公开记录存在风险
软件健康报告模式 0.27.0 · 指标 1.13.0 · 2026-07-29 06:29 UTC
DanceNitra / ramr
RAMR — Retrieval-Augmented Memory Reliability: a contamination-resistant synthetic benchmark for agentic-RAG / memory systems (findings + method)
DanceNitra/ramr 的健康指数为 100 分中的 34 分，处于「存在风险」区间。 其得分最高的类别是Vitality（66/100），最低的是Sustainability & Governance（20/100）。 最近一次更新在 4 天前。 近期的大部分工作由 1 位贡献者完成。
34
总分 / 100软件健康指数
指标归入加权类别，统一采用 1–100 量表。总体分先取类别加权平均；当公开证据触发高风险司法辖区政策时，评级会按政策调整，并设置 49（有风险）的上限。AI 就绪度不计入总体分。
34
优秀85-100堪称典范；基本满足所有检验标准
良好70-84健康；仅有轻微不足
中等50-69可接受，但存在明显不足；建议进行审查
存在风险30-49存在重大薄弱环节；采用时应保持审慎
危急1-29问题严重（项目被弃置、仅有单一维护者、缺乏基本工程规范）
评分画像
每条轴代表一个类别。形状比平均值更重要——健康的对象会填满整个图形，而“一峰一谷”式画像意味着某一维度的优势正掩盖另一维度的风险。
所有权
按类别列示的指标
活力
项目是否仍有生命——是否仍在编写代码，是否仍在发布版本？
66
开发活跃度
54中等
评分方式
| 36/36 | 推送新近度 — 最近一次推送于 4 天前 |
| 3.5/36 | 提交节奏 — 52 周中有 5 周有提交 |
| 14.6/18 | 提交量 — 最近一年 41 次提交 |
| 0/10 | OpenSSF Scorecard：Maintained — project was created within the last 90 days. Please review its contents carefully |
所用输入
| commits_last_year | 41 |
| human_commit_share | 1 |
| days_since_last_push | 4 |
| active_weeks_last_year | 5 |
发布纪律
84良好
评分方式
| 27/27 | 有发布版本 — 已发布 1 个发布版本 |
| 36/36 | 发布时效 — 最近一次发布版本于 30 天前 |
| 12.6/27 | 发布节奏 — 节奏未知（仅一次发布） |
| 0/10 | OpenSSF Scorecard：Signed-Releases — 无数据 |
所用输入
| releases_count | 1 |
| latest_release_tag | v0.4.1 |
| releases_from_tags | 否 |
| days_since_latest_release | 30 |
| mean_days_between_releases | — |
已排除计分（无数据或不适用）：OpenSSF Scorecard：Signed-Releases。 其余权重已重新归一化。
社区与采用
项目是否拥有用户、下载量与关注度，并具备欢迎贡献者参与的配置？
24
流行度与采用
1危急
评分方式
| 0/60 | 星标 — 0 个星标 |
| 0/25 | 复刻 — 0 个复刻 |
| 0/15 | 关注者 — 0 位关注者 |
所用输入
| forks | 0 |
| stars | 0 |
| watchers | 0 |
| growth_state | unverified |
| growth_factor_pct | 100 |
| growth_unverified_reason | no_history |
社区健康
50中等
评分方式
| 22.5/22.5 | README |
| 22.5/22.5 | 许可证 — 可识别的许可证（MIT） |
| 0/18 | CONTRIBUTING 指南 |
| 0/13.5 | 行为准则 |
| 0/7.2 | 议题模板 |
| 0/6.3 | PR 模板 |
所用输入
| has_readme | 是 |
| has_license | 是 |
| has_contributing | 否 |
| has_issue_template | 否 |
| has_code_of_conduct | 否 |
| has_pull_request_template | 否 |
可持续性与治理
项目能否在其成员之外延续——巴士系数、响应能力、由谁支持，以及软件包的维护状况？
20
维护者韧性（巴士系数）
10危急
评分方式
| 9/54 | 巴士系数 — 1 位贡献者贡献了半数提交 |
| 0/22.5 | 提交分布 — 头号贡献者编写了 100% 的提交 |
| 1.4/13.5 | 贡献者广度 — 1 位贡献者 |
| 0/10 | OpenSSF Scorecard：Contributors — project has 0 contributing companies or organizations -- score normalized to 0 |
所用输入
| bus_factor | 1 |
| contributors_sampled | 1 |
| top_contributor_share | 1 |
议题与 PR 响应能力
1危急
评分方式
| 0/46.8 | 议题解决 — 没有议题或无数据 |
| 0/38.3 | PR 接受 — 没有已裁定的拉取请求或无数据 |
| 0/15 | OpenSSF Scorecard：Code-Review — Found 0/30 approved changesets -- score normalized to 0 |
所用输入
| merged_prs | 0 |
| open_issues | 0 |
| closed_issues | 0 |
| issue_closed_ratio | — |
| closed_unmerged_prs | 0 |
已排除计分（无数据或不适用）：议题解决, PR 接受。 其余权重已重新归一化。
所有权与托管责任
50中等
评分方式
| 10/30 | 所有权背书 — 个人（用户）账户 |
| 0/20 | 已验证域名 — 不适用于个人账户 |
| 5.6/25 | 所有者影响力 — DanceNitra 有 5 位关注者 |
| 24/25 | 既往记录 — 44 个公开仓库，账户约 8 年 |
所用输入
| followers | 5 |
| owner_type | User |
| is_verified | — |
| owner_login | DanceNitra |
| public_repos | 44 |
| account_age_days | 2,924 |
已排除计分（无数据或不适用）：已验证域名。 其余权重已重新归一化。
工程质量
基础的工程与文档实践是否到位？
31
工程实践
1危急
评分方式
| 0/24 | CI 工作流 |
| 0/24 | 存在测试 |
| 0/16 | Linter 配置 |
| 0/9.6 | Pre-commit 钩子 |
| 0/6.4 | .editorconfig |
| 0/20 | OpenSSF Scorecard：CI-Tests — 无数据 |
所用输入
| has_ci | 否 |
| has_tests | 否 |
| has_editorconfig | 否 |
| has_linter_config | 否 |
| has_precommit_config | 否 |
已排除计分（无数据或不适用）：OpenSSF Scorecard：CI-Tests。 其余权重已重新归一化。
文档
75良好
评分方式
| 30/30 | README |
| 0/25 | 文档目录 |
| 15/15 | 文档 / 主页站点 — https://dancenitra.github.io/agora/public/leaderboard/ |
| 10/10 | 仓库描述 |
| 10/10 | 主题标签 — 6 个主题标签 |
| 10/10 | Wiki |
所用输入
| topics | agent-memory, benchmark, evaluation, llm, rag, retrieval |
| has_wiki | 是 |
| homepage | https://dancenitra.github.io/agora/public/leaderboard/ |
| has_readme | 是 |
| has_docs_dir | 否 |
| has_description | 是 |
安全
可见的安全与供应链实践是否稳固，且不存在未解决的高风险司法辖区暴露？
26
安全态势
26危急
评分方式
| 7.5/7.5 | Binary-Artifacts — no binaries found in the repo |
| 0/7.5 | Branch-Protection — branch protection not enabled on development/release branches |
| 0/2.5 | CI-Tests — 无数据 |
| 0/2.5 | CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected |
| 0/7.5 | Code-Review — Found 0/30 approved changesets -- score normalized to 0 |
| 0/2.5 | Contributors — project has 0 contributing companies or organizations -- score normalized to 0 |
| 0/10 | Dangerous-Workflow — 无数据 |
| 0/7.5 | Dependency-Update-Tool — no update tool detected |
| 0/5 | Fuzzing — project is not fuzzed |
| 2.5/2.5 | 许可证 — license file detected |
| 0/7.5 | Maintained — project was created within the last 90 days. Please review its contents carefully |
| 0/5 | Packaging — 无数据 |
| 0/5 | Pinned-Dependencies — 无数据 |
| 0/5 | SAST — no SAST tool detected |
| 0/5 | Security-Policy — security policy file not detected |
| 0/7.5 | Signed-Releases — 无数据 |
| 0/7.5 | Token-Permissions — 无数据 |
| 7.5/7.5 | Vulnerabilities — 0 existing vulnerabilities detected |
所用输入
| source | openssf_scorecard |
| checks_evaluated | 12 |
| scorecard_version | v5.5.0 |
| checks_inconclusive | 6 |
| scorecard_aggregate | 2.6 |
已排除计分（无数据或不适用）：ci_tests, dangerous_workflow, packaging, pinned_dependencies, signed_releases, token_permissions。 其余权重已重新归一化。
