Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-09 06:16 UTC

front-matter / commonmeta-py

Documentation

PythonMIT★ 19 stars⑂ 8 forkssince Nov 2022View on GitHub ↗
KindCommand-line toolLibraryhow this is determined

front-matter/commonmeta-py holds a health index of 67 out of 100, placing it in the Good band. It scores highest on Engineering Quality (84/100) and lowest on Security (41/100). It was last updated today. A single contributor accounts for most of its recent work.

67
overall / 100
Good

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.

67
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 61 is calibrated to 67 on the published index scale (record calibration 2026-08-02).

Ownership

Front MatterOrganization
11 followers137 public repossince Feb 2021

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIcommonmeta-py0.305-3380 days agobibtexcommonmetacrossrefcsldataciteinveniordmmetadataopenalexschemaorgscience

Metrics by category

Vitality

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

72Good · 21% of overall
How it's scored
36/36Push recency — last push 0 days ago
21.5/36Commit cadence — 31/52 weeks with commits
18/18Commit volume — 250 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year250
human_commit_share1
days_since_last_push0
active_weeks_last_year31
How it's scored
27/27Ships releases — 6 releases published
7.2/36Release recency — latest release 469 days ago
12.6/27Release cadence — a release every ~124.4 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count6
latest_release_tag0.113
releases_from_tagsno
days_since_latest_release469
mean_days_between_releases124.4
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?

52Moderate · 17% of overall
How it's scored
20.4/60Stars — 19 stars
7/25Forks — 8 forks
0/15Watchers — 2 watchers
Inputs used
forks8
stars19
watchers2
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

80Excellent
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (MIT)
0/18CONTRIBUTING guide
13.5/13.5Code of conduct
7.2/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges6
has_contributingno
has_issue_templateyes
has_code_of_conductyes
readme_badge_servicesgithub.com, shields.io, sonarcloud.io
has_pull_request_templateyes

Sustainability & Governance

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

53Moderate · 23% of overall
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
0.1/22.5Commit distribution — top contributor authored 100% of commits
5.4/13.5Contributor breadth — 4 contributors
10/10OpenSSF Scorecard: Contributors — project has 6 contributing companies or organizations
Inputs used
bus_factor1
contributors_sampled4
top_contributor_share0.997
How it's scored
26.9/42Issue resolution — 64% of issues closed
10/30PR acceptance — 31/93 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_prs31
open_issues9
closed_issues16
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.64
closed_unmerged_prs62
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.
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
7.8/25Owner reach — 11 followers of front-matter
24.2/25Track record — 137 public repos, account ~5 yr old
Inputs used
followers11
owner_typeOrganization
is_verifiedno
owner_loginfront-matter
public_repos137
account_age_days2,043

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 0 days ago
20/20Version history — 338 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagescommonmeta-py
ecosystemspypi
any_deprecatedno
min_days_since_publish0

Engineering Quality

Are baseline engineering and documentation practices in place?

84Excellent · 19% of overall
How it's scored
24/24CI workflows — 2 workflow(s)
24/24Tests present
16/16Linter config — .pylintrc, pyproject.toml ([tool.ruff])
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — no data
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: CI-Tests. Remaining weights renormalized.

Documentation

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://python.commonmeta.org
10/10Repository description
10/10Topics — 5 topics
0/10Wiki
Inputs used
topicsbibtex, citeproc, doi, metadata, python
has_wikino
homepagehttps://python.commonmeta.org
docs_sitehttps://python.commonmeta.org
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

41Weak · 16% of overall
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
0/2.5CI-Tests — no data
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
2.5/2.5Contributors — project has 6 contributing companies or organizations
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 0 issue activity found in the last 90 days -- score normalized to 10
0/5Packaging — no data
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
0/5SAST — no SAST tool detected
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — no data
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities — 34 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated15
scorecard_versionv5.5.0
checks_inconclusive3
scorecard_aggregate4.2
Excluded from scoring (no data or not applicable): CI-Tests, Packaging, Signed-Releases. Remaining weights renormalized.
How it's scored
6.3/35Direct dependencies free of known advisories — 4 affected: pillow 11.3.0 (critical 9.1), click 8.1.8 (high 7.2), orjson 3.11.5 (high 7.5), +1 more
0/25Indirect dependencies free of known advisories — transitive set not separable from development and test dependencies in this scope
23.1/40No advisories left outstanding — 4 advisory-carrying package(s) unaddressed past 90 days; oldest published 229 days ago
Inputs used
sourceosv
advisories62
affected_packages11
assessed_packages271
unassessed_packages0
affected_by_severitycritical 2, high 4, moderate 5
direct_affected_packages4
Excluded from scoring (no data or not applicable): Indirect dependencies free of known advisories. Remaining weights renormalized. Matched 271 resolved dependencies against OSV. This repository publishes no package the index resolves, so the repository dependency graph was assessed instead. That graph mixes development and test pins with shipped dependencies, so only the declared runtime dependencies are scored; transitive findings are reported as context and excluded from the score. Reachability is not analyzed.

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.

