Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-10-07 10:48 UTC

sineframe / m3

PythonCustom license★ 7 stars⑂ 2 forkssince Sep 2026View on GitHub ↗
KindMCP serverNetwork serviceCommand-line toolLibraryhow this is determined
#mcp-tools#mcp#model-context-protocol#mcp-testing

sineframe/m3 holds a health index of 62 out of 100, placing it in the Moderate band. It scores highest on AI Readiness (84/100) and lowest on Security (27/100). It was last updated today. A single contributor accounts for most of its recent work.

62
overall / 100
Moderate

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.

62
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 58 is calibrated to 62 on the published index scale (record calibration 2026-08-02).

Ownership

SineframeOrganization
0 followers1 public reposince Sep 2026

This repository is backed by an organization — shared, accountable stewardship that can outlive any single maintainer.

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIsf-m3-app0.2.372,217300 days ago—
PyPIsf-m3-cli0.2.372,009300 days ago—
PyPIsf-m30.2.372,670300 days agoagentsmcpmodel-context-protocolpytesttesting

Metrics by category

Vitality

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

71Good · 21% of overall

Development activity

59Moderate
How it's scored
36/36Push recency — last push 0 days ago
4.8/36Commit cadence — 7/52 weeks with commits
18/18Commit volume — 260 commits in the last year
0/10OpenSSF Scorecard: Maintained — project was created within the last 90 days. Please review its contents carefully
Inputs used
commits_last_year260
human_commit_share1
days_since_last_push0
active_weeks_last_year7

Release discipline

90Excellent
How it's scored
27/27Ships releases — 31 releases published
36/36Release recency — latest release 0 days ago
27/27Release cadence — a release every ~0.4 days
0/10OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases.
Inputs used
releases_count31
latest_release_tagv0.2.37
releases_from_tagsno
days_since_latest_release0
mean_days_between_releases0.4

Community & Adoption

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

42Weak · 17% of overall

Popularity & adoption

13Critical
How it's scored
12.6/60Stars — 7 stars
0/25Forks — 2 forks
0/15Watchers — 1 watchers
Inputs used
forks2
stars7
watchers1
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

64Moderate
How it's scored
22.5/22.5README
16.9/22.5License — license file present, not a recognized license
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges1
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_servicesgithub.com
has_pull_request_templateno

Ecosystem adoption (downloads)

57Moderate
How it's scored
45.7/80Monthly downloads — 2,670 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagessf-m3
dependents—
ecosystemspypi
total_downloads—
monthly_downloads2,670
unverified_packages_excludedsf-m3-app, sf-m3-cli
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?

54Moderate · 23% of overall

Maintainer resilience (bus factor)

20At Risk
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
2.2/22.5Commit distribution — top contributor authored 90% of commits
2.7/13.5Contributor breadth — 2 contributors
6/10OpenSSF Scorecard: Contributors — project has 2 contributing companies or organizations -- score normalized to 6
Inputs used
bus_factor1
contributors_sampled2
top_contributor_share0.9

Issue & PR responsiveness

81Excellent
How it's scored
42/42Issue resolution — 100% of issues closed
28.5/30PR acceptance — 117/123 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_prs117
open_issues0
closed_issues1
prs_merged_7d57
prs_decided_7d60
prs_merged_30d57
prs_decided_30d60
issue_closed_ratio1
closed_unmerged_prs6
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
30/30Ownership backing — organization-owned
0/20Verified domain
0/25Owner reach — 0 followers of sineframe
2.3/25Track record — 1 public repos, account ~0 yr old
Inputs used
followers0
owner_typeOrganization
is_verifiedno
owner_loginsineframe
public_repos1
account_age_days28

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 3 package(s) on pypi
35/35Publish recency — latest publish 0 days ago
20/20Version history — 30 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagessf-m3-app, sf-m3-cli, sf-m3
ecosystemspypi
any_deprecatedno
min_days_since_publish0

Engineering Quality

Are baseline engineering and documentation practices in place?

