026-08-10"
      },
      "description": "Dataset namespace from the RepoReapers curation research. This namespace did not resolve at the 2026-08-10 snapshot (HTTP 404); the entry stays as a dated event, and its duplicate-cluster diagnostics survive in the scholarly record.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 11
    },
    {
      "id": "AHK-0020",
      "slug": "sgl-umons--bodegha",
      "url": "https://ai-academic.org/registry/sgl-umons--bodegha/",
      "github_repo_id": 269348790,
      "full_name": "sgl-umons/BoDeGHa",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/sgl-umons/BoDeGHa",
      "archived": false,
      "on_both_hubs": true,
      "category": "analysis-measurement",
      "task": "measure-platforms-longitudinally",
      "campaigns": [
        {
          "name": "2026-08-03__platform-ecosystem-longitudinal-measurement",
          "date": "2026-08-03",
          "claim": "High-coverage, effort-bounded map as of 2026-08-03 (AWAITING_INDEPENDENT_QA, action ceiling reached before two low-yield passes): supports a platform-native append-only panel design contract, but forbids treating current API values as history, absence as deletion, inactivity as exit, or namespaces as people.",
          "claim_ref": "2026-08-03__platform-ecosystem-longitudinal-measurement",
          "scout_citations": 1,
          "campaign_placed_on_both_hubs": true
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 27,
        "forks": 13,
        "watchers": 2,
        "language": "Python",
        "license_spdx": "NOASSERTION",
        "created_at": "2020-06-04T12:05:00Z",
        "pushed_at": "2026-02-17T14:30:49Z",
        "topics": [],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "Maintained home of BoDeGHa, a classifier separating bot from human GitHub accounts; cited for its validation pattern.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 12
    },
    {
      "id": "AHK-0021",
      "slug": "som-research--hfcommunity",
      "url": "https://ai-academic.org/registry/som-research--hfcommunity/",
      "github_repo_id": 516389626,
      "full_name": "SOM-Research/HFCommunity",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/SOM-Research/HFCommunity",
      "archived": false,
      "on_both_hubs": true,
      "category": "analysis-measurement",
      "task": "measure-platforms-longitudinally",
      "campaigns": [
        {
          "name": "2026-08-03__platform-ecosystem-longitudinal-measurement",
          "date": "2026-08-03",
          "claim": "High-coverage, effort-bounded map as of 2026-08-03 (AWAITING_INDEPENDENT_QA, action ceiling reached before two low-yield passes): supports a platform-native append-only panel design contract, but forbids treating current API values as history, absence as deletion, inactivity as exit, or namespaces as people.",
          "claim_ref": "2026-08-03__platform-ecosystem-longitudinal-measurement",
          "scout_citations": 1,
          "campaign_placed_on_both_hubs": true
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 16,
        "forks": 2,
        "watchers": 3,
        "language": "Python",
        "license_spdx": "CC-BY-SA-4.0",
        "created_at": "2022-07-21T13:47:30Z",
        "pushed_at": "2024-10-14T16:05:11Z",
        "topics": [
          "data-science",
          "database",
          "dataset",
          "huggingface"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "Current home of HFCommunity, a relational dataset built from a model hub's public activity; acquisition deferred to dated dumps.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 13
    },
    {
      "id": "AHK-0022",
      "slug": "arx-deidentifier--arx",
      "url": "https://ai-academic.org/registry/arx-deidentifier--arx/",
      "github_repo_id": 9751165,
      "full_name": "arx-deidentifier/arx",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/arx-deidentifier/arx",
      "archived": false,
      "on_both_hubs": true,
      "category": "data-collection-curation",
      "task": "govern-research-data",
      "campaigns": [
        {
          "name": "2026-08-03__privacy-consent-retention-data-governance",
          "date": "2026-08-03",
          "claim": "High-coverage, effort-bounded map as of 2026-08-03 (AWAITING_INDEPENDENT_QA): adopt one append-only research-data lifecycle contract binding purpose, fields, identities, custody, linkage, retention, release and review; no generic deletion-receipt standard exists and no legal-applicability conclusion is drawn.",
          "claim_ref": "2026-08-03__privacy-consent-retention-data-governance",
          "scout_citations": 1,
          "campaign_placed_on_both_hubs": true
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 733,
        "forks": 234,
        "watchers": 32,
        "language": "Java",
        "license_spdx": "Apache-2.0",
        "created_at": "2013-04-29T15:23:18Z",
        "pushed_at": "2025-10-01T15:44:48Z",
        "topics": [
          "arx",
          "cross-platform",
          "data-analytics",
          "data-anonymization",
          "de-identification",
          "open-source",
          "privacy"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "A data-anonymization workbench in Java; admitted without benchmark or dataset-specific validation, and the ledger says so.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 14
    },
    {
      "id": "AHK-0023",
      "slug": "data-privacy-stack--presidio",
      "url": "https://ai-academic.org/registry/data-privacy-stack--presidio/",
      "github_repo_id": 132129752,
      "full_name": "data-privacy-stack/presidio",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/data-privacy-stack/presidio",
      "archived": false,
      "on_both_hubs": true,
      "category": "data-collection-curation",
      "task": "govern-research-data",
      "campaigns": [
        {
          "name": "2026-08-03__privacy-consent-retention-data-governance",
          "date": "2026-08-03",
          "claim": "High-coverage, effort-bounded map as of 2026-08-03 (AWAITING_INDEPENDENT_QA): adopt one append-only research-data lifecycle contract binding purpose, fields, identities, custody, linkage, retention, release and review; no generic deletion-receipt standard exists and no legal-applicability conclusion is drawn.",
          "claim_ref": "2026-08-03__privacy-consent-retention-data-governance",
          "scout_citations": 1,
          "campaign_placed_on_both_hubs": true
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 10398,
        "forks": 1239,
        "watchers": 95,
        "language": "Python",
        "license_spdx": "MIT",
        "created_at": "2018-05-04T11:08:58Z",
        "pushed_at": "2026-08-09T06:51:19Z",
        "topics": [
          "anonymization",
          "data-anonymization",
          "data-masking",
          "data-obfuscation",
          "data-privacy",
          "data-redaction",
          "de-identification",
          "guardrails",
          "image-redactor",
          "named-entity-recognition",
          "nlp",
          "personally-identifiable-information",
          "phi",
          "pii",
          "pii-detection",
          "privacy",
          "python",
          "sensitive-data",
          "spacy",
          "transformers"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "PII detection and masking tooling; the ledger marks capability claims as project self-description, not verified findings.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 15
    },
    {
      "id": "AHK-0024",
      "slug": "databiosphere--consent",
      "url": "https://ai-academic.org/registry/databiosphere--consent/",
      "github_repo_id": 23197094,
      "full_name": "DataBiosphere/consent",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/DataBiosphere/consent",
      "archived": false,
      "on_both_hubs": true,
      "category": "data-collection-curation",
      "task": "govern-research-data",
      "campaigns": [
        {
          "name": "2026-08-03__privacy-consent-retention-data-governance",
          "date": "2026-08-03",
          "claim": "High-coverage, effort-bounded map as of 2026-08-03 (AWAITING_INDEPENDENT_QA): adopt one append-only research-data lifecycle contract binding purpose, fields, identities, custody, linkage, retention, release and review; no generic deletion-receipt standard exists and no legal-applicability conclusion is drawn.",
          "claim_ref": "2026-08-03__privacy-consent-retention-data-governance",
          "scout_citations": 1,
          "campaign_placed_on_both_hubs": true
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 11,
        "forks": 2,
        "watchers": 48,
        "language": "Java",
        "license_spdx": "BSD-3-Clause",
        "created_at": "2014-08-21T17:50:53Z",
        "pushed_at": "2026-08-08T07:18:14Z",
        "topics": [],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "A consent-management service from the biomedical data world; kept as governance-machinery evidence, uninspected at runtime.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 16
    },
    {
      "id": "AHK-0025",
      "slug": "ebispot--duo",
      "url": "https://ai-academic.org/registry/ebispot--duo/",
      "github_repo_id": 71328309,
      "full_name": "EBISPOT/DUO",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/EBISPOT/DUO",
      "archived": false,
      "on_both_hubs": true,
      "category": "data-collection-curation",
      "task": "govern-research-data",
      "campaigns": [
        {
          "name": "2026-08-03__privacy-consent-retention-data-governance",
          "date": "2026-08-03",
          "claim": "High-coverage, effort-bounded map as of 2026-08-03 (AWAITING_INDEPENDENT_QA): adopt one append-only research-data lifecycle contract binding purpose, fields, identities, custody, linkage, retention, release and review; no generic deletion-receipt standard exists and no legal-applicability conclusion is drawn.",
          "claim_ref": "2026-08-03__privacy-consent-retention-data-governance",
          "scout_citations": 1,
          "campaign_placed_on_both_hubs": true
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 70,
        "forks": 17,
        "watchers": 13,
        "language": "Makefile",
        "license_spdx": "NOASSERTION",
        "created_at": "2016-10-19T07:00:06Z",
        "pushed_at": "2022-09-21T14:41:14Z",
        "topics": [
          "biomedical-applications",
          "biomedical-informatics",
          "datasets-tagged",
          "genomics-data",
          "obofoundry",
          "ontology",
          "owl"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "The Data Use Ontology: machine-readable data-use conditions from genomics; the ledger notes other domains would need mapping.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 17
    },
    {
      "id": "AHK-0026",
      "slug": "ethyca--fides",
      "url": "https://ai-academic.org/registry/ethyca--fides/",
      "github_repo_id": 336102115,
      "full_name": "ethyca/fides",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/ethyca/fides",
      "archived": false,
      "on_both_hubs": true,
      "category": "data-collection-curation",
      "task": "govern-research-data",
      "campaigns": [
        {
          "name": "2026-08-03__privacy-consent-retention-data-governance",
          "date": "2026-08-03",
          "claim": "High-coverage, effort-bounded map as of 2026-08-03 (AWAITING_INDEPENDENT_QA): adopt one append-only research-data lifecycle contract binding purpose, fields, identities, custody, linkage, retention, release and review; no generic deletion-receipt standard exists and no legal-applicability conclusion is drawn.",
          "claim_ref": "2026-08-03__privacy-consent-retention-data-governance",
          "scout_citations": 1,
          "campaign_placed_on_both_hubs": true
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 474,
        "forks": 94,
        "watchers": 22,
        "language": "Python",
        "license_spdx": "Apache-2.0",
        "created_at": "2021-02-04T22:42:33Z",
        "pushed_at": "2026-08-06T17:50:27Z",
        "topics": [
          "data",
          "data-privacy",
          "data-privacy-compliance",
          "developer-tools",
          "gdpr",
          "hacktoberfest",
          "privacy-as-code",
          "python"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "Privacy-engineering tooling for policy-as-code; a reproducible first-party locator is registered, execution was not performed.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 18
    },
    {
      "id": "AHK-0027",
      "slug": "moj-analytical-services--splink",
      "url": "https://ai-academic.org/registry/moj-analytical-services--splink/",
      "github_repo_id": 223420284,
      "full_name": "moj-analytical-services/splink",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/moj-analytical-services/splink",
      "archived": false,
      "on_both_hubs": true,
      "category": "data-collection-curation",
      "task": "govern-research-data",
      "campaigns": [
        {
          "name": "2026-08-03__privacy-consent-retention-data-governance",
          "date": "2026-08-03",
          "claim": "High-coverage, effort-bounded map as of 2026-08-03 (AWAITING_INDEPENDENT_QA): adopt one append-only research-data lifecycle contract binding purpose, fields, identities, custody, linkage, retention, release and review; no generic deletion-receipt standard exists and no legal-applicability conclusion is drawn.",
          "claim_ref": "2026-08-03__privacy-consent-retention-data-governance",
          "scout_citations": 1,
          "campaign_placed_on_both_hubs": true
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 2331,
        "forks": 252,
        "watchers": 16,
        "language": "Python",
        "license_spdx": "MIT",
        "created_at": "2019-11-22T14:27:33Z",
        "pushed_at": "2026-08-06T14:48:23Z",
        "topics": [
          "data-matching",
          "data-science",
          "deduplicate-data",
          "deduplication",
          "duckdb",
          "em-algorithm",
          "entity-resolution",
          "fuzzy-matching",
          "record-linkage",
          "spark",
          "uk-gov-data-science"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "A Python library for probabilistic record linkage at scale. Two campaign ledgers across the survey's hubs cite it: industry classification crosswalks, and data governance, where linkage quality depends on stated model assumptions.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 19
    },
    {
      "id": "AHK-0028",
      "slug": "opendp--opendp",
      "url": "https://ai-academic.org/registry/opendp--opendp/",
      "github_repo_id": 336597985,
      "full_name": "opendp/opendp",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/opendp/opendp",
      "archived": false,
      "on_both_hubs": true,
      "category": "data-collection-curation",
      "task": "govern-research-data",
      "campaigns": [
        {
          "name": "2026-08-03__privacy-consent-retention-data-governance",
          "date": "2026-08-03",
          "claim": "High-coverage, effort-bounded map as of 2026-08-03 (AWAITING_INDEPENDENT_QA): adopt one append-only research-data lifecycle contract binding purpose, fields, identities, custody, linkage, retention, release and review; no generic deletion-receipt standard exists and no legal-applicability conclusion is drawn.",
          "claim_ref": "2026-08-03__privacy-consent-retention-data-governance",
          "scout_citations": 1,
          "campaign_placed_on_both_hubs": true
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 428,
        "forks": 78,
        "watchers": 11,
        "language": "Rust",
        "license_spdx": "MIT",
        "created_at": "2021-02-06T17:40:39Z",
        "pushed_at": "2026-08-09T17:11:27Z",
        "topics": [
          "differential-privacy",
          "dp-programming-framework",
          "opendp",
          "privacy"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "A differential-privacy framework in Rust; experimental features and domain assumptions are flagged for pinning.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 20
    },
    {
      "id": "AHK-0029",
      "slug": "w3c-cg--dpv",
      "url": "https://ai-academic.org/registry/w3c-cg--dpv/",
      "github_repo_id": 372342615,
      "full_name": "w3c-cg/dpv",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/w3c-cg/dpv",
      "archived": false,
      "on_both_hubs": true,