54Moderate · 4% of overall
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
40/40Legible commit history — 98 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.98
agent_instruction_files—
agent_instruction_max_bytes—
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config — .pylintrc, pyproject.toml ([tool.ruff])
0/11Static type checking
10/10Reproducible environment — lockfile
0/10Demonstrated agent practice — no agent-authored commits among the last 100
5/8Automated maintenance — dependency automation configured, none observed in the sampled commits
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileno
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configyes
typecheck_configs—
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0
How it's scored
0/45Type-checkable code — Python without a type-check config
50.6/55Manageable file sizes — 8/100 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes374,484
source_files_sampled100
oversized_source_files8
How it's scored
0/40API schema (OpenAPI/GraphQL/proto) — not applicable to this kind of software
0/20MCP server — not applicable to this kind of software
40/40Runnable examples — notebooks
Inputs used
example_dirsnotebooks
has_mcp_signalno
api_schema_files—
interfaces_expected_of—
Excluded from scoring (no data or not applicable): API schema (OpenAPI/GraphQL/proto), MCP server. Remaining weights renormalized.

Key facts

19GitHub stars
4contributors
250commits, last 12 months
0days since last push
6releases
1bus factor
9open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • pypi download statistics for 'commonmeta-py' unavailable this scan (stats endpoint failed after retries); adoption may be under-evidenced
  • deps.dev does not index pypi:commonmeta-py@0.305; advisories assessed against the repository dependency graph instead

More detail

Star and fork history 0 ★ / 8 ⇿
0Stars
8Forks
6Releases

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.

02468812023-032024-112026-07
Major 0Minor 1Patch 1

Each point covers 4 days.

OpenSSF Scorecard 4.2 / 10
4.2aggregate

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 · 2026-09-09 06:15 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
n/aCI-Testsno pull request found
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 0/30 approved changesets -- score normalized to 0
10Contributorsproject has 6 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
n/aPackagingpackaging workflow not detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0SASTno SAST tool detected
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0Vulnerabilities34 existing vulnerabilities detected
Direct dependencies 35
RegistryPackageVersion constraintManifest
PyPIcommonmeta-schema==1.0rc31pyproject.toml
PyPIdateparser>=1.1.7,<2pyproject.toml
PyPIPyYAML>=5.4pyproject.toml
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PyPIdatacite>=1.1.1,<2pyproject.toml
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PyPIorjson>=3.9.14,<4pyproject.toml
PyPIorjsonl>=1.0.0,<2pyproject.toml
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PyPIjsonschema-rs>=0.47pyproject.toml
PyPIweasyprint>=69,<70pyproject.toml
All dependencies 271

Full resolved dependency set from the GitHub dependency graph: 47 direct and 224 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

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PyPItypes-beautifulsoup44.12.0.20250516indirect
PyPItypes-dateparser1.3.0.20260206indirect
PyPItypes-dateparser1.4.3.20260907indirect
PyPItypes-html5lib1.1.11.20251117indirect
PyPItypes-html5lib1.1.11.20260518indirect
PyPItypes-pyyaml6.0.12.20250915indirect
PyPItypes-pyyaml6.0.12.20260906indirect
PyPItypes-webencodings0.5.0.20251108indirect
PyPItypes-webencodings0.6.0.20260907indirect
PyPItypes-xmltodict0.15.0.20250907indirect
PyPItyping-inspection0.4.2indirect
PyPItyping-inspection0.4.4indirect
PyPItzdata2026.3indirect
PyPItzlocal5.3.1indirect
PyPItzlocal5.4.4indirect
PyPIuri-template1.3.0indirect
PyPIuritemplate4.2.0indirect
PyPIurllib31.26.20indirect
PyPIurllib32.7.0indirect
PyPIvcrpy7.0.0indirect
PyPIvcrpy8.3.0indirect
PyPIwatchdog6.0.0indirect
PyPIwcwidth0.8.3indirect
PyPIwebcolors24.11.1indirect
PyPIwebcolors25.10.0indirect
PyPIwebencodings0.5.1indirect
PyPIwebencodings0.6.1indirect
PyPIwebsocket-client1.9.0indirect
PyPIwebsocket-client1.9.2indirect
PyPIwerkzeug3.1.8indirect
PyPIwrapt2.4.0indirect
PyPIxopen2.0.2indirect
PyPIxopen2.1.0indirect
PyPIyarl1.22.0indirect
PyPIzipp3.23.1indirect
PyPIzipp4.1.0indirect
PyPIzlib-ng1.0.0indirect
PyPIzopfli0.4.3indirect
Dependency advisories 11

This repository publishes no package the index resolves, so its own dependency graph was assessed — 271 packages, which also include development and test pins that never ship: 11 carry known advisories, of which 4 are direct.

PackageVersionRelationSeverityAdvisoriesFixed in
pillow11.3.0directcritical3612.3.0
black25.11.0indirectcritical326.3.1
click8.1.8directhigh18.3.3
orjson3.11.5directhigh13.11.6
urllib31.26.20indirecthigh102.7.0
vcrpy7.0.0indirecthigh18.2.1
requests2.32.5directmoderate22.33.0
bleach6.2.0indirectmoderate26.4.0
jupyter-server2.18.2indirectmoderate22.20.0
pytest8.4.2indirectmoderate29.0.3
setuptools82.0.1indirectmoderate283.0.0

An advisory means the version recorded in the dependency graph falls inside an advisory’s affected range. Reachability is not analysed, and the graph includes development and test pins — a finding may concern tooling rather than shipped software.

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.