Public recordAt risk
Software health reportschema 0.27.0 · metrics 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 holds a health index of 34 out of 100, placing it in the At risk band. It scores highest on Vitality (66/100) and lowest on Sustainability & Governance (20/100). It was last updated 4 days ago. A single contributor accounts for most of its recent work.
34
overall / 100Software health index
Metrics are grouped into weighted categories on one standardized 1–100 scale. Overall starts as their weighted mean; when public evidence triggers the High-Risk Jurisdiction Policy, the rating is adjusted and receives an At risk ceiling of 49. AI Readiness sits outside the overall score.
34
Excellent85-100Exemplary; meets essentially all checked criteria
Good70-84Healthy; minor gaps
Moderate50-69Acceptable with notable gaps; review recommended
At risk30-49Significant weaknesses; adoption warrants caution
Critical1-29Severe problems (abandoned, single-maintainer, no hygiene)
Score profile
Each axis is a category. The shape matters more than the average — a healthy subject fills the whole shape, while a spike-and-crater profile means strength in one dimension is masking risk in another.
Ownership
Rastislav DrahošPersonal account
5 followers44 public repossince Jul 2018
This repository is owned by a personal account. A single-owner project carries more continuity risk than an organization-backed one.
Metrics by category
Vitality
Is the project alive — is code being written and are releases shipping?
66
Development activity
54Moderate
How it's scored
| 36/36 | Push recency — last push 4 days ago |
| 3.5/36 | Commit cadence — 5/52 weeks with commits |
| 14.6/18 | Commit volume — 41 commits in the last year |
| 0/10 | OpenSSF Scorecard: Maintained — project was created within the last 90 days. Please review its contents carefully |
Inputs used
| commits_last_year | 41 |
| human_commit_share | 1 |
| days_since_last_push | 4 |
| active_weeks_last_year | 5 |
Release discipline
84Good
How it's scored
| 27/27 | Ships releases — 1 releases published |
| 36/36 | Release recency — latest release 30 days ago |
| 12.6/27 | Release cadence — cadence unknown (single release) |
| 0/10 | OpenSSF Scorecard: Signed-Releases — no data |
Inputs used
| releases_count | 1 |
| latest_release_tag | v0.4.1 |
| releases_from_tags | no |
| days_since_latest_release | 30 |
| mean_days_between_releases | — |
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: Signed-Releases. Remaining weights renormalized.
Community & Adoption
Does the project have users, downloads, attention, and a welcoming setup for contributors?
24
Popularity & adoption
1Critical
How it's scored
| 0/60 | Stars — 0 stars |
| 0/25 | Forks — 0 forks |
| 0/15 | Watchers — 0 watchers |
Inputs used
| forks | 0 |
| stars | 0 |
| watchers | 0 |
| growth_state | unverified |
| growth_factor_pct | 100 |
| growth_unverified_reason | no_history |
Community health
50Moderate
How it's scored
| 22.5/22.5 | README |
| 22.5/22.5 | License — recognized license (MIT) |
| 0/18 | CONTRIBUTING guide |
| 0/13.5 | Code of conduct |
| 0/7.2 | Issue template |
| 0/6.3 | PR template |
Inputs used
| has_readme | yes |
| has_license | yes |
| has_contributing | no |
| has_issue_template | no |
| has_code_of_conduct | no |
| has_pull_request_template | no |
Sustainability & Governance
Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?
20
Maintainer resilience (bus factor)
10Critical
How it's scored
| 9/54 | Bus factor — 1 contributor(s) cover half of all commits |
| 0/22.5 | Commit distribution — top contributor authored 100% of commits |
| 1.4/13.5 | Contributor breadth — 1 contributors |
| 0/10 | OpenSSF Scorecard: Contributors — project has 0 contributing companies or organizations -- score normalized to 0 |
Inputs used
| bus_factor | 1 |
| contributors_sampled | 1 |
| top_contributor_share | 1 |
Issue & PR responsiveness
1Critical
How it's scored
| 0/46.8 | Issue resolution — no issues or no data |
| 0/38.3 | PR acceptance — no decided pull requests or no data |
| 0/15 | OpenSSF Scorecard: Code-Review — Found 0/30 approved changesets -- score normalized to 0 |
Inputs used
| merged_prs | 0 |
| open_issues | 0 |
| closed_issues | 0 |
| issue_closed_ratio | — |
| closed_unmerged_prs | 0 |
Excluded from scoring (no data or not applicable): Issue resolution, PR acceptance. Remaining weights renormalized.