82Excellent · 19% of overall

Engineering practices

84Excellent
How it's scored
24/24CI workflows — 4 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff])
0/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 27 out of 27 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

80Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://m3.sineframe.com
0/10Repository description
10/10Topics — 4 topics
0/10Wiki
Inputs used
topicsmcp-tools, mcp, model-context-protocol, mcp-testing
has_wikino
homepagehttps://m3.sineframe.com
docs_sitehttps://m3.sineframe.com
has_readmeyes
has_docs_diryes
has_descriptionno

Security

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

27At Risk · 16% of overall

Security posture

27At Risk
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — branch protection not enabled on development/release branches
2.5/2.5CI-Tests — 27 out of 27 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
1.5/2.5Contributors — project has 2 contributing companies or organizations -- score normalized to 6
10/10Dangerous-Workflow — no dangerous workflow patterns detected
0/7.5Dependency-Update-Tool — no update tool detected
0/5Fuzzing — project is not fuzzed
2.2/2.5License — license file detected
0/7.5Maintained — project was created within the last 90 days. Please review its contents carefully
0/5Packaging — no data
3.5/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 7
0/5SAST — SAST tool is not run on all commits -- score normalized to 0
0/5Security-Policy — security policy file not 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
0/7.5Vulnerabilities — 17 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate2.7
Excluded from scoring (no data or not applicable): Packaging. 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.

84Excellent · 4% of overall

Agent context & guidance

100Exceptional
How it's scored
45/45Agent instructions — docs/site/guides/elicitation/agents.md, docs/site/troubleshooting/agents.md
15/15Machine-readable docs (llms.txt) — llms.txt served by the project website (https://m3.sineframe.com/llms.txt)
40/40Legible commit history — 83 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtyes
llms_txt_urlhttps://m3.sineframe.com/llms.txt
legible_history_share0.83
agent_instruction_filesdocs/site/guides/elicitation/agents.md, docs/site/troubleshooting/agents.md
agent_instruction_max_bytes8,291

Verify loop (build / test / typecheck)

83Excellent
How it's scored
18/18One-command bootstrap — justfile
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff])
11/11Static type checking — app/src/m3_app/py.typed, sdk/src/m3/py.typed
10/10Reproducible environment — lockfile
4/10Demonstrated agent practice — 2 of the last 100 commits agent-authored or agent-credited
0/8Automated maintenance — no automated dependency updates observed
7/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 7
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileno
typed_languageno
bootstrap_filesjustfile
has_devcontainerno
has_linter_configyes
typecheck_configsapp/src/m3_app/py.typed, sdk/src/m3/py.typed
agent_commit_share0.02
toolchain_manifests—
dependency_bot_commit_share0

Code legibility for models

80Excellent
How it's scored
27/45Type-checkable code — Python with type-check config (app/src/m3_app/py.typed, sdk/src/m3/py.typed)
52.8/55Manageable file sizes — 22/552 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes259,577
source_files_sampled552
oversized_source_files22

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

7GitHub stars
2contributors
260commits, last 12 months
0days since last push
31releases
1bus factor
0open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository
  • deps.dev does not index pypi:sf-m3-app@0.2.37; advisories assessed against the repository dependency graph instead

More detail

OpenSSF Scorecard 2.7 / 10
2.7aggregate

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 · 2026-10-07 10:47 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
10CI-Tests27 out of 27 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
6Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
9Licenselicense file detected
0Maintainedproject was created within the last 90 days. Please review its contents carefully
n/aPackagingpackaging workflow not detected
7Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 7
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
0Signed-ReleasesProject has not signed or included provenance with any releases.
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0Vulnerabilities17 existing vulnerabilities detected
Direct dependencies 21
RegistryPackageVersion constraintManifest
PyPIsf-m3==0.2.0a13app/pyproject.toml
PyPIfastapi>=0.115,<1app/pyproject.toml
PyPIpydantic-settings>=2.4,<3app/pyproject.toml
PyPIuvicorn>=0.30,<1app/pyproject.toml
PyPIsf-m3==0.2.0a13cli/pyproject.toml
PyPIsf-m3-app==0.2.0a13cli/pyproject.toml
PyPIkeyring>=25,<26cli/pyproject.toml
PyPIagent-client-protocol==0.12.1sdk/pyproject.toml
PyPIanyio>=4.5,<5sdk/pyproject.toml
PyPIhttpcore>=1,<2sdk/pyproject.toml
PyPIhttpcore2>=2.5,<3sdk/pyproject.toml
PyPIhttpx>=0.27,<1sdk/pyproject.toml
PyPIhttpx2>=2.5,<3sdk/pyproject.toml
PyPIidna>=3,<4sdk/pyproject.toml
PyPIjsonschema>=4.20,<5sdk/pyproject.toml
PyPImcp>=2.0.0,<3sdk/pyproject.toml
PyPIpydantic>=2.8,<3sdk/pyproject.toml
PyPIpython-dotenv>=1,<2sdk/pyproject.toml
PyPIstarlette>=0.40,<2sdk/pyproject.toml
PyPItomli>=2,<3sdk/pyproject.toml
PyPIuvicorn>=0.30,<1sdk/pyproject.toml
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

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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 v2.10.0, schema v0.34.0 — full methodology · metrics wiki.

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