AI 就绪度
该仓库在多大程度上具备与 AI 编码代理协同开发与维护的条件？这是一枚独立的实验性徽章——权重为 0.0，因此单独呈现，不影响总体健康评分。
29
AI 代理上下文与指引
40存在风险
评分方式
| 0/45 | 代理指令 — 没有 CLAUDE.md / AGENTS.md / 编辑器规则 |
| 0/15 | 机器可读文档（llms.txt） |
| 40/40 | 可读的提交历史 — 41 次人类提交中有 37 次说明了意图（结构化标题或解释性正文） |
所用输入
| has_llms_txt | 否 |
| legible_history_share | 0.902 |
| agent_instruction_files | — |
| agent_instruction_max_bytes | — |
评分方式
| 0/18 | 一条命令的引导启动 |
| 0/22 | 自动化测试 |
| 0/11 | Lint / 格式化配置 |
| 0/11 | 静态类型检查 |
| 0/10 | 可复现环境 |
| 10/10 | 已体现的代理实践 — 最近 41 次提交中有 13 次由代理编写或署名代理 |
| 0/8 | 自动化维护 — 未观察到自动依赖更新 |
| 0/10 | OpenSSF Scorecard：Pinned-Dependencies — 无数据 |
所用输入
| has_nix | 否 |
| has_tests | 否 |
| lockfiles | — |
| has_dockerfile | 否 |
| typed_language | 否 |
| bootstrap_files | — |
| has_devcontainer | 否 |
| has_linter_config | 否 |
| typecheck_configs | — |
| agent_commit_share | 0.317 |
| toolchain_manifests | — |
| dependency_bot_commit_share | 0 |
已排除计分（无数据或不适用）：OpenSSF Scorecard：Pinned-Dependencies。 其余权重已重新归一化。
面向模型的代码可读性
53中等
评分方式
| 0/45 | 可类型检查的代码 — Python，未配置类型检查 |
| 53.3/55 | 可控的文件大小 — 采样的 33 个源文件中有 1 个超过 60KB |
所用输入
| primary_language | Python |
| largest_source_bytes | 385,518 |
| source_files_sampled | 33 |
| oversized_source_files | 1 |
关键数据
0GitHub 星标
1贡献者
41最近 12 个月提交数
4距最近推送天数
1发布版本数
1巴士系数（bus factor）
0开放议题
—软件包生态系统数
数据采集警告
- GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository
更多细节
OpenSSF Scorecard 2.6 / 10
2.6综合
来自开源项目 OpenSSF Scorecard 的独立、工具无关的安全评估。每项检查奖励的是安全实践本身，而非特定供应商的工具。Scorecard 无法判定的检查项标记为 不适用，并从安全评分中剔除（绝不按零分计）。
| 10 | Binary-Artifacts | no binaries found in the repo |
| 0 | Branch-Protection | branch protection not enabled on development/release branches |
| 不适用 | CI-Tests | no pull request found |
| 0 | CII-Best-Practices | no effort to earn an OpenSSF best practices badge detected |
| 0 | Code-Review | Found 0/30 approved changesets -- score normalized to 0 |
| 0 | Contributors | project has 0 contributing companies or organizations -- score normalized to 0 |
| 不适用 | Dangerous-Workflow | no workflows found |
| 0 | Dependency-Update-Tool | no update tool detected |
| 0 | Fuzzing | project is not fuzzed |
| 10 | License | license file detected |
| 0 | Maintained | project was created within the last 90 days. Please review its contents carefully |
| 不适用 | Packaging | packaging workflow not detected |
| 不适用 | Pinned-Dependencies | no dependencies found |
| 0 | SAST | no SAST tool detected |
| 0 | Security-Policy | security policy file not detected |
| 不适用 | Signed-Releases | no releases found |
| 不适用 | Token-Permissions | No tokens found |
| 10 | Vulnerabilities | 0 existing vulnerabilities detected |
全部依赖 未采集
本报告未能采集到解析后的依赖集合：GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository
原始 JSON 报告 机器可读
{
"data": {
"repo": {
"topics": [
"agent-memory",
"benchmark",
"evaluation",
"llm",
"rag",
"retrieval"
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"is_fork": false,
"size_kb": 715,
"has_wiki": true,
"homepage": "https://dancenitra.github.io/agora/public/leaderboard/",
"languages": {
"Python": 596480
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"pushed_at": "2026-07-24T23:44:28Z",
"created_at": "2026-06-23T17:50:24Z",
"owner_type": "User",
"updated_at": "2026-07-28T14:10:11Z",
"description": "RAMR — Retrieval-Augmented Memory Reliability: a contamination-resistant synthetic benchmark for agentic-RAG / memory systems (findings + method)",
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"primary_language": "Python",
"significant_languages": [
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},
"owner": {
"blog": null,
"name": "Rastislav Drahoš",
"type": "User",
"login": "DanceNitra",
"company": null,
"location": null,
"followers": 5,
"avatar_url": "https://avatars.githubusercontent.com/u/41733909?v=4",
"created_at": "2018-07-26T09:54:30Z",
"is_verified": null,
"public_repos": 44,
"account_age_days": 2924
},
"license": {
"state": "standard",
"spdx_id": "MIT",
"raw_spdx": "MIT",
"file_present": true,
"scorecard_found": true,
"profile_has_license": true
},
"activity": {
"releases": [
{
"tag": "v0.4.1",
"kind": "patch",
"published_at": "2026-06-28T09:49:21Z"
}
],
"recent_commits": [
{
"oid": "b18db2400bcd341723e0f0fa06f2aad637759622",
"body": "No code, data, metric or claim changed. This version exists so the citable record\nand the repository agree on who maintains RAMR.\n\nContext: the inspeximus README had credited Rastislav Drahos by name for some time\nwhile CITATION.cff and the Zenodo creators said \"Agora\". A supplier or auditor\ncheck f\n[…]\n do. Its DOI is\nnow listed in CITATION.cff identifiers so the ladder stays complete, and the name\nlands on this new version instead.\n\nCo-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>",
"is_bot": false,
"headline": "v0.5.1: attribution only - the author is named",
"author_name": "Rastislav Drahoš",
"author_login": "DanceNitra",
"committed_at": "2026-07-24T23:44:18Z",
"body_truncated": true,
"is_coding_agent": true
},
{
"oid": "47adf324b3d854c403b764e90ca588e251c980c8",