      "category": "data-collection-curation",
      "task": "govern-research-data",
      "campaigns": [
        {
          "name": "2026-08-03__privacy-consent-retention-data-governance",
          "date": "2026-08-03",
          "claim": "High-coverage, effort-bounded map as of 2026-08-03 (AWAITING_INDEPENDENT_QA): adopt one append-only research-data lifecycle contract binding purpose, fields, identities, custody, linkage, retention, release and review; no generic deletion-receipt standard exists and no legal-applicability conclusion is drawn.",
          "claim_ref": "2026-08-03__privacy-consent-retention-data-governance",
          "scout_citations": 1,
          "campaign_placed_on_both_hubs": true
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 80,
        "forks": 34,
        "watchers": 17,
        "language": "HTML",
        "license_spdx": "NOASSERTION",
        "created_at": "2021-05-31T00:32:40Z",
        "pushed_at": "2026-08-06T18:13:32Z",
        "topics": [
          "data-protection",
          "gdpr",
          "privacy",
          "semantics",
          "vocabulary"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "The Data Privacy Vocabulary: terms for processing, purposes and legal concepts; the ledger notes that vocabulary is not compliance.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 21
    },
    {
      "id": "AHK-0030",
      "slug": "agentops-ai--agentops",
      "url": "https://ai-academic.org/registry/agentops-ai--agentops/",
      "github_repo_id": 679017521,
      "full_name": "AgentOps-AI/agentops",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/AgentOps-AI/agentops",
      "archived": false,
      "on_both_hubs": true,
      "category": "human-agent-operations",
      "task": "token-economics-ai-cost",
      "campaigns": [
        {
          "name": "2026-08-01__token-usage-observability-accounting",
          "date": "2026-08-01",
          "claim": "High-coverage, effort-bounded map as of 2026-08-01; not saturated — supports a provider-neutral measurement contract, but the Token Economist may run only as a shadow measurement system until sample-based capture checks pass.",
          "claim_ref": "2026-08-01__token-usage-observability-accounting",
          "scout_citations": 2,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 5761,
        "forks": 612,
        "watchers": 51,
        "language": "Python",
        "license_spdx": "MIT",
        "created_at": "2023-08-15T23:26:23Z",
        "pushed_at": "2026-06-25T08:25:03Z",
        "topics": [
          "agent",
          "agentops",
          "agents-sdk",
          "ai",
          "anthropic",
          "autogen",
          "cost-estimation",
          "crewai",
          "evals",
          "evaluation-metrics",
          "groq",
          "langchain",
          "llm",
          "mistral",
          "ollama",
          "openai",
          "openai-agents"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "Session-level agent observability in Python: token and cost tracking, tool calls, replay. Cited twice in the token-economics ledger.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 22
    },
    {
      "id": "AHK-0031",
      "slug": "arize-ai--openinference",
      "url": "https://ai-academic.org/registry/arize-ai--openinference/",
      "github_repo_id": 735999703,
      "full_name": "Arize-ai/openinference",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/Arize-ai/openinference",
      "archived": false,
      "on_both_hubs": true,
      "category": "human-agent-operations",
      "task": "token-economics-ai-cost",
      "campaigns": [
        {
          "name": "2026-08-01__token-usage-observability-accounting",
          "date": "2026-08-01",
          "claim": "High-coverage, effort-bounded map as of 2026-08-01; not saturated — supports a provider-neutral measurement contract, but the Token Economist may run only as a shadow measurement system until sample-based capture checks pass.",
          "claim_ref": "2026-08-01__token-usage-observability-accounting",
          "scout_citations": 3,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 1138,
        "forks": 288,
        "watchers": 16,
        "language": "Python",
        "license_spdx": "Apache-2.0",
        "created_at": "2023-12-26T17:33:58Z",
        "pushed_at": "2026-08-08T17:57:51Z",
        "topics": [
          "aiops",
          "gemini",
          "hacktoberfest",
          "haystack",
          "langchain",
          "langraph",
          "llamaindex",
          "llmops",
          "llms",
          "mcp",
          "openai",
          "openai-agents",
          "opentelemetry",
          "pydantic-ai",
          "smolagents",
          "telemetry",
          "tracing",
          "vercel",
          "vertex"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "OpenTelemetry-compatible tracing conventions and instrumentations for model applications, with masking support.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 23
    },
    {
      "id": "AHK-0032",
      "slug": "berriai--litellm",
      "url": "https://ai-academic.org/registry/berriai--litellm/",
      "github_repo_id": 671269505,
      "full_name": "BerriAI/litellm",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/BerriAI/litellm",
      "archived": false,
      "on_both_hubs": true,
      "category": "human-agent-operations",
      "task": "token-economics-ai-cost",
      "campaigns": [
        {
          "name": "2026-08-01__token-usage-observability-accounting",
          "date": "2026-08-01",
          "claim": "High-coverage, effort-bounded map as of 2026-08-01; not saturated — supports a provider-neutral measurement contract, but the Token Economist may run only as a shadow measurement system until sample-based capture checks pass.",
          "claim_ref": "2026-08-01__token-usage-observability-accounting",
          "scout_citations": 5,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 55954,
        "forks": 10443,
        "watchers": 220,
        "language": "Python",
        "license_spdx": "NOASSERTION",
        "created_at": "2023-07-27T00:09:52Z",
        "pushed_at": "2026-08-09T13:09:30Z",
        "topics": [
          "ai-gateway",
          "anthropic",
          "azure-openai",
          "bedrock",
          "gateway",
          "langchain",
          "litellm",
          "llm",
          "llm-gateway",
          "llmops",
          "mcp-gateway",
          "openai",
          "openai-proxy",
          "rust",
          "rust-ai",
          "vertex-ai"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "A multi-provider model gateway; the ledger cites its spend-tracking dimensions and its public issue history as cost-accounting evidence.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 24
    },
    {
      "id": "AHK-0033",
      "slug": "crewaiinc--crewai",
      "url": "https://ai-academic.org/registry/crewaiinc--crewai/",
      "github_repo_id": 710601088,
      "full_name": "crewAIInc/crewAI",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/crewAIInc/crewAI",
      "archived": false,
      "on_both_hubs": true,
      "category": "human-agent-operations",
      "task": "token-economics-ai-cost",
      "campaigns": [
        {
          "name": "2026-08-01__token-usage-observability-accounting",
          "date": "2026-08-01",
          "claim": "High-coverage, effort-bounded map as of 2026-08-01; not saturated — supports a provider-neutral measurement contract, but the Token Economist may run only as a shadow measurement system until sample-based capture checks pass.",
          "claim_ref": "2026-08-01__token-usage-observability-accounting",
          "scout_citations": 3,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 56858,
        "forks": 8107,
        "watchers": 390,
        "language": "Python",
        "license_spdx": "MIT",
        "created_at": "2023-10-27T03:26:59Z",
        "pushed_at": "2026-08-09T14:30:56Z",
        "topics": [
          "agents",
          "ai",
          "ai-agents",
          "aiagentframework",
          "llms"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "A multi-agent framework in Python; two survey ledgers cite it — for usage-accounting fields and for role-and-process organization design.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 25
    },
    {
      "id": "AHK-0034",
      "slug": "future-agi--traceai",
      "url": "https://ai-academic.org/registry/future-agi--traceai/",
      "github_repo_id": 966544022,
      "full_name": "future-agi/traceAI",
      "requested_name": "future-agi/traceai",
      "successor_slug": null,
      "repo_url": "https://github.com/future-agi/traceAI",
      "archived": false,
      "on_both_hubs": true,
      "category": "human-agent-operations",
      "task": "token-economics-ai-cost",
      "campaigns": [
        {
          "name": "2026-08-01__token-usage-observability-accounting",
          "date": "2026-08-01",
          "claim": "High-coverage, effort-bounded map as of 2026-08-01; not saturated — supports a provider-neutral measurement contract, but the Token Economist may run only as a shadow measurement system until sample-based capture checks pass.",
          "claim_ref": "2026-08-01__token-usage-observability-accounting",
          "scout_citations": 2,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 210,
        "forks": 38,
        "watchers": 2,
        "language": "Python",
        "license_spdx": "Apache-2.0",
        "created_at": "2025-04-15T04:57:02Z",
        "pushed_at": "2026-07-30T13:41:20Z",
        "topics": [
          "ai",
          "ai-agents",
          "langchain",
          "large-language-models",
          "observability",
          "openai",
          "opentelemetry",
          "tracing"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "OpenTelemetry tracing that instruments model calls, token counts and agent decisions.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 26
    },
    {
      "id": "AHK-0035",
      "slug": "lmnr-ai--lmnr",
      "url": "https://ai-academic.org/registry/lmnr-ai--lmnr/",
      "github_repo_id": 849139885,
      "full_name": "lmnr-ai/lmnr",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/lmnr-ai/lmnr",
      "archived": false,
      "on_both_hubs": true,
      "category": "human-agent-operations",
      "task": "token-economics-ai-cost",
      "campaigns": [
        {
          "name": "2026-08-01__token-usage-observability-accounting",
          "date": "2026-08-01",
          "claim": "High-coverage, effort-bounded map as of 2026-08-01; not saturated — supports a provider-neutral measurement contract, but the Token Economist may run only as a shadow measurement system until sample-based capture checks pass.",
          "claim_ref": "2026-08-01__token-usage-observability-accounting",
          "scout_citations": 2,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 3155,
        "forks": 220,
        "watchers": 9,
        "language": "TypeScript",
        "license_spdx": "Apache-2.0",
        "created_at": "2024-08-29T03:45:28Z",
        "pushed_at": "2026-08-07T12:51:04Z",
        "topics": [
          "agent-observability",
          "agents",
          "ai",
          "ai-observability",
          "aiops",
          "analytics",
          "developer-tools",
          "evals",
          "evaluation",
          "llm-evaluation",
          "llm-observability",
          "llmops",
          "monitoring",
          "observability",
          "open-source",
          "rust",
          "rust-lang",
          "self-hosted",
          "ts",
          "typescript"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "An OpenTelemetry-native tracing and evaluation platform for agents, in TypeScript.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 27
    },
    {
      "id": "AHK-0036",
      "slug": "open-telemetry--semantic-conventions",
      "url": "https://ai-academic.org/registry/open-telemetry--semantic-conventions/",
      "github_repo_id": 638591290,
      "full_name": "open-telemetry/semantic-conventions",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/open-telemetry/semantic-conventions",
      "archived": false,
      "on_both_hubs": true,
      "category": "human-agent-operations",
      "task": "token-economics-ai-cost",
      "campaigns": [
        {
          "name": "2026-08-01__token-usage-observability-accounting",
          "date": "2026-08-01",
          "claim": "High-coverage, effort-bounded map as of 2026-08-01; not saturated — supports a provider-neutral measurement contract, but the Token Economist may run only as a shadow measurement system until sample-based capture checks pass.",
          "claim_ref": "2026-08-01__token-usage-observability-accounting",
          "scout_citations": 1,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 627,
        "forks": 377,
        "watchers": 47,
        "language": "Jinja",
        "license_spdx": "Apache-2.0",
        "created_at": "2023-05-09T17:15:53Z",
        "pushed_at": "2026-08-07T16:40:19Z",
        "topics": [],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "The OpenTelemetry semantic-conventions registry; kept as the source the GenAI conventions moved out of, with the successor listed separately.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 28
    },
    {
      "id": "AHK-0037",
      "slug": "open-telemetry--semantic-conventions-genai",
      "url": "https://ai-academic.org/registry/open-telemetry--semantic-conventions-genai/",
      "github_repo_id": 1229425836,
      "full_name": "open-telemetry/semantic-conventions-genai",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/open-telemetry/semantic-conventions-genai",
      "archived": false,
      "on_both_hubs": true,
      "category": "human-agent-operations",
      "task": "token-economics-ai-cost",
      "campaigns": [
        {
          "name": "2026-08-01__token-usage-observability-accounting",
          "date": "2026-08-01",
          "claim": "High-coverage, effort-bounded map as of 2026-08-01; not saturated — supports a provider-neutral measurement contract, but the Token Economist may run only as a shadow measurement system until sample-based capture checks pass.",
          "claim_ref": "2026-08-01__token-usage-observability-accounting",
          "scout_citations": 2,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 234,
        "forks": 75,
        "watchers": 8,
        "language": "Python",
        "license_spdx": "Apache-2.0",
        "created_at": "2026-05-05T03:08:44Z",
        "pushed_at": "2026-08-09T03:40:06Z",
        "topics": [],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "Current home of the GenAI semantic conventions — the vocabulary that token and cost telemetry is standardizing on.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 29
    },
    {
      "id": "AHK-0038",
      "slug": "openlit--openlit",
      "url": "https://ai-academic.org/registry/openlit--openlit/",
      "github_repo_id": 747319327,
      "full_name": "openlit/openlit",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/openlit/openlit",
      "archived": false,
      "on_both_hubs": true,
      "category": "human-agent-operations",
      "task": "token-economics-ai-cost",
      "campaigns": [
        {
          "name": "2026-08-01__token-usage-observability-accounting",
          "date": "2026-08-01",
          "claim": "High-coverage, effort-bounded map as of 2026-08-01; not saturated — supports a provider-neutral measurement contract, but the Token Economist may run only as a shadow measurement system until sample-based capture checks pass.",
          "claim_ref": "2026-08-01__token-usage-observability-accounting",
          "scout_citations": 2,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 2676,
        "forks": 350,
        "watchers": 19,
        "language": "TypeScript",
        "license_spdx": "Apache-2.0",
        "created_at": "2024-01-23T17:40:59Z",
        "pushed_at": "2026-08-07T19:42:27Z",
        "topics": [
          "ai-observability",
          "amd-gpu",
          "clickhouse",
          "distributed-tracing",
          "genai",
          "gpu-monitoring",
          "grafana",
          "langchain",
          "llmops",
          "llms",
          "metrics",
          "monitoring-tool",
          "nvidia-smi",
          "observability",
          "open-source",
          "openai",
          "opentelemetry",
          "otlp",
          "python",
