Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-17 09:13 UTC

skynetcmd / m3-memory

Local-first Memory Framework for AI Agents · 99.2% LongMemEval-S retrieval @ k=10 · Supports Claude · Antigravity · LangChain · Hermes · Gemini · OpenCode · OpenClaw · MCP-native and plugins · Hybrid search (FTS5 + vector + MMR) · GDPR · FIPS 140-3 ready · 100% local (fully offline) or cloud capable

PythonApache-2.0★ 25 stars⑂ 3 forkssince Feb 2026View on GitHub ↗
KindCommand-line toolLibraryMCP serverNetwork servicehow this is determined
#agentic-memory#ai-agents#claude-code#gdpr#gemini-cli#local-llm#mcp#rag#vector-search#ai-memory#mcp-server#openclaw#privacy#fips-140-3#langchain#langgraph#mem0#agent-memory#knowledge-graph#long-term-memory

skynetcmd/m3-memory holds a health index of 83 out of 100, placing it in the Excellent band. It scores highest on Engineering Quality (90/100) and lowest on Sustainability & Governance (53/100). It was last updated today. A single contributor accounts for most of its recent work.

83
overall / 100
Excellent

Software health index

Metrics are grouped into weighted categories on one standardized 1–100 scale. Overall starts as their weighted mean, calibrated against the distribution of the public record so bands carry percentile meaning; when public evidence triggers the High-Risk Jurisdiction Policy, the rating is adjusted and receives an At Risk ceiling of 34.

83
Exceptional93-100The record's top tier (≈ top 5%); essentially all checked criteria met
Excellent80-92Strong across the board; minor gaps
Good65-79Healthy; gaps are limited and manageable
Moderate50-64Acceptable with notable gaps; review recommended
Weak35-49Material weaknesses across several areas
At Risk20-34Significant weaknesses; adoption warrants caution
Critical1-19Severe problems (abandoned, single-maintainer, no hygiene)
VitalityCommunity &AdoptionSustainability &GovernanceEngineeringQualitySecurityAI Readiness

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.

The weighted overall 70 is calibrated to 83 on the published index scale (record calibration 2026-08-02).

Ownership

skynetcmdPersonal account
4 followers5 public repossince Jan 2024

This repository is owned by a personal account. A single-owner project carries more continuity risk than an organization-backed one.

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIm3-memory2026.9.14.43,8611642 days agomcpmcp-servermodel-context-protocolagentic-memoryai-memorylong-term-memorylocal-llmclaudeclaude-codegeminigemini-cliaiderragrag-memoryvector-searchhybrid-searchsqlitegdprprivacyhomelabai-agentsollamacontradiction-detectionbitemporallocal-firstmulti-agentknowledge-graphpersistent-memorylongmemevalfips-140-3openclawassistant-memoryagent-memoryself-hostedofflineno-cloudeasy-installmcp-agent

Metrics by category

Vitality

Is the project alive — is code being written and are releases shipping?

84Excellent · 21% of overall

Development activity

80Excellent
How it's scored
36/36Push recency — last push 0 days ago
15.9/36Commit cadence — 23/52 weeks with commits
18/18Commit volume — 1,571 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 27 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year1,571
human_commit_share0.99
days_since_last_push0
active_weeks_last_year23

Release discipline

90Excellent
How it's scored
27/27Ships releases — 100 releases published
36/36Release recency — latest release 2 days ago
27/27Release cadence — a release every ~0.3 days
0/10OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases.
Inputs used
releases_count100
latest_release_tagv2026.9.14.4
releases_from_tagsno
days_since_latest_release2
mean_days_between_releases0.3

Community & Adoption

Does the project have users, downloads, attention, and a welcoming setup for contributors?

57Moderate · 17% of overall

Popularity & adoption

25At Risk
How it's scored
22.4/60Stars — 25 stars
2.5/25Forks — 3 forks
0/15Watchers — 1 watchers
Inputs used
forks3
stars25
watchers1
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

92Excellent
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (Apache-2.0)
18/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges0
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_services—
has_pull_request_templateyes

Ecosystem adoption (downloads)

60Moderate
How it's scored
47.8/80Monthly downloads — 3,861 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesm3-memory
dependents—
ecosystemspypi
total_downloads—
monthly_downloads3,861
unverified_packages_excluded—
Excluded from scoring (no data or not applicable): Registry dependents. Remaining weights renormalized.

Sustainability & Governance

Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?