"body": "Owner decision 2026-07-25: move from anonymous stewardship to a named maintainer.\nThe driver is that in the one channel with live demand - downstream vendor-security\nand third-party-risk review - supplier attestation fields require a nameable party,\nand cryptography does not substitute for one.\n\nThe\n[…]\nstory is\n not rewritten. GitHub noreply is used instead of the personal address so the\n name is public but the mailbox is not.\n\nCo-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>",
"is_bot": false,
"headline": "citation: name the author",
"author_name": "Rastislav Drahoš",
"author_login": "DanceNitra",
"committed_at": "2026-07-24T23:40:34Z",
"body_truncated": true,
"is_coding_agent": true
},
{
"oid": "3dd44ad4f310f8cd1f351ff92471714462021a2a",
"body": "CITATION.cff -> 0.5.0 (2026-07-25) and a README changelog entry. The preflight is\nnot a twelfth metric - it is a check on whether a comparison was admissible at\nall - so the metric count stays at eleven and the abstract gains the gate.\n\nCo-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>",
"is_bot": false,
"headline": "v0.5.0: version the preflight release",
"author_name": "Agora",
"author_login": null,
"committed_at": "2026-07-24T22:28:58Z",
"body_truncated": false,
"is_coding_agent": true
},
{
"oid": "a62b8080ab20001e187b7925c740e85ad71c577c",
"body": "…t died\n\nA RAMR metric only means something if the arms were comparing the same thing.\nramr_preflight.py is the check we ask of ourselves before publishing any RAMR\nnumber, shipped as a zero-dependency module anyone can point at their own\ncomparison.\n\n G0 budget parity are the arms given compa\n[…]\nat run's persisted\nretrieval_coverage.json and pilot_summary_*.json but are not reproducible from\nthis repo. The --demo numbers are.\n\nCo-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>",
"is_bot": false,
"headline": "preflight: four admissibility gates, each aborting with the layer tha…",
"author_name": "Agora",
"author_login": null,
"committed_at": "2026-07-24T22:27:19Z",
"body_truncated": true,
"is_coding_agent": true
},
{
"oid": "a8e66332addf1d5dd288822502672e197f368db5",
"body": "…ndocumented checkpoint-undo)",
"is_bot": false,
"headline": "integrity: scope the revert 'only inspeximus' reading (Letta has an u…",
"author_name": "agora-builder",
"author_login": null,
"committed_at": "2026-07-23T15:25:03Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "54ff69799fafecbe5c5329db66eb6addf9f2c079",
"body": "The cross-system integrity results (integrity/ module) are now rendered as a standing, PR-submittable\nleaderboard at dancenitra.github.io/agora/public/leaderboard/. Submission flow already lives in\nintegrity/SUBMISSION.md.\n\nCo-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>",
"is_bot": false,
"headline": "README: link the standing Agent-Memory Integrity Leaderboard",
"author_name": "Agora",
"author_login": null,
"committed_at": "2026-07-22T16:31:27Z",
"body_truncated": false,
"is_coding_agent": true
},
{
"oid": "3fe7edcef5d72cb917baeb7da27c036004c6267e",
"body": "…e to 1.29.0\n\nAdds ramr_integrity_recall.py: after a supersession/revert/poison, does recall return the correct\ncurrent value? revert is the unique win on this scenario (inspeximus 1.00 vs cosine-recency 0.00,\nnaive 0.55 -- recency has no revert op); supersession ties a fair recency baseline (both 1\n[…]\nOPE-LEAKAGE 0.82->0.80, breakeven boost arm\n<=0.03 (cited headline stays +0.00). Also removed an internal path a docstring leaked.\n\nCo-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>",
"is_bot": false,
"headline": "v0.4.3: INTEGRITY-CONDITIONED RECALL metric; re-vendor inspeximus cor…",
"author_name": "Agora",
"author_login": null,
"committed_at": "2026-07-22T14:43:12Z",
"body_truncated": true,
"is_coding_agent": true
},
{
"oid": "5bf763fabb317148c70747690960830d1fa49d59",
"body": "…hange)\n\nThe public benchmark vendored a pinned snapshot of our memory library under its old name, mnemo. This\nrenames it to inspeximus everywhere -- module (mnemo/mnemo.py -> inspeximus/core.py), class\n(Mnemo -> Inspeximus), and every reference -- so the repo carries no trace of the old name. Zero\n\n[…]\n-> \"an inspeximus\" article slips the mechanical rename introduced; and\ngitignore now excludes an unrelated WIP metric's artifacts.\n\nCo-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>",
"is_bot": false,
"headline": "v0.4.2: rename the vendored library mnemo -> inspeximus (no numbers c…",
"author_name": "Agora",
"author_login": null,
"committed_at": "2026-07-22T13:43:43Z",
"body_truncated": true,
"is_coding_agent": true
},
{
"oid": "003cdd4eaa431e1413dd01ef94d5c4d15d5353b7",
"body": "…-19 hardening this repo missed)",
"is_bot": false,
"headline": "gitignore: cover .env variants and key material (restores the 2026-07…",
"author_name": "Agora",
"author_login": null,
"committed_at": "2026-07-19T21:45:37Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "3f8a66ad9d7d17ec5e32596b67200acc68091422",
"body": "…-memory two-writer test)\n\nStore V1 -> correct to V2 -> stale writer re-asserts V1; check what top-1\nretrieval actually serves after each step + whether the backend can hand back\na state receipt that detects the echo. Measured: naive recency baseline fails\necho_resistance (the test can fail); mnemo, mem0 (update()), Chroma (delete+add)\nall pass this minimal case - honest parity on the serve; only mnemo exposes a\nwitness receipt. Run it on your own stack; the result is yours.",