          "tracing"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "OpenTelemetry-native tracing and metrics with a model cost registry, in TypeScript.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 30
    },
    {
      "id": "AHK-0039",
      "slug": "traceloop--openllmetry",
      "url": "https://ai-academic.org/registry/traceloop--openllmetry/",
      "github_repo_id": 686364232,
      "full_name": "traceloop/openllmetry",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/traceloop/openllmetry",
      "archived": false,
      "on_both_hubs": true,
      "category": "human-agent-operations",
      "task": "token-economics-ai-cost",
      "campaigns": [
        {
          "name": "2026-08-01__token-usage-observability-accounting",
          "date": "2026-08-01",
          "claim": "High-coverage, effort-bounded map as of 2026-08-01; not saturated — supports a provider-neutral measurement contract, but the Token Economist may run only as a shadow measurement system until sample-based capture checks pass.",
          "claim_ref": "2026-08-01__token-usage-observability-accounting",
          "scout_citations": 2,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 7368,
        "forks": 1047,
        "watchers": 19,
        "language": "Python",
        "license_spdx": "Apache-2.0",
        "created_at": "2023-09-02T14:42:59Z",
        "pushed_at": "2026-08-09T10:06:29Z",
        "topics": [
          "artifical-intelligence",
          "datascience",
          "generative-ai",
          "good-first-issue",
          "good-first-issues",
          "help-wanted",
          "llm",
          "llmops",
          "metrics",
          "ml",
          "model-monitoring",
          "monitoring",
          "observability",
          "open-source",
          "open-telemetry",
          "opentelemetry",
          "opentelemetry-python",
          "python"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "Apache-2.0 OpenTelemetry instrumentations spanning model and agent frameworks.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 31
    },
    {
      "id": "AHK-0040",
      "slug": "annechao--inext",
      "url": "https://ai-academic.org/registry/annechao--inext/",
      "github_repo_id": 530199776,
      "full_name": "AnneChao/iNEXT",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/AnneChao/iNEXT",
      "archived": false,
      "on_both_hubs": false,
      "category": "literature-discovery",
      "task": "calibrate-search-recall",
      "campaigns": [
        {
          "name": "2026-08-03__research-discovery-recall-coverage-calibration",
          "date": "2026-08-03",
          "claim": "High-coverage, effort-bounded map as of 2026-08-03, not saturated (STOP_RESOURCE_CEILING_OPEN_TAILS): adopt auditable frame controls, sequestered sentinels and conjunctive stop protocols; test estimators only on known-answer fixtures; reject any estimator, overlap, count or zero-yield result as a recall certificate.",
          "claim_ref": "2026-08-03__research-discovery-recall-coverage-calibration",
          "scout_citations": 1,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 9,
        "forks": 2,
        "watchers": 1,
        "language": "R",
        "license_spdx": null,
        "created_at": "2022-08-29T11:59:56Z",
        "pushed_at": "2025-07-31T07:59:51Z",
        "topics": [],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "R package for diversity estimation from ecology; admitted as part of the recall-calibration toolkit.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 32
    },
    {
      "id": "AHK-0041",
      "slug": "camaradesuk--asysd",
      "url": "https://ai-academic.org/registry/camaradesuk--asysd/",
      "github_repo_id": 353004916,
      "full_name": "camaradesuk/ASySD",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/camaradesuk/ASySD",
      "archived": false,
      "on_both_hubs": false,
      "category": "literature-discovery",
      "task": "calibrate-search-recall",
      "campaigns": [
        {
          "name": "2026-08-03__research-discovery-recall-coverage-calibration",
          "date": "2026-08-03",
          "claim": "High-coverage, effort-bounded map as of 2026-08-03, not saturated (STOP_RESOURCE_CEILING_OPEN_TAILS): adopt auditable frame controls, sequestered sentinels and conjunctive stop protocols; test estimators only on known-answer fixtures; reject any estimator, overlap, count or zero-yield result as a recall certificate.",
          "claim_ref": "2026-08-03__research-discovery-recall-coverage-calibration",
          "scout_citations": 1,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 23,
        "forks": 6,
        "watchers": 3,
        "language": "HTML",
        "license_spdx": "GPL-3.0",
        "created_at": "2021-03-30T13:08:56Z",
        "pushed_at": "2026-08-07T15:52:00Z",
        "topics": [],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "A deduplication tool for systematic searches, published with its evaluation; recorded as tool-and-evaluation evidence.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 33
    },
    {
      "id": "AHK-0042",
      "slug": "fellstat--shinyrecap",
      "url": "https://ai-academic.org/registry/fellstat--shinyrecap/",
      "github_repo_id": 146911709,
      "full_name": "fellstat/shinyrecap",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/fellstat/shinyrecap",
      "archived": false,
      "on_both_hubs": false,
      "category": "literature-discovery",
      "task": "calibrate-search-recall",
      "campaigns": [
        {
          "name": "2026-08-03__research-discovery-recall-coverage-calibration",
          "date": "2026-08-03",
          "claim": "High-coverage, effort-bounded map as of 2026-08-03, not saturated (STOP_RESOURCE_CEILING_OPEN_TAILS): adopt auditable frame controls, sequestered sentinels and conjunctive stop protocols; test estimators only on known-answer fixtures; reject any estimator, overlap, count or zero-yield result as a recall certificate.",
          "claim_ref": "2026-08-03__research-discovery-recall-coverage-calibration",
          "scout_citations": 1,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 4,
        "forks": 1,
        "watchers": 2,
        "language": "R",
        "license_spdx": "NOASSERTION",
        "created_at": "2018-08-31T15:41:43Z",
        "pushed_at": "2026-07-08T03:58:46Z",
        "topics": [],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "A capture-recapture implementation in R; the campaign uses this method family to estimate what a search did not find.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 34
    },
    {
      "id": "AHK-0043",
      "slug": "nealhaddaway--citationchaser",
      "url": "https://ai-academic.org/registry/nealhaddaway--citationchaser/",
      "github_repo_id": 334349453,
      "full_name": "nealhaddaway/citationchaser",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/nealhaddaway/citationchaser",
      "archived": false,
      "on_both_hubs": false,
      "category": "literature-discovery",
      "task": "calibrate-search-recall",
      "campaigns": [
        {
          "name": "2026-08-03__research-discovery-recall-coverage-calibration",
          "date": "2026-08-03",
          "claim": "High-coverage, effort-bounded map as of 2026-08-03, not saturated (STOP_RESOURCE_CEILING_OPEN_TAILS): adopt auditable frame controls, sequestered sentinels and conjunctive stop protocols; test estimators only on known-answer fixtures; reject any estimator, overlap, count or zero-yield result as a recall certificate.",
          "claim_ref": "2026-08-03__research-discovery-recall-coverage-calibration",
          "scout_citations": 1,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 153,
        "forks": 15,
        "watchers": 5,
        "language": "R",
        "license_spdx": null,
        "created_at": "2021-01-30T06:56:17Z",
        "pushed_at": "2025-03-21T06:43:19Z",
        "topics": [
          "bibliometrics",
          "citation-chasing",
          "evidence-synthesis",
          "information-retrieval",
          "literature-review",
          "meta-analysis",
          "scientometrics",
          "searching",
          "systematic-mapping",
          "systematic-review",
          "systematic-searching"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "R tool for forward and backward citation chasing; admitted as citation-search machinery for recall work.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 35
    },
    {
      "id": "AHK-0044",
      "slug": "allenai--aries",
      "url": "https://ai-academic.org/registry/allenai--aries/",
      "github_repo_id": 655622257,
      "full_name": "allenai/aries",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/allenai/aries",
      "archived": false,
      "on_both_hubs": false,
      "category": "paper-development-review",
      "task": "revise-manuscripts-from-feedback",
      "campaigns": [
        {
          "name": "2026-07-30__feedback-driven-manuscript-revision",
          "date": "2026-07-30",
          "claim": "High-coverage, effort-bounded, not saturated as of 2026-07-30: no single inspected public work supplies the whole feedback-to-document loop, so the strongest design is a supervised orchestrator combining multi-selector comment anchoring with orphan/ambiguity states, editorial diagnosis with global-before-local planning, and small reversible explained proposals under author decision.",
          "claim_ref": "2026-07-30__feedback-driven-manuscript-revision",
          "scout_citations": 2,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 55,
        "forks": 2,
        "watchers": 1,
        "language": "Python",
        "license_spdx": "Apache-2.0",
        "created_at": "2023-06-19T09:09:49Z",
        "pushed_at": "2023-07-05T18:05:09Z",
        "topics": [],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "Dataset and code for aligning reviewer feedback with paper edits; the official form of the ARIES research.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 36
    },
    {
      "id": "AHK-0045",
      "slug": "allenai--peerread",
      "url": "https://ai-academic.org/registry/allenai--peerread/",
      "github_repo_id": 121447308,
      "full_name": "allenai/PeerRead",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/allenai/PeerRead",
      "archived": false,
      "on_both_hubs": false,
      "category": "paper-development-review",
      "task": "revise-manuscripts-from-feedback",
      "campaigns": [
        {
          "name": "2026-07-30__feedback-driven-manuscript-revision",
          "date": "2026-07-30",
          "claim": "High-coverage, effort-bounded, not saturated as of 2026-07-30: no single inspected public work supplies the whole feedback-to-document loop, so the strongest design is a supervised orchestrator combining multi-selector comment anchoring with orphan/ambiguity states, editorial diagnosis with global-before-local planning, and small reversible explained proposals under author decision.",
          "claim_ref": "2026-07-30__feedback-driven-manuscript-revision",
          "scout_citations": 2,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 431,
        "forks": 107,
        "watchers": 25,
        "language": "Python",
        "license_spdx": null,
        "created_at": "2018-02-13T23:06:21Z",
        "pushed_at": "2025-12-09T19:04:36Z",
        "topics": [],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "A public dataset of scientific reviews and drafts; the ledger keeps it with an explicit usage caveat.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 37
    },
    {
      "id": "AHK-0046",
      "slug": "amperser--proselint",
      "url": "https://ai-academic.org/registry/amperser--proselint/",
      "github_repo_id": 29220809,
      "full_name": "amperser/proselint",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/amperser/proselint",
      "archived": false,
      "on_both_hubs": false,
      "category": "paper-development-review",
      "task": "revise-manuscripts-from-feedback",
      "campaigns": [
        {
          "name": "2026-07-30__feedback-driven-manuscript-revision",
          "date": "2026-07-30",
          "claim": "High-coverage, effort-bounded, not saturated as of 2026-07-30: no single inspected public work supplies the whole feedback-to-document loop, so the strongest design is a supervised orchestrator combining multi-selector comment anchoring with orphan/ambiguity states, editorial diagnosis with global-before-local planning, and small reversible explained proposals under author decision.",
          "claim_ref": "2026-07-30__feedback-driven-manuscript-revision",
          "scout_citations": 2,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 4560,
        "forks": 179,
        "watchers": 43,
        "language": "JavaScript",
        "license_spdx": "BSD-3-Clause",
        "created_at": "2015-01-14T01:24:07Z",
        "pushed_at": "2026-08-03T13:41:26Z",
        "topics": [
          "advice",
          "knowledge",
          "language",
          "linter",
          "prose",
          "style",
          "writer"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "A prose linter whose diagnostic schema — line, span, message, replacement — the campaign recorded as revision-pipeline evidence.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 38
    },
    {
      "id": "AHK-0047",
      "slug": "facebookresearch--editeval",
      "url": "https://ai-academic.org/registry/facebookresearch--editeval/",
      "github_repo_id": 542093732,
      "full_name": "facebookresearch/EditEval",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/facebookresearch/EditEval",
      "archived": true,
      "on_both_hubs": false,
      "category": "paper-development-review",
      "task": "revise-manuscripts-from-feedback",
      "campaigns": [
        {
          "name": "2026-07-30__feedback-driven-manuscript-revision",
          "date": "2026-07-30",
          "claim": "High-coverage, effort-bounded, not saturated as of 2026-07-30: no single inspected public work supplies the whole feedback-to-document loop, so the strongest design is a supervised orchestrator combining multi-selector comment anchoring with orphan/ambiguity states, editorial diagnosis with global-before-local planning, and small reversible explained proposals under author decision.",
          "claim_ref": "2026-07-30__feedback-driven-manuscript-revision",
          "scout_citations": 2,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "archived",
      "metrics": {
        "stars": 142,
        "forks": 5,
        "watchers": 1,
        "language": "Python",
        "license_spdx": "CC0-1.0",
        "created_at": "2022-09-27T13:15:35Z",
        "pushed_at": "2022-11-26T20:03:29Z",
        "topics": [],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "Official code and data of the EditEval editing benchmark; archived upstream, kept as the work's record.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 39
    },
    {
      "id": "AHK-0048",
      "slug": "hypothesis--product-backlog",
      "url": "https://ai-academic.org/registry/hypothesis--product-backlog/",
      "github_repo_id": 69482288,
      "full_name": "hypothesis/product-backlog",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/hypothesis/product-backlog",
      "archived": false,
      "on_both_hubs": false,
      "category": "paper-development-review",
      "task": "revise-manuscripts-from-feedback",
      "campaigns": [
        {
          "name": "2026-07-30__feedback-driven-manuscript-revision",
          "date": "2026-07-30",
          "claim": "High-coverage, effort-bounded, not saturated as of 2026-07-30: no single inspected public work supplies the whole feedback-to-document loop, so the strongest design is a supervised orchestrator combining multi-selector comment anchoring with orphan/ambiguity states, editorial diagnosis with global-before-local planning, and small reversible explained proposals under author decision.",
          "claim_ref": "2026-07-30__feedback-driven-manuscript-revision",
          "scout_citations": 2,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 122,
        "forks": 7,
        "watchers": 21,
        "language": null,
        "license_spdx": null,
        "created_at": "2016-09-28T16:27:04Z",
        "pushed_at": "2022-06-06T12:32:25Z",
        "topics": [],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "Issue tracker of an annotation platform; admitted as adverse evidence — it documents where anchoring annotations to changing documents fails.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 40