Ownership & stewardship
50Moderate
How it's scored
| 10/30 | Ownership backing — personal (user) account |
| 0/20 | Verified domain — not applicable to user accounts |
| 5.6/25 | Owner reach — 5 followers of DanceNitra |
| 24/25 | Track record — 44 public repos, account ~8 yr old |
Inputs used
| followers | 5 |
| owner_type | User |
| is_verified | — |
| owner_login | DanceNitra |
| public_repos | 44 |
| account_age_days | 2,924 |
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.
Engineering Quality
Are baseline engineering and documentation practices in place?
31
Engineering practices
1Critical
How it's scored
| 0/24 | CI workflows |
| 0/24 | Tests present |
| 0/16 | Linter config |
| 0/9.6 | Pre-commit hooks |
| 0/6.4 | .editorconfig |
| 0/20 | OpenSSF Scorecard: CI-Tests — no data |
Inputs used
| has_ci | no |
| has_tests | no |
| has_editorconfig | no |
| has_linter_config | no |
| has_precommit_config | no |
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: CI-Tests. Remaining weights renormalized.
Documentation
75Good
How it's scored
| 30/30 | README |
| 0/25 | Documentation directory |
| 15/15 | Documentation / homepage site — https://dancenitra.github.io/agora/public/leaderboard/ |
| 10/10 | Repository description |
| 10/10 | Topics — 6 topics |
| 10/10 | Wiki |
Inputs used
| topics | agent-memory, benchmark, evaluation, llm, rag, retrieval |
| has_wiki | yes |
| homepage | https://dancenitra.github.io/agora/public/leaderboard/ |
| has_readme | yes |
| has_docs_dir | no |
| has_description | yes |
Security
Are visible security and supply-chain practices strong, without unresolved high-risk jurisdiction exposure?
26
Security posture
26Critical
How it's scored
| 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 — no data |
| 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 — no data |
| 0/7.5 | Dependency-Update-Tool — no update tool detected |
| 0/5 | Fuzzing — project is not fuzzed |
| 2.5/2.5 | License — license file detected |
| 0/7.5 | Maintained — project was created within the last 90 days. Please review its contents carefully |
| 0/5 | Packaging — no data |
| 0/5 | Pinned-Dependencies — no data |
| 0/5 | SAST — no SAST tool detected |
| 0/5 | Security-Policy — security policy file not detected |
| 0/7.5 | Signed-Releases — no data |
| 0/7.5 | Token-Permissions — no data |
| 7.5/7.5 | Vulnerabilities — 0 existing vulnerabilities detected |
Inputs used
| source | openssf_scorecard |
| checks_evaluated | 12 |
| scorecard_version | v5.5.0 |
| checks_inconclusive | 6 |
| scorecard_aggregate | 2.6 |
Excluded from scoring (no data or not applicable): ci_tests, dangerous_workflow, packaging, pinned_dependencies, signed_releases, token_permissions. Remaining weights renormalized.
AI Readiness
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.
29
Agent context & guidance
40At risk
How it's scored
| 0/45 | Agent instructions — no CLAUDE.md / AGENTS.md / editor rules |
| 0/15 | Machine-readable docs (llms.txt) |
| 40/40 | Legible commit history — 37 of 41 human commits state their intent (structured subject or explanatory body) |
Inputs used
| has_llms_txt | no |
| legible_history_share | 0.902 |
| agent_instruction_files | — |
| agent_instruction_max_bytes | — |
Verify loop (build / test / typecheck)
11Critical
How it's scored
| 0/18 | One-command bootstrap |
| 0/22 | Automated tests |
| 0/11 | Lint / format config |
| 0/11 | Static type checking |
| 0/10 | Reproducible environment |
| 10/10 | Demonstrated agent practice — 13 of the last 41 commits agent-authored or agent-credited |
| 0/8 | Automated maintenance — no automated dependency updates observed |
| 0/10 | OpenSSF Scorecard: Pinned-Dependencies — no data |
Inputs used
| has_nix | no |
| has_tests | no |
| lockfiles | — |
| has_dockerfile | no |
| typed_language | no |
| bootstrap_files | — |
| has_devcontainer | no |
| has_linter_config | no |
| typecheck_configs | — |
| agent_commit_share | 0.317 |
| toolchain_manifests | — |
| dependency_bot_commit_share | 0 |
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: Pinned-Dependencies. Remaining weights renormalized.