"is_bot": false,
"headline": "integrity: two-writer retrieval-coherence fixture (step 6 of the team…",
"author_name": "agora-builder",
"author_login": null,
"committed_at": "2026-07-19T21:45:16Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "61b81d62ab22b860bfb68b1ee5c863d00df08ec9",
"body": "Deterministic temporal cell (unique-token ground truth, no judge): reversed-ingest\nnow-accuracy, as_of valid-time point queries, transaction-time back-fill. Measured:\nmnemo 4/4; mem0 default vector store has no valid-time channel. Framed as PARITY:\nZep (arXiv:2501.13956) and Graphiti are documented bi-temporal too and are listed,\nnot run/scored -- we do not claim to beat them on this axis. Result JSON persisted.\n\nCo-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>",
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"headline": "Add bi-temporal integrity cell (honest parity, not a mnemo win)",
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"body": "Consolidate the agent-memory integrity axis into the RAMR brand (one DOI, one\nhome). Adds integrity/ : the cross-system revert+echo harness (shared ground-\ntruth-blind judge, native configs) and a run-your-own erasure self-check tool.\nREVERT is a new dimension (not one of the 9 synthetic metrics); E\n[…]\nlly above and is now also measured cross-system. Non-breaking:\nthe verified 9-metric pipeline and DOI-cited numbers are untouched.\n\nCo-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>",
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"headline": "Merge cross-system integrity + erasure self-check under RAMR",
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"body": "…oral invalidation defends (0/26 echo-attributable); raw 0.87 residual = extraction misses, not echo",
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"headline": "echo-resistance: real Graphiti runtime (Neo4j+OpenAI, n=30) — bi-temp…",
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"body": "…ootstrap CI\n\nRe-ran mem0 in its own recommended config (gpt-4o-mini + text-embedding-3-small + Chroma)\nso the number isn't a non-native-judge artifact, and report a CI instead of a point\nestimate (the earlier n=10 vs n=30 swing showed a point estimate is unsafe): resurrection\n~47% under a value-pre\n[…]\ninistic (0.00 off / 1.00 guard, judge-independent). Framed as a small\nsynthetic demonstration with disclosed limits, not a definitive benchmark.\n\nCo-Authored-By: Claude Fable 5 <noreply@anthropic.com>",
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"headline": "ECHO-RESISTANCE: mem0 measured in its NATIVE config (OpenAI) with a b…",
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"body": "… runtime blocked, not faked)\n\nWe could not run Graphiti end-to-end here (its extraction needs strict structured-output\nschema adherence our OSS-cloud judge models don't meet) and declined to shim the parser\nrather than publish a non-faithful number. From its source (edge_operations.py):\nget_between\n[…]\no DEFEND (~1.0). Marked clearly as code-path reading,\nnot a measured number; runtime confirmation (OpenAI/Anthropic-class judge) is future work.\n\nCo-Authored-By: Claude Fable 5 <noreply@anthropic.com>",
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"headline": "ECHO-RESISTANCE: add honest Zep/Graphiti note (code-verified defends;…",
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"body": "… mem0 measured)\n\nA top-1 retrieval metric is fair to a supersession store but a strawman for an\nadd-based store (mem0) that reconciles at read-time. This scores echo-resistance\nat the answer level (recall top-k -> judge LLM -> current value?), fair to both.\nMeasured n=30, mem0 2.0.11 run fully loca\n[…]\nall mem0ai chromadb). Add a backend via a 3-method adapter. Value-preserving\nechoes; single judge model; n=30. ramr_echo_resistance_backends.py.\n\nCo-Authored-By: Claude Fable 5 <noreply@anthropic.com>",
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"headline": "ECHO-RESISTANCE: add fair ANSWER-LEVEL cross-backend comparison (real…",
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"body": "…endored mnemo\n\nNew RAMR metric ramr_echo_resistance.py: FORGET-PRECISION shows a correction sticks\n(1.00), but re-stating the retired value (verbatim OR reworded) resurrects it on a\nlast-writer-wins / validity-recency store -> echo-resistance 0.00. A superseded-object\nledger (mnemo echo_guard, obje\n[…]\nVERSION/CHAIN-FRAGILITY/DISTRACTION/OUTCOME-LIFT/FACT-RETENTION unchanged\n(all mnemo additions are opt-in, default-off = byte-identical legacy).\n\nCo-Authored-By: Claude Fable 5 <noreply@anthropic.com>",
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"body": "…to extract_int) - works for string/abstention claims now",
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"headline": "v0.4.1: Folklore Meter honours claim custom extractor (was hardcoded …",