    },
    {
      "id": "AHK-0049",
      "slug": "onlyoffice--onlyoffice-nextcloud",
      "url": "https://ai-academic.org/registry/onlyoffice--onlyoffice-nextcloud/",
      "github_repo_id": 144824637,
      "full_name": "ONLYOFFICE/onlyoffice-nextcloud",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/ONLYOFFICE/onlyoffice-nextcloud",
      "archived": false,
      "on_both_hubs": false,
      "category": "paper-development-review",
      "task": "revise-manuscripts-from-feedback",
      "campaigns": [
        {
          "name": "2026-07-30__feedback-driven-manuscript-revision",
          "date": "2026-07-30",
          "claim": "High-coverage, effort-bounded, not saturated as of 2026-07-30: no single inspected public work supplies the whole feedback-to-document loop, so the strongest design is a supervised orchestrator combining multi-selector comment anchoring with orphan/ambiguity states, editorial diagnosis with global-before-local planning, and small reversible explained proposals under author decision.",
          "claim_ref": "2026-07-30__feedback-driven-manuscript-revision",
          "scout_citations": 2,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 748,
        "forks": 204,
        "watchers": 32,
        "language": "PHP",
        "license_spdx": "AGPL-3.0",
        "created_at": "2018-08-15T08:08:02Z",
        "pushed_at": "2026-08-04T14:47:43Z",
        "topics": [
          "integration",
          "nextcloud",
          "onlyoffice"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "Integration of a document editor into a collaboration platform; cited for comments and tracked-changes machinery in revision workflows.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 41
    },
    {
      "id": "AHK-0050",
      "slug": "openreview--openreview",
      "url": "https://ai-academic.org/registry/openreview--openreview/",
      "github_repo_id": 370825411,
      "full_name": "openreview/openreview",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/openreview/openreview",
      "archived": false,
      "on_both_hubs": false,
      "category": "paper-development-review",
      "task": "revise-manuscripts-from-feedback",
      "campaigns": [
        {
          "name": "2026-07-30__feedback-driven-manuscript-revision",
          "date": "2026-07-30",
          "claim": "High-coverage, effort-bounded, not saturated as of 2026-07-30: no single inspected public work supplies the whole feedback-to-document loop, so the strongest design is a supervised orchestrator combining multi-selector comment anchoring with orphan/ambiguity states, editorial diagnosis with global-before-local planning, and small reversible explained proposals under author decision.",
          "claim_ref": "2026-07-30__feedback-driven-manuscript-revision",
          "scout_citations": 1,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 34,
        "forks": 6,
        "watchers": 5,
        "language": null,
        "license_spdx": null,
        "created_at": "2021-05-25T20:55:23Z",
        "pushed_at": "2026-08-07T19:54:27Z",
        "topics": [],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "Public documentation of the OpenReview platform; kept as the documentation manifestation of that work.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 42
    },
    {
      "id": "AHK-0051",
      "slug": "readium--annotations",
      "url": "https://ai-academic.org/registry/readium--annotations/",
      "github_repo_id": 854502995,
      "full_name": "readium/annotations",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/readium/annotations",
      "archived": false,
      "on_both_hubs": false,
      "category": "paper-development-review",
      "task": "revise-manuscripts-from-feedback",
      "campaigns": [
        {
          "name": "2026-07-30__feedback-driven-manuscript-revision",
          "date": "2026-07-30",
          "claim": "High-coverage, effort-bounded, not saturated as of 2026-07-30: no single inspected public work supplies the whole feedback-to-document loop, so the strongest design is a supervised orchestrator combining multi-selector comment anchoring with orphan/ambiguity states, editorial diagnosis with global-before-local planning, and small reversible explained proposals under author decision.",
          "claim_ref": "2026-07-30__feedback-driven-manuscript-revision",
          "scout_citations": 2,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 12,
        "forks": 1,
        "watchers": 7,
        "language": "HTML",
        "license_spdx": "BSD-3-Clause",
        "created_at": "2024-09-09T09:39:46Z",
        "pushed_at": "2026-08-04T13:55:24Z",
        "topics": [
          "specification"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "A specification for annotations in digital reading systems; cited for its selector model and exported annotation shape.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 43
    },
    {
      "id": "AHK-0052",
      "slug": "textlint--textlint",
      "url": "https://ai-academic.org/registry/textlint--textlint/",
      "github_repo_id": 28478929,
      "full_name": "textlint/textlint",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/textlint/textlint",
      "archived": false,
      "on_both_hubs": false,
      "category": "paper-development-review",
      "task": "revise-manuscripts-from-feedback",
      "campaigns": [
        {
          "name": "2026-07-30__feedback-driven-manuscript-revision",
          "date": "2026-07-30",
          "claim": "High-coverage, effort-bounded, not saturated as of 2026-07-30: no single inspected public work supplies the whole feedback-to-document loop, so the strongest design is a supervised orchestrator combining multi-selector comment anchoring with orphan/ambiguity states, editorial diagnosis with global-before-local planning, and small reversible explained proposals under author decision.",
          "claim_ref": "2026-07-30__feedback-driven-manuscript-revision",
          "scout_citations": 2,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 3169,
        "forks": 165,
        "watchers": 32,
        "language": "TypeScript",
        "license_spdx": "MIT",
        "created_at": "2014-12-25T10:34:46Z",
        "pushed_at": "2026-08-06T18:48:27Z",
        "topics": [
          "javascript",
          "lint",
          "linter",
          "markdown",
          "natural-language",
          "nlp",
          "textlint"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "Pluggable text linting in TypeScript with fix and dry-run modes; recorded as machinery for controlled language passes.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 44
    },
    {
      "id": "AHK-0053",
      "slug": "vipulraheja--iterater",
      "url": "https://ai-academic.org/registry/vipulraheja--iterater/",
      "github_repo_id": 465049834,
      "full_name": "vipulraheja/iterater",
      "requested_name": "vipulraheja/IteraTeR",
      "successor_slug": null,
      "repo_url": "https://github.com/vipulraheja/iterater",
      "archived": false,
      "on_both_hubs": false,
      "category": "paper-development-review",
      "task": "revise-manuscripts-from-feedback",
      "campaigns": [
        {
          "name": "2026-07-30__feedback-driven-manuscript-revision",
          "date": "2026-07-30",
          "claim": "High-coverage, effort-bounded, not saturated as of 2026-07-30: no single inspected public work supplies the whole feedback-to-document loop, so the strongest design is a supervised orchestrator combining multi-selector comment anchoring with orphan/ambiguity states, editorial diagnosis with global-before-local planning, and small reversible explained proposals under author decision.",
          "claim_ref": "2026-07-30__feedback-driven-manuscript-revision",
          "scout_citations": 2,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 83,
        "forks": 6,
        "watchers": 8,
        "language": "Python",
        "license_spdx": "Apache-2.0",
        "created_at": "2022-03-01T20:41:43Z",
        "pushed_at": "2023-11-15T21:55:06Z",
        "topics": [
          "bart",
          "bert",
          "iterative-text-editing",
          "iterative-text-revision",
          "natural-language-processing",
          "nlp",
          "pegasus",
          "roberta",
          "text-editing",
          "text-revision",
          "transformer",
          "transformers",
          "writing-assistant",
          "writing-systems"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "Shared repository of the IteraTeR iterative text-revision research; the R3 paper points here for its system.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 45
    },
    {
      "id": "AHK-0054",
      "slug": "aimino-tech--opendocswork-mcp",
      "url": "https://ai-academic.org/registry/aimino-tech--opendocswork-mcp/",
      "github_repo_id": 1250280866,
      "full_name": "Aimino-Tech/opendocswork-mcp",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/Aimino-Tech/opendocswork-mcp",
      "archived": false,
      "on_both_hubs": true,
      "category": "presentation-visuals",
      "task": "make-slides-decks-talks",
      "campaigns": [
        {
          "name": "2026-08-01__make-ppt-v2",
          "date": "2026-08-01",
          "claim": "High-coverage, effort-bounded map as of 2026-08-02; not saturated (K=2 unmet, clocks 0/2) — benchmark is specification-only and on HOLD, with 8 unresolved leads and no executed fidelity, export, or round-trip result.",
          "claim_ref": "2026-08-01__make-ppt-v2",
          "scout_citations": 1,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 155,
        "forks": 15,
        "watchers": 1,
        "language": "Rust",
        "license_spdx": "GPL-3.0",
        "created_at": "2026-05-26T13:30:19Z",
        "pushed_at": "2026-06-16T08:49:43Z",
        "topics": [
          "ai-agent",
          "claude",
          "document-processing",
          "excel",
          "llm",
          "mcp-server",
          "model-context-protocol",
          "office-documents",
          "open-source",
          "pdf",
          "powerpoint",
          "rust",
          "word"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "A Rust MCP server for Office documents; the ledger flags its unresolved license.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 46
    },
    {
      "id": "AHK-0055",
      "slug": "barun-saha--slide-deck-ai",
      "url": "https://ai-academic.org/registry/barun-saha--slide-deck-ai/",
      "github_repo_id": 683734054,
      "full_name": "barun-saha/slide-deck-ai",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/barun-saha/slide-deck-ai",
      "archived": false,
      "on_both_hubs": true,
      "category": "presentation-visuals",
      "task": "make-slides-decks-talks",
      "campaigns": [
        {
          "name": "2026-08-01__make-ppt-v2",
          "date": "2026-08-01",
          "claim": "High-coverage, effort-bounded map as of 2026-08-02; not saturated (K=2 unmet, clocks 0/2) — benchmark is specification-only and on HOLD, with 8 unresolved leads and no executed fidelity, export, or round-trip result.",
          "claim_ref": "2026-08-01__make-ppt-v2",
          "scout_citations": 1,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 370,
        "forks": 62,
        "watchers": 2,
        "language": "Python",
        "license_spdx": "MIT",
        "created_at": "2023-08-27T14:35:20Z",
        "pushed_at": "2026-07-26T04:50:20Z",
        "topics": [
          "anthropic",
          "azure-openai",
          "bert",
          "cli",
          "gemini-ai",
          "gemini-api",
          "gemini-flash",
          "generative-ai",
          "hackathon",
          "large-language-models",
          "litellm",
          "llama",
          "ollama",
          "openrouterai",
          "pdf",
          "powerpoint-presentations",
          "pypi",
          "sambanova",
          "streamlit",
          "togetherai"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "Template-based PPTX generation in Python driven by model output.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 47
    },
    {
      "id": "AHK-0056",
      "slug": "digitalartificialint-cmd--citepoint",
      "url": "https://ai-academic.org/registry/digitalartificialint-cmd--citepoint/",
      "github_repo_id": 1227313942,
      "full_name": "digitalartificialint-cmd/CitePoint",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/digitalartificialint-cmd/CitePoint",
      "archived": false,
      "on_both_hubs": true,
      "category": "presentation-visuals",
      "task": "make-slides-decks-talks",
      "campaigns": [
        {
          "name": "2026-08-01__make-ppt-v2",
          "date": "2026-08-01",
          "claim": "High-coverage, effort-bounded map as of 2026-08-02; not saturated (K=2 unmet, clocks 0/2) — benchmark is specification-only and on HOLD, with 8 unresolved leads and no executed fidelity, export, or round-trip result.",
          "claim_ref": "2026-08-01__make-ppt-v2",
          "scout_citations": 1,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 1,
        "forks": 1,
        "watchers": 0,
        "language": "VBA",
        "license_spdx": "MIT",
        "created_at": "2026-05-02T14:08:16Z",
        "pushed_at": "2026-05-02T14:08:47Z",
        "topics": [],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "A VBA add-in that tracks slide-level citations inside PowerPoint.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 48
    },
    {
      "id": "AHK-0057",
      "slug": "gitbrent--pptxgenjs",
      "url": "https://ai-academic.org/registry/gitbrent--pptxgenjs/",
      "github_repo_id": 52322425,
      "full_name": "gitbrent/PptxGenJS",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/gitbrent/PptxGenJS",
      "archived": false,
      "on_both_hubs": true,
      "category": "presentation-visuals",
      "task": "make-slides-decks-talks",
      "campaigns": [
        {
          "name": "2026-08-01__make-ppt-v2",
          "date": "2026-08-01",
          "claim": "High-coverage, effort-bounded map as of 2026-08-02; not saturated (K=2 unmet, clocks 0/2) — benchmark is specification-only and on HOLD, with 8 unresolved leads and no executed fidelity, export, or round-trip result.",
          "claim_ref": "2026-08-01__make-ppt-v2",
          "scout_citations": 1,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 5966,
        "forks": 944,
        "watchers": 77,
        "language": "TypeScript",
        "license_spdx": "MIT",
        "created_at": "2016-02-23T02:15:29Z",
        "pushed_at": "2025-11-28T20:17:14Z",
        "topics": [
          "es6-powerpoint",
          "export-to-pptx",
          "html-to-powerpoint",
          "javascript",
          "javascript-powerpoint",
          "node-powerpoint",
          "officejs-alternative",
          "powerpoint",
          "powerpoint-generation",
          "powerpoint-library",
          "powerpoint-presentations",
          "pptx",
          "pptxgenjs",
          "presentation-library",
          "react-powerpoint",
          "slide-generator",
          "typescript-powerpoint"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "TypeScript library for programmatic PPTX generation via OOXML.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 49
    },
    {
      "id": "AHK-0058",
      "slug": "hkuds--paper2slides",
      "url": "https://ai-academic.org/registry/hkuds--paper2slides/",
      "github_repo_id": 1111537966,
      "full_name": "HKUDS/Paper2Slides",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/HKUDS/Paper2Slides",
      "archived": false,
      "on_both_hubs": true,
      "category": "presentation-visuals",
      "task": "make-slides-decks-talks",
      "campaigns": [
        {
          "name": "2026-08-01__make-ppt-v2",
          "date": "2026-08-01",
          "claim": "High-coverage, effort-bounded map as of 2026-08-02; not saturated (K=2 unmet, clocks 0/2) — benchmark is specification-only and on HOLD, with 8 unresolved leads and no executed fidelity, export, or round-trip result.",
          "claim_ref": "2026-08-01__make-ppt-v2",
          "scout_citations": 1,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 3815,
        "forks": 473,
        "watchers": 29,
        "language": "Python",
        "license_spdx": "MIT",
        "created_at": "2025-12-07T06:15:43Z",
        "pushed_at": "2026-05-20T09:08:14Z",
        "topics": [
          "agentic-ai",