53Moderate · 23% of overall

Maintainer resilience (bus factor)

18Critical
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
6.2/22.5Commit distribution — top contributor authored 72% of commits
2.7/13.5Contributor breadth — 2 contributors
0/10OpenSSF Scorecard: Contributors — project has 0 contributing companies or organizations -- score normalized to 0
Inputs used
bus_factor1
contributors_sampled2
top_contributor_share0.723

Issue & PR responsiveness

78Good
How it's scored
40.6/42Issue resolution — 97% of issues closed
27.2/30PR acceptance — 107/118 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — Found 0/30 approved changesets -- score normalized to 0
Inputs used
merged_prs107
open_issues1
closed_issues28
prs_merged_7d16
prs_decided_7d17
prs_merged_30d17
prs_decided_30d18
issue_closed_ratio0.966
closed_unmerged_prs11
first_time_authors_30d0
first_time_prs_merged_30d0
first_time_prs_decided_30d0
Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.

Ownership & stewardship

32At Risk
How it's scored
10/30Ownership backing — personal (user) account
0/20Verified domain — not applicable to user accounts
5/25Owner reach — 4 followers of skynetcmd
10.9/25Track record — 5 public repos, account ~2 yr old
Inputs used
followers4
owner_typeUser
is_verified—
owner_loginskynetcmd
public_repos5
account_age_days962
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 2 days ago
20/20Version history — 164 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesm3-memory
ecosystemspypi
any_deprecatedno
min_days_since_publish2

Engineering Quality

Are baseline engineering and documentation practices in place?

90Excellent · 19% of overall

Engineering practices

84Excellent
How it's scored
24/24CI workflows — 4 workflow(s)
24/24Tests present
16/16Linter config — eslint.config.js, pyproject.toml ([tool.ruff])
0/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 3 out of 3 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://github.com/skynetcmd/m3-memory
10/10Repository description
10/10Topics — 20 topics
10/10Wiki
Inputs used
topicsagentic-memory, ai-agents, claude-code, gdpr, gemini-cli, local-llm, mcp, rag, vector-search, ai-memory, mcp-server, openclaw, privacy, fips-140-3, langchain, langgraph, mem0, agent-memory, knowledge-graph, long-term-memory
has_wikiyes
homepagehttps://github.com/skynetcmd/m3-memory
docs_sitehttps://github.com/skynetcmd/m3-memory
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

Are visible security and supply-chain practices strong, without unresolved high-risk jurisdiction exposure?

63Moderate · 16% of overall

Security posture

63Moderate
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — no data
2.5/2.5CI-Tests — 3 out of 3 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0/7.5Code-Review — Found 0/30 approved changesets -- score normalized to 0
0/2.5Contributors — project has 0 contributing companies or organizations -- score normalized to 0
10/10Dangerous-Workflow — no dangerous workflow patterns detected
7.5/7.5Dependency-Update-Tool — update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
7.5/7.5Maintained — 30 commit(s) and 27 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
1/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 2
5/5SAST — SAST tool is run on all commits
5/5Security-Policy — security policy file detected
0/7.5Signed-Releases — Project has not signed or included provenance with any releases.
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate6.3
Excluded from scoring (no data or not applicable): Branch-Protection. Remaining weights renormalized.

AI Readiness

How well is the repo equipped to be developed and maintained with AI coding agents? Carries a deliberately small weight (4%): agent tooling is a real maintenance signal, but a repository with none can still reach 100/100.

73Good · 4% of overall

Agent context & guidance

85Excellent
How it's scored
45/45Agent instructions — AGENTS.md, CLAUDE.md, GEMINI.md, commands/agents.md, docs/AGENTS.md
0/15Machine-readable docs (llms.txt)
40/40Legible commit history — 97 of 99 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.98
agent_instruction_filesAGENTS.md, CLAUDE.md, GEMINI.md, commands/agents.md, docs/AGENTS.md
agent_instruction_max_bytes5,711

Verify loop (build / test / typecheck)

66Good
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config — eslint.config.js, pyproject.toml ([tool.ruff])
11/11Static type checking — examples/homelab-dashboard/frontend/tsconfig.json
10/10Reproducible environment — Dockerfile, lockfile
10/10Demonstrated agent practice — 13 of the last 100 commits agent-authored or agent-credited
0/8Automated maintenance — no automated dependency updates observed
2/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 2
Inputs used
has_nixno
has_testsyes
lockfilespackage-lock.json
has_dockerfileyes
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configyes
typecheck_configsexamples/homelab-dashboard/frontend/tsconfig.json
agent_commit_share0.13
toolchain_manifests—
dependency_bot_commit_share0

Code legibility for models

80Excellent
How it's scored
27/45Type-checkable code — Python with type-check config (examples/homelab-dashboard/frontend/tsconfig.json)
53.5/55Manageable file sizes — 20/748 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes173,495
source_files_sampled748
oversized_source_files20