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"body": "…gineering folklore\n\nramr_folklore_meter.py: run a contrarian, exact-match claim across a model gradient\n(local Ollama + pluggable frontier anchor) -> verdict REAL / WEAK-MODEL ARTIFACT /\nREGIME-SPECIFIC / NULL. Robust ANSWER-line extraction (retry-until-clean, no\nlast-number fallback). README documents the tool + two worked verdicts\n(decision-trace memory -> weak-model artifact; multi-agent vote -> regime-specific).",
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"headline": "v0.4.0: Folklore Meter — judge-free capability-gradient test of AI-en…",
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"body": "RESUME = the tested continuation invariant passed; NOT global execution\nauthorization, and does not bypass downstream policy/approval/effect gates.\nAligned with safal207/LS#654 (which verified the v0.3.0 canonical sources).\nSemantic clarification only: fixture bytes + sha256 digests are unchanged, so\nexisting pins (incl. LS#654) stay valid. README + conformance-runner docstring.",
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"headline": "v0.3.1: pin RESUME verdict semantics in the RAMR<->LS standard",
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"body": "Adds 3 canonical ramr-ls-evidence-v0.1 fixtures (frozen + sha256): superseded_approval\n-> REJECT, incomplete_dependency_chain -> ABSTAIN, target_state_drift -> REVALIDATE\n(with duplicate_successful_outcome -> REJECT). run_ramr_ls_fixtures.py scores each\nfixture's RAMR-side measured quantity vs the f\n[…]\neded/drift ride mnemo bi-temporal valid_from/invalidated_at; incomplete\nrides chain-fragility. RAMR measures reliability, LS owns the verdict. Collaboration:\nsafal207/LS, anthropics/claude-code#34556.",
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"headline": "v0.3.0: RAMR<->LS fixture set spans all 4 verdicts + conformance runner",
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"body": "… reliability-layer harness\n\nHosts the canonical shared fixture (duplicate_successful_outcome, frozen + sha256\ndigest) and ramr_ls_evidence.py, which emits the v0.1 envelope from a memory store\n(thin projection of bi-temporal valid_from/invalidated_at, provenance, Beta\nreliability, recall budget) an\n[…]\nn provenance + poison-propagation graduation guard\n(both regression-gated: FORGET-PRECISION/SUPERSESSION-FP/OPERATIONAL-CONTINUITY\nunchanged). Collaboration: safal207/LS, anthropics/claude-code#34556.",
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"headline": "v0.2.0: RAMR<->LS interop — canonical ramr-ls-evidence-v0.1 fixture +…",
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"body": "mnemo: remember(valid_from=), consolidate supersedes by validity-time not\ningest-order, recall(as_of=T). New ramr_temporal_asof.py: under reversed ingest\n(stale fact arrives later) the old ingest-order rule serves STALE (now-acc 0.00)\nwhile validity-time serves CURRENT (1.00) and as-of returns the h\n[…]\ningest-time so ordered streams are byte-identical;\nFORGET-PRECISION / SUPERSESSION-FP / OPERATIONAL-CONTINUITY all unchanged. Field-\nstandard (Graphiti/Zep/Neo4j); from the 122-transcript memory scan.",
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"headline": "v0.1.9: TEMPORAL-AS-OF metric + bi-temporal validity in mnemo",
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"oid": "6f7e53eaa7d87dc30ae4a016a5d6bb734de66d6a",
"body": "…inuity idea\n\nMake the attribution visible in the README (not just the commit/docstring):\nthe metric implements a property proposed by @safal207; framed as a first cut\nwith fixture input welcome.",
"is_bot": false,
"headline": "v0.1.8: credit @safal207 (claude-code#34556) for the operational-cont…",
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"body": "New agentic axis beyond fact recall: does the agent re-execute a completed\naction after compaction (a duplicate side-effect)? ramr_operational_continuity.py\nmeasures the duplicate-rate of a budget-limited resume recall. Result: recency\nweighting is necessary AND sufficient -- with it, duplicate-rate\n[…]\nbudget floor (robust to 200 old-session completions); without it, 1.00 at\nevery budget. Answers the operational-continuity property raised in\nclaude-code#34556. Pure-recall proxy, 6 seeds, cloud-free.",
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"headline": "v0.1.8: add OPERATIONAL-CONTINUITY metric (idempotent resume)",
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"body": "…ESSION-FP metric)\n\nThe numeric value-update detector over-fired on enumerated facts and silently\nsuperseded coexisting records (6-item store -> 1/6 active). Fixed by positional\nnumber comparison (exactly one number-slot changes for a real update). Added\nramr_supersession_fp.py (the dual of FORGET-PRECISION: 0.00 false-positive,\n6/6 survive) + verified-numbers row. FORGET-PRECISION re-measured 1.00/1.00,\nregression-gated.",
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"headline": "v0.1.7: fix supersession false-positive on enumerated facts (+ SUPERS…",
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"headline": "README: metrics table 6->7 (add COMPRESSION-vs-RAW row, consistency)",
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"oid": "2709f8d02846029d18d3adc34dde110a70747e0a",