          "llm-agents",
          "paper2poster",
          "paper2slides"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "Paper-to-slides generation research; admitted as a negative case — output slides render as images, which the campaign distinguishes from editable decks.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 50
    },
    {
      "id": "AHK-0059",
      "slug": "iofficeai--officecli",
      "url": "https://ai-academic.org/registry/iofficeai--officecli/",
      "github_repo_id": 1182212878,
      "full_name": "iOfficeAI/OfficeCLI",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/iOfficeAI/OfficeCLI",
      "archived": false,
      "on_both_hubs": true,
      "category": "presentation-visuals",
      "task": "make-slides-decks-talks",
      "campaigns": [
        {
          "name": "2026-08-01__make-ppt-v2",
          "date": "2026-08-01",
          "claim": "High-coverage, effort-bounded map as of 2026-08-02; not saturated (K=2 unmet, clocks 0/2) — benchmark is specification-only and on HOLD, with 8 unresolved leads and no executed fidelity, export, or round-trip result.",
          "claim_ref": "2026-08-01__make-ppt-v2",
          "scout_citations": 1,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 27037,
        "forks": 1839,
        "watchers": 78,
        "language": "C#",
        "license_spdx": "Apache-2.0",
        "created_at": "2026-03-15T07:39:12Z",
        "pushed_at": "2026-08-04T13:15:13Z",
        "topics": [
          "agent",
          "ai",
          "claude-code",
          "cli",
          "codex",
          "docx",
          "excel",
          "office",
          "openclaw",
          "pptx",
          "presentation",
          "skills",
          "word",
          "xlsx"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "A C# command-line tool for semantic Office-document operations.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 51
    },
    {
      "id": "AHK-0060",
      "slug": "kdnsna--pptlint",
      "url": "https://ai-academic.org/registry/kdnsna--pptlint/",
      "github_repo_id": 1297302692,
      "full_name": "kdnsna/pptlint",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/kdnsna/pptlint",
      "archived": false,
      "on_both_hubs": true,
      "category": "presentation-visuals",
      "task": "make-slides-decks-talks",
      "campaigns": [
        {
          "name": "2026-08-01__make-ppt-v2",
          "date": "2026-08-01",
          "claim": "High-coverage, effort-bounded map as of 2026-08-02; not saturated (K=2 unmet, clocks 0/2) — benchmark is specification-only and on HOLD, with 8 unresolved leads and no executed fidelity, export, or round-trip result.",
          "claim_ref": "2026-08-01__make-ppt-v2",
          "scout_citations": 1,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 2,
        "forks": 0,
        "watchers": 0,
        "language": "HTML",
        "license_spdx": "MIT",
        "created_at": "2026-07-11T09:24:06Z",
        "pushed_at": "2026-07-14T04:06:16Z",
        "topics": [
          "ai-slides",
          "checker",
          "github-actions",
          "linter",
          "local-first",
          "office-open-xml",
          "powerpoint",
          "ppt",
          "pptx",
          "presentation"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "Structural linting for PPTX files with a visual-attestation gate, wired for CI use.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 52
    },
    {
      "id": "AHK-0061",
      "slug": "kdnsna--ultimate-ppt-master-skill",
      "url": "https://ai-academic.org/registry/kdnsna--ultimate-ppt-master-skill/",
      "github_repo_id": 1221560860,
      "full_name": "kdnsna/ultimate-ppt-master-skill",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/kdnsna/ultimate-ppt-master-skill",
      "archived": false,
      "on_both_hubs": true,
      "category": "presentation-visuals",
      "task": "make-slides-decks-talks",
      "campaigns": [
        {
          "name": "2026-08-01__make-ppt-v2",
          "date": "2026-08-01",
          "claim": "High-coverage, effort-bounded map as of 2026-08-02; not saturated (K=2 unmet, clocks 0/2) — benchmark is specification-only and on HOLD, with 8 unresolved leads and no executed fidelity, export, or round-trip result.",
          "claim_ref": "2026-08-01__make-ppt-v2",
          "scout_citations": 1,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 1,
        "forks": 0,
        "watchers": 0,
        "language": "Python",
        "license_spdx": "MIT",
        "created_at": "2026-04-26T11:35:36Z",
        "pushed_at": "2026-08-07T15:38:19Z",
        "topics": [
          "agent-skill",
          "ai-ppt",
          "ai-presentation",
          "codex",
          "document-conversion",
          "editable-pptx",
          "gpt-image-generation",
          "html-to-pptx",
          "local-first",
          "office-productivity",
          "powerpoint",
          "pptx",
          "pptx-generator",
          "presentation",
          "presentation-design",
          "presentation-generator",
          "presentation-tool",
          "quality-assurance",
          "slides",
          "web-deck"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "An agent skill for targeted PPTX edits that preserves the surrounding package.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 53
    },
    {
      "id": "AHK-0062",
      "slug": "officecli--officecli",
      "url": "https://ai-academic.org/registry/officecli--officecli/",
      "github_repo_id": 1198229219,
      "full_name": "officecli/officecli",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/officecli/officecli",
      "archived": false,
      "on_both_hubs": true,
      "category": "presentation-visuals",
      "task": "make-slides-decks-talks",
      "campaigns": [
        {
          "name": "2026-08-01__make-ppt-v2",
          "date": "2026-08-01",
          "claim": "High-coverage, effort-bounded map as of 2026-08-02; not saturated (K=2 unmet, clocks 0/2) — benchmark is specification-only and on HOLD, with 8 unresolved leads and no executed fidelity, export, or round-trip result.",
          "claim_ref": "2026-08-01__make-ppt-v2",
          "scout_citations": 1,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 87,
        "forks": 7,
        "watchers": 0,
        "language": "Shell",
        "license_spdx": "MIT",
        "created_at": "2026-04-01T08:24:42Z",
        "pushed_at": "2026-06-12T03:01:51Z",
        "topics": [
          "ai",
          "ai-agents",
          "ai-document-generator",
          "automation",
          "claude-code",
          "cli",
          "codex",
          "developer-tools",
          "document-automation",
          "docx",
          "image-generation",
          "local-first",
          "npm",
          "office-documents",
          "officecli",
          "openclaw",
          "powerpoint",
          "pptx",
          "report-generation",
          "xlsx"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "A shell-based Office document CLI with an optional hosted service; distinct from the similarly named C# tool, and listed separately.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 54
    },
    {
      "id": "AHK-0063",
      "slug": "scanny--python-pptx",
      "url": "https://ai-academic.org/registry/scanny--python-pptx/",
      "github_repo_id": 6794278,
      "full_name": "scanny/python-pptx",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/scanny/python-pptx",
      "archived": false,
      "on_both_hubs": true,
      "category": "presentation-visuals",
      "task": "make-slides-decks-talks",
      "campaigns": [
        {
          "name": "2026-08-01__make-ppt-v2",
          "date": "2026-08-01",
          "claim": "High-coverage, effort-bounded map as of 2026-08-02; not saturated (K=2 unmet, clocks 0/2) — benchmark is specification-only and on HOLD, with 8 unresolved leads and no executed fidelity, export, or round-trip result.",
          "claim_ref": "2026-08-01__make-ppt-v2",
          "scout_citations": 1,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 3484,
        "forks": 731,
        "watchers": 77,
        "language": "Python",
        "license_spdx": "MIT",
        "created_at": "2012-11-21T11:03:31Z",
        "pushed_at": "2024-08-07T17:36:44Z",
        "topics": [],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "The Python OOXML library for creating and partially editing PPTX decks.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 55
    },
    {
      "id": "AHK-0064",
      "slug": "tristan-mcinnis--pptx-from-layouts-skill",
      "url": "https://ai-academic.org/registry/tristan-mcinnis--pptx-from-layouts-skill/",
      "github_repo_id": 1146536591,
      "full_name": "tristan-mcinnis/pptx-from-layouts-skill",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/tristan-mcinnis/pptx-from-layouts-skill",
      "archived": false,
      "on_both_hubs": true,
      "category": "presentation-visuals",
      "task": "make-slides-decks-talks",
      "campaigns": [
        {
          "name": "2026-08-01__make-ppt-v2",
          "date": "2026-08-01",
          "claim": "High-coverage, effort-bounded map as of 2026-08-02; not saturated (K=2 unmet, clocks 0/2) — benchmark is specification-only and on HOLD, with 8 unresolved leads and no executed fidelity, export, or round-trip result.",
          "claim_ref": "2026-08-01__make-ppt-v2",
          "scout_citations": 1,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 15,
        "forks": 2,
        "watchers": 0,
        "language": "Python",
        "license_spdx": "MIT",
        "created_at": "2026-01-31T08:55:06Z",
        "pushed_at": "2026-06-03T03:36:40Z",
        "topics": [
          "agents",
          "ai",
          "claude",
          "claude-code",
          "codex",
          "openai",
          "opencode",
          "powerpoint",
          "pptx",
          "pptx-generator",
          "pptx-parser",
          "presentation-slides",
          "python",
          "skill",
          "skills"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "An agent skill that profiles a deck's template and selects layouts semantically before writing slides.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 56
    },
    {
      "id": "AHK-0065",
      "slug": "wozzeck16621--pptx-from-layouts-skill",
      "url": "https://ai-academic.org/registry/wozzeck16621--pptx-from-layouts-skill/",
      "github_repo_id": null,
      "full_name": "wozzeck16621/pptx-from-layouts-skill",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": null,
      "archived": false,
      "on_both_hubs": true,
      "category": "presentation-visuals",
      "task": "make-slides-decks-talks",
      "campaigns": [
        {
          "name": "2026-08-01__make-ppt-v2",
          "date": "2026-08-01",
          "claim": "High-coverage, effort-bounded map as of 2026-08-02; not saturated (K=2 unmet, clocks 0/2) — benchmark is specification-only and on HOLD, with 8 unresolved leads and no executed fidelity, export, or round-trip result.",
          "claim_ref": "2026-08-01__make-ppt-v2",
          "scout_citations": 1,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "unavailable",
      "metrics": {
        "stars": null,
        "forks": null,
        "watchers": null,
        "language": null,
        "license_spdx": null,
        "created_at": null,
        "pushed_at": null,
        "topics": [],
        "http_status": 404,
        "snapshot_date": "2026-08-10"
      },
      "description": "A template-layout PowerPoint skill. This namespace did not resolve at the 2026-08-10 snapshot (HTTP 404); the entry stays as a dated event.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 57
    },
    {
      "id": "AHK-0066",
      "slug": "xiaozhou2024--slideagent",
      "url": "https://ai-academic.org/registry/xiaozhou2024--slideagent/",
      "github_repo_id": 1043104253,
      "full_name": "XiaoZhou2024/SlideAgent",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/XiaoZhou2024/SlideAgent",
      "archived": false,
      "on_both_hubs": true,
      "category": "presentation-visuals",
      "task": "make-slides-decks-talks",
      "campaigns": [
        {
          "name": "2026-08-01__make-ppt-v2",
          "date": "2026-08-01",
          "claim": "High-coverage, effort-bounded map as of 2026-08-02; not saturated (K=2 unmet, clocks 0/2) — benchmark is specification-only and on HOLD, with 8 unresolved leads and no executed fidelity, export, or round-trip result.",
          "claim_ref": "2026-08-01__make-ppt-v2",
          "scout_citations": 1,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 5,
        "forks": 0,
        "watchers": 0,
        "language": "Python",
        "license_spdx": null,
        "created_at": "2025-08-23T06:31:46Z",
        "pushed_at": "2026-01-09T03:28:05Z",
        "topics": [],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "Research code for slide-generation and slide-editing agents.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 58
    },
    {
      "id": "AHK-0067",
      "slug": "ykuwai--ppt-mcp",
      "url": "https://ai-academic.org/registry/ykuwai--ppt-mcp/",
      "github_repo_id": 1159140448,
      "full_name": "ykuwai/ppt-mcp",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/ykuwai/ppt-mcp",
      "archived": false,
      "on_both_hubs": true,
      "category": "presentation-visuals",
      "task": "make-slides-decks-talks",
      "campaigns": [
        {
          "name": "2026-08-01__make-ppt-v2",
          "date": "2026-08-01",
          "claim": "High-coverage, effort-bounded map as of 2026-08-02; not saturated (K=2 unmet, clocks 0/2) — benchmark is specification-only and on HOLD, with 8 unresolved leads and no executed fidelity, export, or round-trip result.",
          "claim_ref": "2026-08-01__make-ppt-v2",
          "scout_citations": 1,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 51,
        "forks": 10,
        "watchers": 0,
        "language": "Python",
        "license_spdx": null,
        "created_at": "2026-02-16T11:15:49Z",
        "pushed_at": "2026-08-03T23:52:50Z",
        "topics": [],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "A PPTX MCP server; admitted as adverse evidence for a display-versus-export mismatch with CJK text.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 59
    },
    {
      "id": "AHK-0068",
      "slug": "franklee16--hbs-case-writer",
      "url": "https://ai-academic.org/registry/franklee16--hbs-case-writer/",
      "github_repo_id": 1216995176,
      "full_name": "franklee16/hbs-case-writer",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/franklee16/hbs-case-writer",
      "archived": false,
      "on_both_hubs": false,
      "category": "teaching",
      "task": "engineer-teaching-cases",
      "campaigns": [
        {
          "name": "2026-08-03__teaching-case-teaching-note-engineering",
          "date": "2026-08-03",
          "claim": "High-coverage, effort-bounded public-evidence map as of 2026-08-03 with stop clock 0/2 (no plateau, not saturated, AWAITING_INDEPENDENT_QA): build an in-house typed case/teaching-note alignment and acceptance layer, since no located public work implements and validates the full target graph end to end.",
          "claim_ref": "2026-08-03__teaching-case-teaching-note-engineering",
          "scout_citations": 2,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 22,
        "forks": 7,
        "watchers": 2,
        "language": "Python",
        "license_spdx": null,
        "created_at": "2026-04-21T12:46:45Z",
        "pushed_at": "2026-06-27T01:25:45Z",
        "topics": [],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "A case-writing skill with templates and sourcing instructions, found by the campaign's focused-tool backstop.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 60
    },
    {
      "id": "AHK-0069",
      "slug": "opencasestudies--ocs-template-quarto",
      "url": "https://ai-academic.org/registry/opencasestudies--ocs-template-quarto/",
      "github_repo_id": 1062064505,
      "full_name": "opencasestudies/ocs-template-quarto",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/opencasestudies/ocs-template-quarto",
      "archived": false,
      "on_both_hubs": false,
      "category": "teaching",
      "task": "engineer-teaching-cases",
      "campaigns": [
        {
          "name": "2026-08-03__teaching-case-teaching-note-engineering",
          "date": "2026-08-03",