Code legibility for models
53Moderate
How it's scored
| 0/45 | Type-checkable code — Python without a type-check config |
| 53.3/55 | Manageable file sizes — 1/33 source files over 60KB |
Inputs used
| primary_language | Python |
| largest_source_bytes | 385,518 |
| source_files_sampled | 33 |
| oversized_source_files | 1 |
Key facts
0GitHub stars
1contributors
41commits, last 12 months
4days since last push
1releases
1bus factor
0open issues
—package ecosystems
Data collection warnings
- GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository
More detail
OpenSSF Scorecard 2.6 / 10
2.6aggregate
Independent, tool-agnostic security assessment from the open-source OpenSSF Scorecard. Each check rewards a security practice, not a specific vendor's tool. Checks Scorecard could not determine are marked n/a and excluded from the security score (never counted as zero).
| 10 | Binary-Artifacts | no binaries found in the repo |
| 0 | Branch-Protection | branch protection not enabled on development/release branches |
| n/a | 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 |
| n/a | 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 |
| n/a | Packaging | packaging workflow not detected |
| n/a | Pinned-Dependencies | no dependencies found |
| 0 | SAST | no SAST tool detected |
| 0 | Security-Policy | security policy file not detected |
| n/a | Signed-Releases | no releases found |
| n/a | Token-Permissions | No tokens found |
| 10 | Vulnerabilities | 0 existing vulnerabilities detected |
All dependencies not collected
The resolved dependency set could not be collected for this report: GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository
Raw JSON report machine-readable
{
"data": {
"repo": {
"topics": [
"agent-memory",
"benchmark",
"evaluation",
"llm",
"rag",
"retrieval"
],
"is_fork": false,
"size_kb": 715,
"has_wiki": true,
"homepage": "https://dancenitra.github.io/agora/public/leaderboard/",
"languages": {
"Python": 596480
},
"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)",
"is_archived": false,
"is_disabled": false,
"license_spdx": "MIT",
"default_branch": "main",
"license_spdx_raw": "MIT",
"primary_language": "Python",
"significant_languages": [
"Python"
]
},
"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>",
"is_bot": false,
"headline": "Add bi-temporal integrity cell (honest parity, not a mnemo win)",
"author_name": "agora-builder",
"author_login": null,
"committed_at": "2026-07-19T07:01:13Z",
"body_truncated": false,
"is_coding_agent": true
},
{
"oid": "f9fea43755fc3e4dc3c0d155f7ca4d9905e4fa36",
"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>",
"is_bot": false,
"headline": "Merge cross-system integrity + erasure self-check under RAMR",
"author_name": "agora-builder",
"author_login": null,
"committed_at": "2026-07-19T06:46:21Z",
"body_truncated": true,
"is_coding_agent": true
},
{
"oid": "203e1ea01829f8fb24b62d39fdf339a1be492d15",
"body": "…oral invalidation defends (0/26 echo-attributable); raw 0.87 residual = extraction misses, not echo",
"is_bot": false,
"headline": "echo-resistance: real Graphiti runtime (Neo4j+OpenAI, n=30) — bi-temp…",
"author_name": "agora-builder",
"author_login": null,
"committed_at": "2026-07-09T18:08:38Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "4fc78fc45ce503e42c101f14565ac030ef75f9a9",
"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>",
"is_bot": false,
"headline": "ECHO-RESISTANCE: mem0 measured in its NATIVE config (OpenAI) with a b…",
"author_name": "agora-builder",
"author_login": null,
"committed_at": "2026-07-09T14:48:33Z",
"body_truncated": true,
"is_coding_agent": true
},
{
"oid": "e746262a91439559559dc7e6bbb89175b0e75b70",
"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>",
"is_bot": false,
"headline": "ECHO-RESISTANCE: add honest Zep/Graphiti note (code-verified defends;…",
"author_name": "agora-builder",
"author_login": null,
"committed_at": "2026-07-09T14:08:54Z",
"body_truncated": true,
"is_coding_agent": true
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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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"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": "mnemo: sync remember_dedup() opt-in NO-OP write (default append-only …",
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"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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{
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"ci_last_conclusion": null,
"oldest_open_issues": []
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"config": {
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"source": {
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"inputs": {
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"components": []
},
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{
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"points": 0,
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},
{
"key": "issue_template",
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"detail": null,
"points": 0,
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"key": "pr_template",
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{
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{
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{
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{
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]
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{
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"notes": [
{
"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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]
},
{
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"notes": [
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"code": "excluded_no_data",
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"components": [
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{
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"inputs": {
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{
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{
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{
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{
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{
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{
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{
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{
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],
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{
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"points": 0,
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"details": [
{
"code": "no_data",
"params": {}
}
],
"max_points": 5
},
{
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"points": 0,
"status": "missed",
"details": [],
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},
{
"key": "security_policy",
"name": "Security-Policy",
"detail": "security policy file not detected",
"points": 0,
"status": "missed",
"details": [],
"max_points": 5
},
{
"key": "signed_releases",
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"detail": "no releases found",
"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
"max_points": 7.5
},
{
"key": "token_permissions",
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"details": [
{
"code": "no_data",
"params": {}
}
],
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},
{
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"detail": "0 existing vulnerabilities detected",
"points": 7.5,
"status": "met",
"details": [],
"max_points": 7.5
}
]
}
],
"description": "Are visible security and supply-chain practices strong, with no malicious dependency and no unresolved high-risk jurisdiction exposure?"