"body": "…gain (honest negative)\n\nTested the 'compression beats oracle' claim. qwen3-coder:30b: compiled summary\ndoes NOT beat raw context at any noise level (lift +0.00/-0.40/-0.55 at\nK=5/20/50). Raw stays 0.95 even at 50 distractors; compaction loses the fact.\nHonest negative; external claim didn't replicate. Metric + result persisted.",
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"headline": "RAMR v0.1.6: COMPRESSION-vs-RAW metric — compaction is a cost, not a …",
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"body": "…5 (consistency)",
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"headline": "README: update Limitations to OUTCOME-RANKED n=12 / FACT-RETENTION n=…",
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"body": "… claim is not small-n noise)\n\nLift +0.358/+0.361/+0.469/+0.427 at D=1/2/4/8, all bootstrap CIs exclude 0\n(min lower bound +0.299); random-credit control negative. Reused cached\nembeddings (no re-embed). VERIFIED_NUMBERS + README updated to n=12.",
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"headline": "RAMR v0.1.5: harden OUTCOME-RANKED to n=12 sets (tighter CI, flagship…",
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"body": "…unchanged)",
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"headline": "mnemo: sync remember_dedup() opt-in NO-OP write (default append-only …",
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"oid": "26a443da64061e4f54c311c6383671d742e5bfbc",
"body": "…ll traceability)\n\nEvery public metric now has a persisted, recomputable source: FORGET-PRECISION\n(1.00/0.97), ABSTENTION (floor 0.6 -> 1.00/1.00), CROSS-SCOPE-LEAKAGE (scoped 0.00\nvs 0.82), SIGNAL-RELIABILITY break-even (lift crosses 0 at 1/(1+D)). Closes the\n'every number traceable' rigor bar for v0.1.2-0.1.4.",
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"headline": "RAMR: persist new-metric result JSONs + add VERIFIED_NUMBERS rows (fu…",
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"body": "… vendored mnemo\n\nShared store, 2 tenants, same schema: leaks A->B 79% without a scope; recall(scope='B')\n-> 0% leakage, 100% in-scope recall. Default scope=None unchanged.",
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"headline": "RAMR v0.1.4: cross-scope leakage metric + recall(scope=) isolation in…",
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"body": "…ored mnemo\n\nrecall(min_relevance) lets the engine return [] instead of confabulating a weak\nmatch; metric shows clean abstention (floor 0.6 -> 100% abstain on out-of-store,\n100% in-store recall) vs 0% abstention at floor 0.",
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"headline": "RAMR v0.1.3: abstention/false-recall metric + relevance-floor in vend…",
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"oid": "33d896b0c79cd8f7ad59448a7a06e0debb371560",
"body": "…erization\n\nramr_breakeven.py sweeps credit reliability p x ambiguity D; recall-lift crosses\nzero at the predicted no-signal floor 1/(1+D), validating the signal-reliability\nlaw on the engine. Characterizes mnemo cal_mode (full/boost/gated) -- default\nstays 'full' (gain and backfire are the same suppression mechanism).",
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"headline": "RAMR v0.1.2: signal-reliability break-even harness + cal_mode charact…",
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"body": "…rsity stores\n\nRequire >=3 shared common words (not just >=12% coverage of a tiny common vocab)\nbefore flagging a memory a hub; otherwise templated stores got 100% hub-flagged\n-> 0% recall. Genuine universal-matcher hubs still caught.",
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"headline": "mnemo: fix hub over-flagging that silently emptied recall on low-dive…",
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"body": "… v0.1.1 archived",
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"headline": "Cite the Zenodo concept DOI (10.5281/zenodo.20818291, always-latest);…",
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"avatar_url": "https://avatars.githubusercontent.com/u/41733909?v=4"
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],
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{
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"documentation_url": "https://github.com/ossf/scorecard/blob/c395761df6afe1a69e476bc60a013a94bcbc153f/docs/checks.md#cii-best-practices"
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{
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"documentation_url": "https://github.com/ossf/scorecard/blob/c395761df6afe1a69e476bc60a013a94bcbc153f/docs/checks.md#dangerous-workflow"
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{
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"documentation_url": "https://github.com/ossf/scorecard/blob/c395761df6afe1a69e476bc60a013a94bcbc153f/docs/checks.md#dependency-update-tool"
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{
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"documentation_url": "https://github.com/ossf/scorecard/blob/c395761df6afe1a69e476bc60a013a94bcbc153f/docs/checks.md#license"
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{