          "claim": "High-coverage, effort-bounded public-evidence map as of 2026-08-03 with stop clock 0/2 (no plateau, not saturated, AWAITING_INDEPENDENT_QA): build an in-house typed case/teaching-note alignment and acceptance layer, since no located public work implements and validates the full target graph end to end.",
          "claim_ref": "2026-08-03__teaching-case-teaching-note-engineering",
          "scout_citations": 2,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 0,
        "forks": 0,
        "watchers": 0,
        "language": "CSS",
        "license_spdx": "MIT",
        "created_at": "2025-09-22T18:56:11Z",
        "pushed_at": "2026-08-05T21:45:03Z",
        "topics": [],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "Quarto template from the Open Case Studies project; typed front matter running from context and objectives through ethics.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 61
    },
    {
      "id": "AHK-0070",
      "slug": "opencasestudies--ocs_guide",
      "url": "https://ai-academic.org/registry/opencasestudies--ocs_guide/",
      "github_repo_id": 439446629,
      "full_name": "opencasestudies/OCS_Guide",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/opencasestudies/OCS_Guide",
      "archived": false,
      "on_both_hubs": false,
      "category": "teaching",
      "task": "engineer-teaching-cases",
      "campaigns": [
        {
          "name": "2026-08-03__teaching-case-teaching-note-engineering",
          "date": "2026-08-03",
          "claim": "High-coverage, effort-bounded public-evidence map as of 2026-08-03 with stop clock 0/2 (no plateau, not saturated, AWAITING_INDEPENDENT_QA): build an in-house typed case/teaching-note alignment and acceptance layer, since no located public work implements and validates the full target graph end to end.",
          "claim_ref": "2026-08-03__teaching-case-teaching-note-engineering",
          "scout_citations": 2,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 2,
        "forks": 2,
        "watchers": 4,
        "language": "CSS",
        "license_spdx": "CC-BY-4.0",
        "created_at": "2021-12-17T20:01:58Z",
        "pushed_at": "2025-06-06T19:41:45Z",
        "topics": [],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "The Open Case Studies guide: contribution, review and learning-objective tagging conventions for teaching cases.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 62
    },
    {
      "id": "AHK-0071",
      "slug": "opendesigncasestudies--odcs-template",
      "url": "https://ai-academic.org/registry/opendesigncasestudies--odcs-template/",
      "github_repo_id": 539507967,
      "full_name": "opendesigncasestudies/odcs-template",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/opendesigncasestudies/odcs-template",
      "archived": false,
      "on_both_hubs": false,
      "category": "teaching",
      "task": "engineer-teaching-cases",
      "campaigns": [
        {
          "name": "2026-08-03__teaching-case-teaching-note-engineering",
          "date": "2026-08-03",
          "claim": "High-coverage, effort-bounded public-evidence map as of 2026-08-03 with stop clock 0/2 (no plateau, not saturated, AWAITING_INDEPENDENT_QA): build an in-house typed case/teaching-note alignment and acceptance layer, since no located public work implements and validates the full target graph end to end.",
          "claim_ref": "2026-08-03__teaching-case-teaching-note-engineering",
          "scout_citations": 2,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 2,
        "forks": 0,
        "watchers": 1,
        "language": null,
        "license_spdx": null,
        "created_at": "2022-09-21T13:39:31Z",
        "pushed_at": "2022-10-10T08:21:42Z",
        "topics": [],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "A design-case template covering stakeholders, constraints, outcomes and teaching materials.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 63
    },
    {
      "id": "AHK-0072",
      "slug": "allenai--asta-theorizer",
      "url": "https://ai-academic.org/registry/allenai--asta-theorizer/",
      "github_repo_id": 1130697863,
      "full_name": "allenai/asta-theorizer",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/allenai/asta-theorizer",
      "archived": false,
      "on_both_hubs": false,
      "category": "theorization",
      "task": "build-theory",
      "campaigns": [
        {
          "name": "2026-07-28__theory-building",
          "date": "2026-07-28",
          "claim": "A high-coverage, effort-bounded, not-saturated English-primary map: doctrine and venue rubrics are plentiful but venue-specific, while machinery is fragmented — no validated end-to-end public theory-building engine, no mode-balanced benchmark, and weak evidence for automated theory judging.",
          "claim_ref": "2026-07-28__theory-building",
          "scout_citations": 3,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 170,
        "forks": 22,
        "watchers": 2,
        "language": "HTML",
        "license_spdx": "Apache-2.0",
        "created_at": "2026-01-08T22:00:58Z",
        "pushed_at": "2026-05-02T04:23:26Z",
        "topics": [],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "Public code, schemas and prompts for a theorizing assistant; the ledger cites its documentation and evaluation paths.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 64
    },
    {
      "id": "AHK-0073",
      "slug": "bear96--system-dynamics-bot",
      "url": "https://ai-academic.org/registry/bear96--system-dynamics-bot/",
      "github_repo_id": 807188847,
      "full_name": "bear96/System-Dynamics-Bot",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/bear96/System-Dynamics-Bot",
      "archived": false,
      "on_both_hubs": false,
      "category": "theorization",
      "task": "build-theory",
      "campaigns": [
        {
          "name": "2026-07-28__theory-building",
          "date": "2026-07-28",
          "claim": "A high-coverage, effort-bounded, not-saturated English-primary map: doctrine and venue rubrics are plentiful but venue-specific, while machinery is fragmented — no validated end-to-end public theory-building engine, no mode-balanced benchmark, and weak evidence for automated theory judging.",
          "claim_ref": "2026-07-28__theory-building",
          "scout_citations": 1,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 20,
        "forks": 9,
        "watchers": 5,
        "language": "Python",
        "license_spdx": "NOASSERTION",
        "created_at": "2024-05-28T16:16:21Z",
        "pushed_at": "2024-10-12T14:58:26Z",
        "topics": [],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "Research code turning problem descriptions into system-dynamics models; code, paper link and requirements are on the record.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 65
    },
    {
      "id": "AHK-0074",
      "slug": "brycewang-stanford--awesome-journal-skills",
      "url": "https://ai-academic.org/registry/brycewang-stanford--awesome-journal-skills/",
      "github_repo_id": 1248879346,
      "full_name": "brycewang-stanford/Awesome-Journal-Skills",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/brycewang-stanford/Awesome-Journal-Skills",
      "archived": false,
      "on_both_hubs": false,
      "category": "theorization",
      "task": "build-theory",
      "campaigns": [
        {
          "name": "2026-07-28__theory-building",
          "date": "2026-07-28",
          "claim": "A high-coverage, effort-bounded, not-saturated English-primary map: doctrine and venue rubrics are plentiful but venue-specific, while machinery is fragmented — no validated end-to-end public theory-building engine, no mode-balanced benchmark, and weak evidence for automated theory judging.",
          "claim_ref": "2026-07-28__theory-building",
          "scout_citations": 3,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 965,
        "forks": 121,
        "watchers": 3,
        "language": "Stata",
        "license_spdx": "MIT",
        "created_at": "2026-05-25T06:19:56Z",
        "pushed_at": "2026-08-09T10:24:51Z",
        "topics": [
          "academic-research",
          "academic-writing",
          "agent-skills",
          "ai-agents",
          "anthropic",
          "awesome-list",
          "causal-inference",
          "claude",
          "claude-code",
          "econometrics",
          "economics",
          "empirical-research",
          "finance",
          "journal",
          "llm",
          "mcp",
          "peer-review",
          "replication",
          "research-tools",
          "scholarly-publishing"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "A journal-targeted skill pack with a puzzle-to-positioning workflow and proposition templates, written for Stata users.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 66
    },
    {
      "id": "AHK-0075",
      "slug": "cjvanlissa--theorytools",
      "url": "https://ai-academic.org/registry/cjvanlissa--theorytools/",
      "github_repo_id": 909294095,
      "full_name": "cjvanlissa/theorytools",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/cjvanlissa/theorytools",
      "archived": false,
      "on_both_hubs": false,
      "category": "theorization",
      "task": "build-theory",
      "campaigns": [
        {
          "name": "2026-07-28__theory-building",
          "date": "2026-07-28",
          "claim": "A high-coverage, effort-bounded, not-saturated English-primary map: doctrine and venue rubrics are plentiful but venue-specific, while machinery is fragmented — no validated end-to-end public theory-building engine, no mode-balanced benchmark, and weak evidence for automated theory judging.",
          "claim_ref": "2026-07-28__theory-building",
          "scout_citations": 3,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 6,
        "forks": 3,
        "watchers": 2,
        "language": "R",
        "license_spdx": null,
        "created_at": "2024-12-28T09:14:19Z",
        "pushed_at": "2026-02-07T08:57:41Z",
        "topics": [],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "R package for formalizing theory as a directed graph; its GitHub and CRAN forms are recorded as one work.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 67
    },
    {
      "id": "AHK-0076",
      "slug": "limyoyo--utd-skills",
      "url": "https://ai-academic.org/registry/limyoyo--utd-skills/",
      "github_repo_id": 1249180378,
      "full_name": "LIMYOYO/utd-skills",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/LIMYOYO/utd-skills",
      "archived": false,
      "on_both_hubs": false,
      "category": "theorization",
      "task": "build-theory",
      "campaigns": [
        {
          "name": "2026-07-28__theory-building",
          "date": "2026-07-28",
          "claim": "A high-coverage, effort-bounded, not-saturated English-primary map: doctrine and venue rubrics are plentiful but venue-specific, while machinery is fragmented — no validated end-to-end public theory-building engine, no mode-balanced benchmark, and weak evidence for automated theory judging.",
          "claim_ref": "2026-07-28__theory-building",
          "scout_citations": 3,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 2,
        "forks": 0,
        "watchers": 0,
        "language": null,
        "license_spdx": "MIT",
        "created_at": "2026-05-25T12:37:42Z",
        "pushed_at": "2026-05-25T12:37:46Z",
        "topics": [],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "A skill set documenting a construct-map to mechanism to hypothesis workflow for theory development.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 68
    },
    {
      "id": "AHK-0077",
      "slug": "allenai--olmocr",
      "url": "https://ai-academic.org/registry/allenai--olmocr/",
      "github_repo_id": 858798469,
      "full_name": "allenai/olmocr",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/allenai/olmocr",
      "archived": false,
      "on_both_hubs": true,
      "category": "tools-document-processing",
      "task": "parse-pdfs-documents",
      "campaigns": [
        {
          "name": "2026-07-28__pdf-parsers",
          "date": "2026-07-28",
          "claim": "A high-coverage, effort-bounded map as of 2026-07-28 ranking five Apple-plausible local parsers (Marker v2 first, medium confidence); the coverage gate is NOT MET, no global winner or recall proof is asserted, no candidate was installed or executed, and multilingual support earned zero credit.",
          "claim_ref": "2026-07-28__pdf-parsers",
          "scout_citations": 2,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 19284,
        "forks": 1594,
        "watchers": 102,
        "language": "Python",
        "license_spdx": "Apache-2.0",
        "created_at": "2024-09-17T14:53:40Z",
        "pushed_at": "2026-03-25T17:52:37Z",
        "topics": [],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "OCR pipeline for scans and multicolumn documents with natural reading-order output; the ledger tempers it with local-setup caveats.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 69
    },
    {
      "id": "AHK-0078",
      "slug": "datalab-to--chandra",
      "url": "https://ai-academic.org/registry/datalab-to--chandra/",
      "github_repo_id": 1072539730,
      "full_name": "datalab-to/chandra",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/datalab-to/chandra",
      "archived": false,
      "on_both_hubs": true,
      "category": "tools-document-processing",
      "task": "parse-pdfs-documents",
      "campaigns": [
        {
          "name": "2026-07-28__pdf-parsers",
          "date": "2026-07-28",
          "claim": "A high-coverage, effort-bounded map as of 2026-07-28 ranking five Apple-plausible local parsers (Marker v2 first, medium confidence); the coverage gate is NOT MET, no global winner or recall proof is asserted, no candidate was installed or executed, and multilingual support earned zero credit.",
          "claim_ref": "2026-07-28__pdf-parsers",
          "scout_citations": 2,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 12012,
        "forks": 1226,
        "watchers": 86,
        "language": "Python",
        "license_spdx": "Apache-2.0",
        "created_at": "2025-10-08T21:34:16Z",
        "pushed_at": "2026-06-26T10:26:47Z",
        "topics": [
          "ai",
          "ocr"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "An OCR model aimed at regulated documents, with open local weights; the ledger's Apple-feasibility caveats travel with it.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 70
    },
    {
      "id": "AHK-0079",
      "slug": "datalab-to--marker",
      "url": "https://ai-academic.org/registry/datalab-to--marker/",
      "github_repo_id": 712111618,
      "full_name": "datalab-to/marker",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/datalab-to/marker",
      "archived": false,
      "on_both_hubs": true,
      "category": "tools-document-processing",
      "task": "parse-pdfs-documents",
      "campaigns": [
        {
          "name": "2026-07-28__pdf-parsers",
          "date": "2026-07-28",
          "claim": "A high-coverage, effort-bounded map as of 2026-07-28 ranking five Apple-plausible local parsers (Marker v2 first, medium confidence); the coverage gate is NOT MET, no global winner or recall proof is asserted, no candidate was installed or executed, and multilingual support earned zero credit.",
          "claim_ref": "2026-07-28__pdf-parsers",
          "scout_citations": 3,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 38588,
        "forks": 2749,
        "watchers": 135,
        "language": "Python",
        "license_spdx": "Apache-2.0",
        "created_at": "2023-10-30T20:14:08Z",
        "pushed_at": "2026-08-07T06:33:06Z",
        "topics": [],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "Document conversion with hybrid native and OCR routing, JSON polygons, and Apple CPU/MPS defaults.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 71
    },
    {
      "id": "AHK-0080",
      "slug": "datalab-to--surya",
      "url": "https://ai-academic.org/registry/datalab-to--surya/",
      "github_repo_id": 741297064,
      "full_name": "datalab-to/surya",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/datalab-to/surya",
      "archived": false,
      "on_both_hubs": true,
      "category": "tools-document-processing",
      "task": "parse-pdfs-documents",
      "campaigns": [
        {
          "name": "2026-07-28__pdf-parsers",