},
{
"key": "ai_readiness",
"band": "critical",
"name": "AI Readiness",
"value": 29,
"weight": 0,
"metrics": [
{
"key": "ai_agent_context",
"band": "at_risk",
"name": "Agent context & guidance",
"note": null,
"notes": [],
"value": 40,
"inputs": {
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"legible_history_share": 0.902,
"agent_instruction_files": [],
"agent_instruction_max_bytes": null
},
"components": [
{
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"detail": "no CLAUDE.md / AGENTS.md / editor rules",
"points": 0,
"status": "missed",
"details": [
{
"code": "no_agent_instructions",
"params": {}
}
],
"max_points": 45
},
{
"key": "machine_readable_docs_llms_txt",
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"points": 0,
"status": "missed",
"details": [],
"max_points": 15
},
{
"key": "legible_commit_history",
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"points": 40,
"status": "met",
"details": [
{
"code": "legible_history",
"params": {
"legible": 37,
"sampled": 41
}
}
],
"max_points": 40
}
]
},
{
"key": "ai_verify_loop",
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"name": "Verify loop (build / test / typecheck)",
"note": "Excluded from scoring (no data or not applicable): OpenSSF Scorecard: Pinned-Dependencies. Remaining weights renormalized.",
"notes": [
{
"code": "excluded_no_data",
"params": {
"components": [
"openssf_scorecard_pinned_dependencies"
]
}
},
{
"code": "weights_renormalized",
"params": {}
}
],
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"inputs": {
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"lockfiles": [],
"has_dockerfile": false,
"typed_language": false,
"bootstrap_files": [],
"has_devcontainer": false,
"has_linter_config": false,
"typecheck_configs": [],
"agent_commit_share": 0.317,
"toolchain_manifests": [],
"dependency_bot_commit_share": 0
},
"components": [
{
"key": "one_command_bootstrap",
"name": "One-command bootstrap",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 18
},
{
"key": "automated_tests",
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"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 22
},
{
"key": "lint_format_config",
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"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 11
},
{
"key": "static_type_checking",
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"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 11
},
{
"key": "reproducible_environment",
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"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 10
},
{
"key": "demonstrated_agent_practice",
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"points": 10,
"status": "met",
"details": [
{
"code": "agent_authored_commits",
"params": {
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"sampled": 41
}
}
],
"max_points": 10
},
{
"key": "automated_maintenance",
"name": "Automated maintenance",
"detail": "no automated dependency updates observed",
"points": 0,
"status": "missed",
"details": [
{
"code": "no_dependency_automation",
"params": {}
}
],
"max_points": 8
},
{
"key": "openssf_scorecard_pinned_dependencies",
"name": "OpenSSF Scorecard: Pinned-Dependencies",
"detail": "no dependencies found",
"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
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}
]
},
{
"key": "ai_code_legibility",
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"note": null,
"notes": [],
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"inputs": {
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"largest_source_bytes": 385518,
"source_files_sampled": 33,
"oversized_source_files": 1
},
"components": [
{
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"detail": "Python without a type-check config",
"points": 0,
"status": "missed",
"details": [
{
"code": "no_typecheck_config_language",
"params": {
"language": "Python"
}
}
],
"max_points": 45
},
{
"key": "manageable_file_sizes",
"name": "Manageable file sizes",
"detail": "1/33 source files over 60KB",
"points": 53.3,
"status": "partial",
"details": [
{
"code": "oversized_source_files",
"params": {
"kb": 60,
"sampled": 33,
"oversized": 1
}
}
],
"max_points": 55
}
]
}
],
"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."
}
],
"metrics_version": "1.13.0"
},
"warnings": [
"GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository"
],
"report_type": "repository",
"generated_at": "2026-07-29T06:29:49.065660Z",
"schema_version": "0.27.0",
"badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/d/DanceNitra/ramr.svg",
"full_name": "DanceNitra/ramr",
"license_state": "standard",
"license_spdx": "MIT"
}Scores are signals, not warranties. They reflect publicly visible practices on GitHub — not a code audit, and not a security guarantee.
Missing data is excluded and weights renormalized, never scored as zero. Methodology is versioned and open: metrics v1.13.0, schema v0.27.0 — full methodology · metrics wiki.
How one result sits in the wider record: aggregate statistics.