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"documentation_url": "https://github.com/ossf/scorecard/blob/c395761df6afe1a69e476bc60a013a94bcbc153f/docs/checks.md#packaging"
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{
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{
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"documentation_url": "https://github.com/ossf/scorecard/blob/c395761df6afe1a69e476bc60a013a94bcbc153f/docs/checks.md#security-policy"
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{
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"documentation_url": "https://github.com/ossf/scorecard/blob/c395761df6afe1a69e476bc60a013a94bcbc153f/docs/checks.md#signed-releases"
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{
"name": "Token-Permissions",
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"reason": "No tokens found",
"documentation_url": "https://github.com/ossf/scorecard/blob/c395761df6afe1a69e476bc60a013a94bcbc153f/docs/checks.md#token-permissions"
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{
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"documentation_url": "https://github.com/ossf/scorecard/blob/c395761df6afe1a69e476bc60a013a94bcbc153f/docs/checks.md#vulnerabilities"
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"config": {
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"source": {
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"host": "github.com",
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"metrics": {
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"components": []
},
"categories": [
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"band": "moderate",
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"metrics": [
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"key": "development_activity",
"band": "moderate",
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"note": null,
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{
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"points": 0,
"status": "missed",
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{
"key": "code_of_conduct",
"name": "Code of conduct",
"detail": null,
"points": 0,
"status": "missed",
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{
"key": "issue_template",
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],
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{
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"components": [
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}
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{
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{
"key": "openssf_scorecard_contributors",
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},
{
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"notes": [
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"code": "excluded_no_data",
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"code": "weights_renormalized",
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"code": "no_issues_or_data",
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{
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{
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"code": "excluded_no_data",
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},
{
"code": "weights_renormalized",
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]
}
],
"description": "Are baseline engineering and documentation practices in place?"
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{
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"weight": 0.16,
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{
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"note": "Excluded from scoring (no data or not applicable): CI-Tests, Dangerous-Workflow, Packaging, Pinned-Dependencies, Signed-Releases, Token-Permissions. Remaining weights renormalized.",
"notes": [
{
"code": "excluded_no_data",
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{
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{
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"points": 7.5,
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{
"key": "branch_protection",
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{
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{
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"points": 0,
"status": "missed",
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{
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"points": 0,
"status": "missed",
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},
{
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"status": "missed",
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{
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{
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{
"key": "fuzzing",
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{
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"points": 2.5,
"status": "met",
"details": [],
"max_points": 2.5
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{
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"points": 0,
"status": "missed",