          "date": "2026-07-28",
          "claim": "A high-coverage, effort-bounded map as of 2026-07-28 ranking five Apple-plausible local parsers (Marker v2 first, medium confidence); the coverage gate is NOT MET, no global winner or recall proof is asserted, no candidate was installed or executed, and multilingual support earned zero credit.",
          "claim_ref": "2026-07-28__pdf-parsers",
          "scout_citations": 4,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 21234,
        "forks": 1524,
        "watchers": 126,
        "language": "Python",
        "license_spdx": "Apache-2.0",
        "created_at": "2024-01-10T05:17:42Z",
        "pushed_at": "2026-07-23T07:30:19Z",
        "topics": [],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "OCR and layout components producing line boxes, polygons and reading order; cited four times in the parsing ledger.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 72
    },
    {
      "id": "AHK-0081",
      "slug": "docling-project--docling",
      "url": "https://ai-academic.org/registry/docling-project--docling/",
      "github_repo_id": 826168160,
      "full_name": "docling-project/docling",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/docling-project/docling",
      "archived": false,
      "on_both_hubs": true,
      "category": "tools-document-processing",
      "task": "parse-pdfs-documents",
      "campaigns": [
        {
          "name": "2026-07-28__pdf-parsers",
          "date": "2026-07-28",
          "claim": "A high-coverage, effort-bounded map as of 2026-07-28 ranking five Apple-plausible local parsers (Marker v2 first, medium confidence); the coverage gate is NOT MET, no global winner or recall proof is asserted, no candidate was installed or executed, and multilingual support earned zero credit.",
          "claim_ref": "2026-07-28__pdf-parsers",
          "scout_citations": 3,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 64459,
        "forks": 4583,
        "watchers": 224,
        "language": "Python",
        "license_spdx": "MIT",
        "created_at": "2024-07-09T07:50:26Z",
        "pushed_at": "2026-08-08T06:02:29Z",
        "topics": [
          "ai",
          "convert",
          "document-parser",
          "document-parsing",
          "documents",
          "docx",
          "html",
          "markdown",
          "pdf",
          "pdf-converter",
          "pdf-to-json",
          "pdf-to-text",
          "pptx",
          "tables",
          "xlsx"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "A permissively licensed document-parsing SDK with provenance boxes and offline operation.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 73
    },
    {
      "id": "AHK-0082",
      "slug": "opendatalab--mineru",
      "url": "https://ai-academic.org/registry/opendatalab--mineru/",
      "github_repo_id": 765083837,
      "full_name": "opendatalab/MinerU",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/opendatalab/MinerU",
      "archived": false,
      "on_both_hubs": true,
      "category": "tools-document-processing",
      "task": "parse-pdfs-documents",
      "campaigns": [
        {
          "name": "2026-07-28__pdf-parsers",
          "date": "2026-07-28",
          "claim": "A high-coverage, effort-bounded map as of 2026-07-28 ranking five Apple-plausible local parsers (Marker v2 first, medium confidence); the coverage gate is NOT MET, no global winner or recall proof is asserted, no candidate was installed or executed, and multilingual support earned zero credit.",
          "claim_ref": "2026-07-28__pdf-parsers",
          "scout_citations": 3,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 77208,
        "forks": 6498,
        "watchers": 273,
        "language": "Python",
        "license_spdx": "NOASSERTION",
        "created_at": "2024-02-29T08:52:34Z",
        "pushed_at": "2026-08-08T09:05:30Z",
        "topics": [
          "ai4science",
          "document-analysis",
          "docx",
          "extract-data",
          "layout-analysis",
          "ocr",
          "parser",
          "pdf",
          "pdf-converter",
          "pdf-extractor-llm",
          "pdf-extractor-pretrain",
          "pdf-extractor-rag",
          "pdf-parser",
          "pptx",
          "python",
          "xlsx"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "Document parser with coordinate-bearing JSON output and an official Apple path; recorded as the incumbent in this campaign's ledger.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 74
    },
    {
      "id": "AHK-0083",
      "slug": "opendatalab--omnidocbench",
      "url": "https://ai-academic.org/registry/opendatalab--omnidocbench/",
      "github_repo_id": 872227315,
      "full_name": "opendatalab/OmniDocBench",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/opendatalab/OmniDocBench",
      "archived": false,
      "on_both_hubs": true,
      "category": "tools-document-processing",
      "task": "parse-pdfs-documents",
      "campaigns": [
        {
          "name": "2026-07-28__pdf-parsers",
          "date": "2026-07-28",
          "claim": "A high-coverage, effort-bounded map as of 2026-07-28 ranking five Apple-plausible local parsers (Marker v2 first, medium confidence); the coverage gate is NOT MET, no global winner or recall proof is asserted, no candidate was installed or executed, and multilingual support earned zero credit.",
          "claim_ref": "2026-07-28__pdf-parsers",
          "scout_citations": 7,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 1959,
        "forks": 191,
        "watchers": 12,
        "language": "Python",
        "license_spdx": "Apache-2.0",
        "created_at": "2024-10-14T04:16:25Z",
        "pushed_at": "2026-07-27T09:24:57Z",
        "topics": [],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "The document-parsing benchmark this lane measures against — not a runnable parser, and the entry says so. Seven ledger rows cite it.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 75
    },
    {
      "id": "AHK-0084",
      "slug": "opendataloader-project--opendataloader-pdf",
      "url": "https://ai-academic.org/registry/opendataloader-project--opendataloader-pdf/",
      "github_repo_id": 982587624,
      "full_name": "opendataloader-project/opendataloader-pdf",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/opendataloader-project/opendataloader-pdf",
      "archived": false,
      "on_both_hubs": true,
      "category": "tools-document-processing",
      "task": "parse-pdfs-documents",
      "campaigns": [
        {
          "name": "2026-07-28__pdf-parsers",
          "date": "2026-07-28",
          "claim": "A high-coverage, effort-bounded map as of 2026-07-28 ranking five Apple-plausible local parsers (Marker v2 first, medium confidence); the coverage gate is NOT MET, no global winner or recall proof is asserted, no candidate was installed or executed, and multilingual support earned zero credit.",
          "claim_ref": "2026-07-28__pdf-parsers",
          "scout_citations": 2,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 28299,
        "forks": 2700,
        "watchers": 113,
        "language": "Java",
        "license_spdx": "Apache-2.0",
        "created_at": "2025-05-13T05:48:02Z",
        "pushed_at": "2026-08-07T12:36:20Z",
        "topics": [
          "a11y",
          "accessibility",
          "ai",
          "bounding-box",
          "document-parsing",
          "eaa",
          "html",
          "json",
          "markdown",
          "ocr",
          "ocr-recognition",
          "pdf",
          "pdf-accessibility",
          "pdf-converter",
          "pdf-extraction",
          "pdf-parser",
          "pdf-ua",
          "rag",
          "tables",
          "tagged-pdf"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "A Java PDF loader with accessibility-oriented JSON and reading order; the ledger records empty-output cases on its own project pages.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 76
    },
    {
      "id": "AHK-0085",
      "slug": "paddlepaddle--paddle",
      "url": "https://ai-academic.org/registry/paddlepaddle--paddle/",
      "github_repo_id": 65711522,
      "full_name": "PaddlePaddle/Paddle",
      "requested_name": "paddlepaddle/paddle",
      "successor_slug": null,
      "repo_url": "https://github.com/PaddlePaddle/Paddle",
      "archived": false,
      "on_both_hubs": true,
      "category": "tools-document-processing",
      "task": "parse-pdfs-documents",
      "campaigns": [
        {
          "name": "2026-07-28__pdf-parsers",
          "date": "2026-07-28",
          "claim": "A high-coverage, effort-bounded map as of 2026-07-28 ranking five Apple-plausible local parsers (Marker v2 first, medium confidence); the coverage gate is NOT MET, no global winner or recall proof is asserted, no candidate was installed or executed, and multilingual support earned zero credit.",
          "claim_ref": "2026-07-28__pdf-parsers",
          "scout_citations": 1,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 24045,
        "forks": 6014,
        "watchers": 707,
        "language": "C++",
        "license_spdx": "Apache-2.0",
        "created_at": "2016-08-15T06:59:08Z",
        "pushed_at": "2026-08-09T18:09:02Z",
        "topics": [
          "deep-learning",
          "distributed-training",
          "efficiency",
          "machine-learning",
          "neural-network",
          "paddlepaddle",
          "python",
          "scalability"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "The deep-learning framework underlying PaddleOCR; kept as lineage context for the OCR row.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 77
    },
    {
      "id": "AHK-0086",
      "slug": "paddlepaddle--paddleocr",
      "url": "https://ai-academic.org/registry/paddlepaddle--paddleocr/",
      "github_repo_id": 262296122,
      "full_name": "PaddlePaddle/PaddleOCR",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/PaddlePaddle/PaddleOCR",
      "archived": false,
      "on_both_hubs": true,
      "category": "tools-document-processing",
      "task": "parse-pdfs-documents",
      "campaigns": [
        {
          "name": "2026-07-28__pdf-parsers",
          "date": "2026-07-28",
          "claim": "A high-coverage, effort-bounded map as of 2026-07-28 ranking five Apple-plausible local parsers (Marker v2 first, medium confidence); the coverage gate is NOT MET, no global winner or recall proof is asserted, no candidate was installed or executed, and multilingual support earned zero credit.",
          "claim_ref": "2026-07-28__pdf-parsers",
          "scout_citations": 3,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 87297,
        "forks": 11162,
        "watchers": 553,
        "language": "Python",
        "license_spdx": "Apache-2.0",
        "created_at": "2020-05-08T10:38:16Z",
        "pushed_at": "2026-07-22T11:59:34Z",
        "topics": [
          "ai4science",
          "chineseocr",
          "document-parsing",
          "document-translation",
          "kie",
          "ocr",
          "paddleocr-vl",
          "pdf-extractor-rag",
          "pdf-parser",
          "pdf2markdown",
          "pp-ocr",
          "pp-structure",
          "rag"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "OCR pipeline with structured coordinates and reading order, under Apache-2.0; cited three times in the ledger.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 78
    },
    {
      "id": "AHK-0087",
      "slug": "pymupdf--pymupdf4llm",
      "url": "https://ai-academic.org/registry/pymupdf--pymupdf4llm/",
      "github_repo_id": 775556234,
      "full_name": "pymupdf/pymupdf4llm",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/pymupdf/pymupdf4llm",
      "archived": false,
      "on_both_hubs": true,
      "category": "tools-document-processing",
      "task": "parse-pdfs-documents",
      "campaigns": [
        {
          "name": "2026-07-28__pdf-parsers",
          "date": "2026-07-28",
          "claim": "A high-coverage, effort-bounded map as of 2026-07-28 ranking five Apple-plausible local parsers (Marker v2 first, medium confidence); the coverage gate is NOT MET, no global winner or recall proof is asserted, no candidate was installed or executed, and multilingual support earned zero credit.",
          "claim_ref": "2026-07-28__pdf-parsers",
          "scout_citations": 2,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 2078,
        "forks": 240,
        "watchers": 17,
        "language": "Python",
        "license_spdx": "AGPL-3.0",
        "created_at": "2024-03-21T15:55:43Z",
        "pushed_at": "2026-08-07T14:42:46Z",
        "topics": [],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "Lightweight extraction of native PDF geometry and reading order for model pipelines; version-mapping caveats are recorded.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 79
    },
    {
      "id": "AHK-0088",
      "slug": "run-llama--liteparse",
      "url": "https://ai-academic.org/registry/run-llama--liteparse/",
      "github_repo_id": 1153982569,
      "full_name": "run-llama/liteparse",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/run-llama/liteparse",
      "archived": false,
      "on_both_hubs": true,
      "category": "tools-document-processing",
      "task": "parse-pdfs-documents",
      "campaigns": [
        {
          "name": "2026-07-28__pdf-parsers",
          "date": "2026-07-28",
          "claim": "A high-coverage, effort-bounded map as of 2026-07-28 ranking five Apple-plausible local parsers (Marker v2 first, medium confidence); the coverage gate is NOT MET, no global winner or recall proof is asserted, no candidate was installed or executed, and multilingual support earned zero credit.",
          "claim_ref": "2026-07-28__pdf-parsers",
          "scout_citations": 2,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 11993,
        "forks": 823,
        "watchers": 36,
        "language": "Rust",
        "license_spdx": "Apache-2.0",
        "created_at": "2026-02-09T22:16:30Z",
        "pushed_at": "2026-08-05T21:39:15Z",
        "topics": [
          "document-ocr",
          "document-processing",
          "ocr",
          "ocr-recognition",
          "pdf",
          "pdf-parser",
          "text-extraction"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "A small Apache-2.0 geometry and OCR baseline in Rust; its own documentation bounds it away from dense multicolumn work.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 80
    },
    {
      "id": "AHK-0089",
      "slug": "eugeneyujunhao--mog",
      "url": "https://ai-academic.org/registry/eugeneyujunhao--mog/",
      "github_repo_id": 992722480,
      "full_name": "eugeneyujunhao/mog",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/eugeneyujunhao/mog",
      "archived": false,
      "on_both_hubs": true,
      "category": "writing-editing",
      "task": "evidence-grounded-editing",
      "campaigns": [
        {
          "name": "2026-07-30__evidence-grounded-editorial-agents",
          "date": "2026-07-30",
          "claim": "High-coverage, effort-bounded, not saturated as of 2026-07-31: an evidence-grounded editorial agent is architecturally a versioned artifact whose paragraphs are projections of a typed claim graph (source packet to evidence objects to typed claims to schema/plan to claim-covered paragraphs to deterministic gates to human redline to versioned page), not a prose generator with citations attached.",
          "claim_ref": "2026-07-30__evidence-grounded-editorial-agents",
          "scout_citations": 3,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 0,
        "forks": 0,
        "watchers": 0,
        "language": null,
        "license_spdx": "MIT",
        "created_at": "2025-05-29T15:56:33Z",
        "pushed_at": "2025-06-29T19:58:55Z",
        "topics": [],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "Official implementation of one of the campaign's anchor works on grounded editing.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 81
    },
    {
      "id": "AHK-0090",
      "slug": "google-research-datasets--ais",
      "url": "https://ai-academic.org/registry/google-research-datasets--ais/",
      "github_repo_id": 588766432,
      "full_name": "google-research-datasets/AIS",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/google-research-datasets/AIS",
      "archived": true,
      "on_both_hubs": true,
      "category": "writing-editing",