Machine-readable interfaces

60Moderate
How it's scored
0/40API schema (OpenAPI/GraphQL/proto)
20/20MCP server
40/40Runnable examples — examples
Inputs used
example_dirsexamples
has_mcp_signalyes
api_schema_files—
interfaces_expected_ofnetwork-service

Key facts

25GitHub stars
2contributors
1,571commits, last 12 months
0days since last push
100releases
1bus factor
1open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • OSV advisory lookup failed: [Errno 101] Network is unreachable

More detail

Star and fork history 0 ★ / 3 ⇿
0Stars
3Forks
11Releases

When each star and fork was added, collected from GitHub and bucketed by day. Cumulative growth sits directly above the daily additions it is made of, so the two read against each other: steady organic accretion looks nothing like an abrupt, short-lived burst. Where that difference is measurable, it is reported as growth authenticity.

12233312026-042026-062026-07
Major 0Minor 0Patch 0
OpenSSF Scorecard 6.3 / 10
6.3aggregate

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).Scorecard v5.5.0 · 2026-09-17 09:10 UTC

10Binary-Artifactsno binaries found in the repo
n/aBranch-Protectioninternal error: error during branchesHandler.setup: internal error: some github tokens can't read classic branch protection rules: https://github.com/ossf/scorecard-action/blob/main/docs/authentication/fine-grained-auth-token.md
10CI-Tests3 out of 3 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 0/30 approved changesets -- score normalized to 0
0Contributorsproject has 0 contributing companies or organizations -- score normalized to 0
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 27 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
2Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 2
10SASTSAST tool is run on all commits
10Security-Policysecurity policy file detected
0Signed-ReleasesProject has not signed or included provenance with any releases.
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 23
RegistryPackageVersion constraintManifest
PyPIfastmcp>=3.2.4,<4pyproject.toml
PyPImcp>=1.28.1,<2pyproject.toml
PyPIhttpx>=0.28.1,<1pyproject.toml
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PyPIpywin32>=311pyproject.toml
PyPIpyobjc-framework-CoreWLAN—pyproject.toml
All dependencies 259

Full resolved dependency set from the GitHub dependency graph: 23 direct and 236 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

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npmpath-key3.1.1indirect
npmpicocolors1.1.1indirect
npmpicomatch4.0.4indirect
npmpostcss8.5.26indirect
npmprelude-ls1.2.1indirect
npmpunycode2.3.1indirect
npmreact19.2.4indirect
npmreact-dom19.2.4indirect
npmreact-refresh0.18.0indirect
npmresolve-from4.0.0indirect
npmrolldown1.0.0-rc.6indirect
npmscheduler0.27.0indirect
npmsemver6.3.1indirect
npmsemver7.7.4indirect
npmshebang-command2.0.0indirect
npmshebang-regex3.0.0indirect
npmsource-map-js1.2.1indirect
npmstrip-json-comments3.1.1indirect
npmsupports-color7.2.0indirect
npmtinyglobby0.2.15indirect
npmts-api-utils2.4.0indirect
npmtslib2.8.1indirect
npmtype-check0.4.0indirect
npmtypescript5.9.3indirect
npmtypescript-eslint8.56.1indirect
npmundici-types7.16.0indirect
npmupdate-browserslist-db1.3.3indirect
npmuri-js4.4.1indirect
npmvite8.0.0-beta.16indirect
npmwhich2.0.2indirect
npmword-wrap1.2.5indirect
npmyallist3.1.1indirect
npmyocto-queue0.1.0indirect
npmzod4.3.6indirect
npmzod-validation-error4.0.2indirect
PyPIargparse—indirect
PyPIbuild—indirect
PyPIcrewai—indirect
PyPIgliner—indirect
PyPIh2—indirect
PyPIhttpcore2—indirect
PyPIhttpx2—indirect
PyPIidna—indirect
PyPIlangchain-core—indirect
PyPIlanggraph—indirect
PyPIlangmem—indirect
PyPIm3-memory2026.7.15.1indirect
PyPImypy—indirect
PyPIpsycopg—indirect
PyPIpydantic-ai-slim—indirect
PyPIpytest—indirect
PyPIpytest-asyncio—indirect
PyPIruff—indirect
PyPIscipy—indirect
PyPIsentence-transformers—indirect
PyPIsetuptools—indirect
PyPIsqlite-vec—indirect
PyPItorch—indirect
PyPItransformers—indirect
PyPItwine—indirect
PyPItypes-pyyaml—indirect
PyPItypes-requests—indirect
PyPItypes-setuptools—indirect
Dependency advisories not assessed

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Missing data is excluded and weights renormalized, never scored as zero. Methodology is versioned and open: metrics v2.10.0, schema v0.34.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statistics — PyPI.