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{
"key": "packaging",
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"status": "excluded",
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{
"code": "no_data",
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{
"key": "pinned_dependencies",
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"points": 0,
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"details": [
{
"code": "no_data",
"params": {}
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{
"key": "sast",
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"points": 0,
"status": "missed",
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{
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"detail": "security policy file not detected",
"points": 0,
"status": "missed",
"details": [],
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{
"key": "signed_releases",
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"code": "no_data",
"params": {}
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{
"key": "token_permissions",
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"detail": "No tokens found",
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"details": [
{
"code": "no_data",
"params": {}
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],
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{
"key": "vulnerabilities",
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"points": 7.5,
"status": "met",
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{
"key": "ai_readiness",
"band": "critical",
"name": "AI Readiness",
"value": 29,
"weight": 0,
"metrics": [
{
"key": "ai_agent_context",
"band": "at_risk",
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"note": null,
"notes": [],
"value": 40,
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"legible_history_share": 0.902,
"agent_instruction_files": [],
"agent_instruction_max_bytes": null
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"components": [
{
"key": "agent_instructions",
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"points": 0,
"status": "missed",
"details": [
{
"code": "no_agent_instructions",
"params": {}
}
],
"max_points": 45
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{
"key": "machine_readable_docs_llms_txt",
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"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 15
},
{
"key": "legible_commit_history",
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"detail": "37 of 41 human commits state their intent (structured subject or explanatory body)",
"points": 40,
"status": "met",
"details": [
{
"code": "legible_history",
"params": {
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}
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}
]
},
{
"key": "ai_verify_loop",
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"note": "Excluded from scoring (no data or not applicable): OpenSSF Scorecard: Pinned-Dependencies. Remaining weights renormalized.",
"notes": [
{
"code": "excluded_no_data",
"params": {
"components": [
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{
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}
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"lockfiles": [],
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"typed_language": false,
"bootstrap_files": [],
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"toolchain_manifests": [],
"dependency_bot_commit_share": 0
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{
"key": "one_command_bootstrap",
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{
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{
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"points": 0,
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{
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"detail": null,
"points": 0,
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},
{
"key": "reproducible_environment",
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"detail": null,
"points": 0,
"status": "missed",
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},
{
"key": "demonstrated_agent_practice",
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"points": 10,
"status": "met",
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{
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"points": 0,
"status": "missed",
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],
"max_points": 8
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{
"key": "openssf_scorecard_pinned_dependencies",
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{
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{
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"points": 53.3,
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"oversized": 1
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"description": "How well is the repo equipped to be developed and maintained with AI coding agents? An independent, experimental badge — weight 0.0, so it is surfaced on its own and does not affect the overall health score."
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],
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