      "task": "evidence-grounded-editing",
      "campaigns": [
        {
          "name": "2026-07-30__evidence-grounded-editorial-agents",
          "date": "2026-07-30",
          "claim": "High-coverage, effort-bounded, not saturated as of 2026-07-31: an evidence-grounded editorial agent is architecturally a versioned artifact whose paragraphs are projections of a typed claim graph (source packet to evidence objects to typed claims to schema/plan to claim-covered paragraphs to deterministic gates to human redline to versioned page), not a prose generator with citations attached.",
          "claim_ref": "2026-07-30__evidence-grounded-editorial-agents",
          "scout_citations": 2,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "archived",
      "metrics": {
        "stars": 31,
        "forks": 2,
        "watchers": 2,
        "language": null,
        "license_spdx": "CC-BY-4.0",
        "created_at": "2023-01-14T00:07:03Z",
        "pushed_at": "2023-01-14T01:05:21Z",
        "topics": [],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "A dataset separating source comprehensibility from attribution; archived upstream, retained with its structured annotations.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 82
    },
    {
      "id": "AHK-0091",
      "slug": "kaijuml--parent",
      "url": "https://ai-academic.org/registry/kaijuml--parent/",
      "github_repo_id": 283720524,
      "full_name": "KaijuML/parent",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/KaijuML/parent",
      "archived": false,
      "on_both_hubs": true,
      "category": "writing-editing",
      "task": "evidence-grounded-editing",
      "campaigns": [
        {
          "name": "2026-07-30__evidence-grounded-editorial-agents",
          "date": "2026-07-30",
          "claim": "High-coverage, effort-bounded, not saturated as of 2026-07-31: an evidence-grounded editorial agent is architecturally a versioned artifact whose paragraphs are projections of a typed claim graph (source packet to evidence objects to typed claims to schema/plan to claim-covered paragraphs to deterministic gates to human redline to versioned page), not a prose generator with citations attached.",
          "claim_ref": "2026-07-30__evidence-grounded-editorial-agents",
          "scout_citations": 2,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 30,
        "forks": 5,
        "watchers": 1,
        "language": "Julia",
        "license_spdx": null,
        "created_at": "2020-07-30T08:57:06Z",
        "pushed_at": "2021-04-06T12:57:18Z",
        "topics": [
          "evaluation",
          "implementation-of-algorithms",
          "parent",
          "wikibio"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "Implementation of the PARENT table-aware evaluation metric, separating supported content from coverage.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 83
    },
    {
      "id": "AHK-0092",
      "slug": "particlemedia--ragtruth",
      "url": "https://ai-academic.org/registry/particlemedia--ragtruth/",
      "github_repo_id": 735798936,
      "full_name": "ParticleMedia/RAGTruth",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/ParticleMedia/RAGTruth",
      "archived": false,
      "on_both_hubs": true,
      "category": "writing-editing",
      "task": "evidence-grounded-editing",
      "campaigns": [
        {
          "name": "2026-07-30__evidence-grounded-editorial-agents",
          "date": "2026-07-30",
          "claim": "High-coverage, effort-bounded, not saturated as of 2026-07-31: an evidence-grounded editorial agent is architecturally a versioned artifact whose paragraphs are projections of a typed claim graph (source packet to evidence objects to typed claims to schema/plan to claim-covered paragraphs to deterministic gates to human redline to versioned page), not a prose generator with citations attached.",
          "claim_ref": "2026-07-30__evidence-grounded-editorial-agents",
          "scout_citations": 2,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 260,
        "forks": 35,
        "watchers": 10,
        "language": "Python",
        "license_spdx": "MIT",
        "created_at": "2023-12-26T05:41:01Z",
        "pushed_at": "2024-12-02T21:28:34Z",
        "topics": [],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "A corpus marking unsupported and contradictory spans at word level across generation tasks; adversarial evidence for grounded editing.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 84
    },
    {
      "id": "AHK-0093",
      "slug": "princeton-nlp--alce",
      "url": "https://ai-academic.org/registry/princeton-nlp--alce/",
      "github_repo_id": 644407378,
      "full_name": "princeton-nlp/ALCE",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/princeton-nlp/ALCE",
      "archived": false,
      "on_both_hubs": true,
      "category": "writing-editing",
      "task": "evidence-grounded-editing",
      "campaigns": [
        {
          "name": "2026-07-30__evidence-grounded-editorial-agents",
          "date": "2026-07-30",
          "claim": "High-coverage, effort-bounded, not saturated as of 2026-07-31: an evidence-grounded editorial agent is architecturally a versioned artifact whose paragraphs are projections of a typed claim graph (source packet to evidence objects to typed claims to schema/plan to claim-covered paragraphs to deterministic gates to human redline to versioned page), not a prose generator with citations attached.",
          "claim_ref": "2026-07-30__evidence-grounded-editorial-agents",
          "scout_citations": 2,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 524,
        "forks": 51,
        "watchers": 8,
        "language": "Python",
        "license_spdx": "MIT",
        "created_at": "2023-05-23T13:02:26Z",
        "pushed_at": "2024-10-09T11:36:02Z",
        "topics": [],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "Benchmark and code for citation correctness and completeness in generated text.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 85
    },
    {
      "id": "AHK-0094",
      "slug": "qhjqhj00--webbrain",
      "url": "https://ai-academic.org/registry/qhjqhj00--webbrain/",
      "github_repo_id": 624301947,
      "full_name": "qhjqhj00/WebBrain",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/qhjqhj00/WebBrain",
      "archived": false,
      "on_both_hubs": true,
      "category": "writing-editing",
      "task": "evidence-grounded-editing",
      "campaigns": [
        {
          "name": "2026-07-30__evidence-grounded-editorial-agents",
          "date": "2026-07-30",
          "claim": "High-coverage, effort-bounded, not saturated as of 2026-07-31: an evidence-grounded editorial agent is architecturally a versioned artifact whose paragraphs are projections of a typed claim graph (source packet to evidence objects to typed claims to schema/plan to claim-covered paragraphs to deterministic gates to human redline to versioned page), not a prose generator with citations attached.",
          "claim_ref": "2026-07-30__evidence-grounded-editorial-agents",
          "scout_citations": 2,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 70,
        "forks": 5,
        "watchers": 5,
        "language": "Python",
        "license_spdx": "Apache-2.0",
        "created_at": "2023-04-06T07:07:00Z",
        "pushed_at": "2023-06-07T09:43:17Z",
        "topics": [],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "Official implementation of the WebBrain grounded-generation research.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 86
    },
    {
      "id": "AHK-0095",
      "slug": "raldir--feverous",
      "url": "https://ai-academic.org/registry/raldir--feverous/",
      "github_repo_id": 369217144,
      "full_name": "Raldir/FEVEROUS",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/Raldir/FEVEROUS",
      "archived": false,
      "on_both_hubs": true,
      "category": "writing-editing",
      "task": "evidence-grounded-editing",
      "campaigns": [
        {
          "name": "2026-07-30__evidence-grounded-editorial-agents",
          "date": "2026-07-30",
          "claim": "High-coverage, effort-bounded, not saturated as of 2026-07-31: an evidence-grounded editorial agent is architecturally a versioned artifact whose paragraphs are projections of a typed claim graph (source packet to evidence objects to typed claims to schema/plan to claim-covered paragraphs to deterministic gates to human redline to versioned page), not a prose generator with citations attached.",
          "claim_ref": "2026-07-30__evidence-grounded-editorial-agents",
          "scout_citations": 2,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 76,
        "forks": 21,
        "watchers": 2,
        "language": "PHP",
        "license_spdx": "Apache-2.0",
        "created_at": "2021-05-20T13:26:28Z",
        "pushed_at": "2024-07-01T15:07:09Z",
        "topics": [],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "The FEVEROUS fact-verification dataset: mixed sentence and table-cell evidence with support, refute and insufficient labels.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 87
    },
    {
      "id": "AHK-0096",
      "slug": "shmsw25--factscore",
      "url": "https://ai-academic.org/registry/shmsw25--factscore/",
      "github_repo_id": 644105792,
      "full_name": "shmsw25/FActScore",
      "requested_name": "shmsw25/factscore",
      "successor_slug": null,
      "repo_url": "https://github.com/shmsw25/FActScore",
      "archived": false,
      "on_both_hubs": true,
      "category": "writing-editing",
      "task": "evidence-grounded-editing",
      "campaigns": [
        {
          "name": "2026-07-30__evidence-grounded-editorial-agents",
          "date": "2026-07-30",
          "claim": "High-coverage, effort-bounded, not saturated as of 2026-07-31: an evidence-grounded editorial agent is architecturally a versioned artifact whose paragraphs are projections of a typed claim graph (source packet to evidence objects to typed claims to schema/plan to claim-covered paragraphs to deterministic gates to human redline to versioned page), not a prose generator with citations attached.",
          "claim_ref": "2026-07-30__evidence-grounded-editorial-agents",
          "scout_citations": 3,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 453,
        "forks": 68,
        "watchers": 6,
        "language": "Python",
        "license_spdx": "MIT",
        "created_at": "2023-05-22T20:37:36Z",
        "pushed_at": "2025-04-13T20:41:02Z",
        "topics": [
          "emnlp2023",
          "evaluation",
          "factuality",
          "language",
          "language-modeling"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "Atomic-fact precision scoring for long-form output; cited for claim-level editorial evaluation.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 88
    },
    {
      "id": "AHK-0097",
      "slug": "stanford-oval--storm",
      "url": "https://ai-academic.org/registry/stanford-oval--storm/",
      "github_repo_id": 776854298,
      "full_name": "stanford-oval/storm",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/stanford-oval/storm",
      "archived": false,
      "on_both_hubs": true,
      "category": "writing-editing",
      "task": "evidence-grounded-editing",
      "campaigns": [
        {
          "name": "2026-07-30__evidence-grounded-editorial-agents",
          "date": "2026-07-30",
          "claim": "High-coverage, effort-bounded, not saturated as of 2026-07-31: an evidence-grounded editorial agent is architecturally a versioned artifact whose paragraphs are projections of a typed claim graph (source packet to evidence objects to typed claims to schema/plan to claim-covered paragraphs to deterministic gates to human redline to versioned page), not a prose generator with citations attached.",
          "claim_ref": "2026-07-30__evidence-grounded-editorial-agents",
          "scout_citations": 6,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 30876,
        "forks": 2891,
        "watchers": 187,
        "language": "Python",
        "license_spdx": "MIT",
        "created_at": "2024-03-24T16:23:39Z",
        "pushed_at": "2025-09-30T18:07:21Z",
        "topics": [
          "agentic-rag",
          "deep-research",
          "emnlp2024",
          "knowledge-curation",
          "large-language-models",
          "naacl",
          "nlp",
          "report-generation",
          "retrieval-augmented-generation"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "A research system that collects references, outlines, and writes citation-bearing articles with a polishing stage; six ledger rows cite it.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 89
    },
    {
      "id": "AHK-0098",
      "slug": "tobiasblask--open-paper-machine",
      "url": "https://ai-academic.org/registry/tobiasblask--open-paper-machine/",
      "github_repo_id": 1163168353,
      "full_name": "TobiasBlask/open-paper-machine",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/TobiasBlask/open-paper-machine",
      "archived": false,
      "on_both_hubs": true,
      "category": "writing-editing",
      "task": "evidence-grounded-editing",
      "campaigns": [
        {
          "name": "2026-07-30__evidence-grounded-editorial-agents",
          "date": "2026-07-30",
          "claim": "High-coverage, effort-bounded, not saturated as of 2026-07-31: an evidence-grounded editorial agent is architecturally a versioned artifact whose paragraphs are projections of a typed claim graph (source packet to evidence objects to typed claims to schema/plan to claim-covered paragraphs to deterministic gates to human redline to versioned page), not a prose generator with citations attached.",
          "claim_ref": "2026-07-30__evidence-grounded-editorial-agents",
          "scout_citations": 2,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 16,
        "forks": 5,
        "watchers": 1,
        "language": "Python",
        "license_spdx": "MIT",
        "created_at": "2026-02-21T07:40:13Z",
        "pushed_at": "2026-04-10T05:58:08Z",
        "topics": [
          "academic-writing",
          "arxiv",
          "claude",
          "claude-code",
          "claude-code-plugin",
          "claude-skills",
          "constitutional-ai",
          "mcp",
          "open-science",
          "paper-generation",
          "research-automation"
        ],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "A staged drafting, verification and revision pipeline; the ledger grades its implementation evidence narrow and low-confidence, and the entry keeps that framing.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 90
    },
    {
      "id": "AHK-0099",
      "slug": "zhzihao--wikigenbench",
      "url": "https://ai-academic.org/registry/zhzihao--wikigenbench/",
      "github_repo_id": 763925116,
      "full_name": "zhzihao/WikiGenBench",
      "requested_name": null,
      "successor_slug": null,
      "repo_url": "https://github.com/zhzihao/WikiGenBench",
      "archived": false,
      "on_both_hubs": true,
      "category": "writing-editing",
      "task": "evidence-grounded-editing",
      "campaigns": [
        {
          "name": "2026-07-30__evidence-grounded-editorial-agents",
          "date": "2026-07-30",
          "claim": "High-coverage, effort-bounded, not saturated as of 2026-07-31: an evidence-grounded editorial agent is architecturally a versioned artifact whose paragraphs are projections of a typed claim graph (source packet to evidence objects to typed claims to schema/plan to claim-covered paragraphs to deterministic gates to human redline to versioned page), not a prose generator with citations attached.",
          "claim_ref": "2026-07-30__evidence-grounded-editorial-agents",
          "scout_citations": 3,
          "campaign_placed_on_both_hubs": false
        }
      ],
      "status_state": "live",
      "metrics": {
        "stars": 13,
        "forks": 2,
        "watchers": 1,
        "language": "Python",
        "license_spdx": null,
        "created_at": "2024-02-27T06:52:37Z",
        "pushed_at": "2025-01-05T15:28:12Z",
        "topics": [],
        "http_status": 200,
        "snapshot_date": "2026-08-10"
      },
      "description": "A generation benchmark the ledger records as the same work as another row, with the count inconsistency preserved rather than smoothed.",
      "description_status": "editorial draft",
      "tags": [],
      "order": 91
    }
  ]
}