Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-08-22 11:10 UTC

mkdocstrings / python-legacy

A legacy Python handler for mkdocstrings.

Python · HTMLISC★ 3 stars⑂ 3 forkssince Dec 2021View on GitHub ↗

mkdocstrings/python-legacy holds a health index of 57 out of 100, placing it in the Moderate band. It scores highest on Engineering Quality (78/100) and lowest on Vitality (29/100). It was last updated 220 days ago. A single contributor accounts for most of its recent work.

57
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.

57
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 55 is calibrated to 57 on the published index scale (record calibration 2026-08-02).

Ownership

mkdocstringsOrganization
65 followers29 public repossince Dec 2020

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPImkdocstrings-python-legacy0.2.7225,1149457 days ago

Metrics by category

Vitality

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

29At Risk · 21% of overall
How it's scored
3.6/36Push recencylast push 220 days ago
0.7/36Commit cadence1/52 weeks with commits
4.3/18Commit volume2 commits in the last year
0/10OpenSSF Scorecard: Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
Inputs used
commits_last_year2
human_commit_share1
days_since_last_push220
active_weeks_last_year1
How it's scored
27/27Ships releases4 releases published
7.2/36Release recencylatest release 457 days ago
19.8/27Release cadencea release every ~85.6 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count4
latest_release_tag0.2.7
releases_from_tagsno
days_since_latest_release457
mean_days_between_releases85.6
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?

57Moderate · 17% of overall
How it's scored
4.9/60Stars3 stars
2.5/25Forks3 forks
0/15Watchers1 watchers
Inputs used
forks3
stars3
watchers1
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

92Excellent
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (ISC)
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_badges4
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_servicesgithub.com, shields.io
has_pull_request_templateyes
How it's scored
71.4/80Monthly downloads225,114 downloads/month across pypi
0/20Registry dependentsnot reported by this ecosystem
Inputs used
packagesmkdocstrings-python-legacy
dependents
ecosystemspypi
total_downloads
monthly_downloads225,114
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?

64Moderate · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
0.7/22.5Commit distributiontop contributor authored 97% of commits
4.1/13.5Contributor breadth3 contributors
10/10OpenSSF Scorecard: Contributorsproject has 3 contributing companies or organizations -- score normalized to 10
Inputs used
bus_factor1
contributors_sampled3
top_contributor_share0.971
How it's scored
42/42Issue resolution100% of issues closed
30/30PR acceptance2/2 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-ReviewFound 1/30 approved changesets -- score normalized to 0
Inputs used
merged_prs2
open_issues0
closed_issues8
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio1
closed_unmerged_prs0
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 backingorganization-owned
0/20Verified domainverified-domain status not read for this organization
13.1/25Owner reach65 followers of mkdocstrings
22.2/25Track record29 public repos, account ~5 yr old
Inputs used
followers65
owner_typeOrganization
is_verified
owner_loginmkdocstrings
public_repos29
account_age_days2,083
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.
How it's scored
25/25Published & resolvable1 package(s) on pypi
14/35Publish recencylatest publish 457 days ago
20/20Version history9 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesmkdocstrings-python-legacy
ecosystemspypi
any_deprecatedno
min_days_since_publish457

Engineering Quality

Are baseline engineering and documentation practices in place?

78Good · 19% of overall
How it's scored
24/24CI workflows2 workflow(s)
24/24Tests present
16/16Linter configruff.toml
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests0 out of 1 merged PRs checked by a CI test -- score normalized to 0
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 sitehttps://mkdocstrings.github.io/python-legacy
10/10Repository description
10/10Topics7 topics
10/10Wiki
Inputs used
topicspython, documentation, python-documentation, mkdocstrings-handler, mkdocstrings, mkdocs, autodoc
has_wikiyes
homepagehttps://mkdocstrings.github.io/python-legacy
docs_sitehttps://mkdocstrings.github.io/python-legacy
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

46Weak · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
0/7.5Branch-Protectionbranch protection not enabled on development/release branches
0/2.5CI-Tests0 out of 1 merged PRs checked by a CI test -- score normalized to 0
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0/7.5Code-ReviewFound 1/30 approved changesets -- score normalized to 0
2.5/2.5Contributorsproject has 3 contributing companies or organizations -- score normalized to 10
10/10Dangerous-Workflowno dangerous workflow patterns detected
0/7.5Dependency-Update-Toolno update tool detected
0/5Fuzzingproject is not fuzzed
2.5/2.5Licenselicense file detected
0/7.5Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
0/5Packagingno data
0/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0/5SASTSAST tool is not run on all commits -- score normalized to 0
0/5Security-Policysecurity policy file not detected
0/7.5Signed-Releasesno data
0/7.5Token-Permissionsdetected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate3.2
Excluded from scoring (no data or not applicable): Packaging, Signed-Releases. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisoriesno direct dependency carries a known advisory
25/25Indirect dependencies free of known advisoriesno indirect dependency carries a known advisory
0/40No advisories left outstandingno advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages20
unassessed_packages0
affected_by_severitynone
direct_affected_packages0
Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:mkdocstrings-python-legacy@0.2.7 runtime dependency closure — what installing the published package pulls in — 20 packages. 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.

63Moderate · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
15/15Machine-readable docs (llms.txt)llms.txt served by the project website (https://mkdocstrings.github.io/python-legacy/llms.txt)
40/40Legible commit history70 of 70 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtyes
llms_txt_urlhttps://mkdocstrings.github.io/python-legacy/llms.txt
legible_history_share1
agent_instruction_files
agent_instruction_max_bytes
How it's scored
18/18One-command bootstrapMakefile
22/22Automated tests
11/11Lint / format configruff.toml
11/11Static type checkingconfig/mypy.ini, src/mkdocstrings_handlers/py.typed
0/10Reproducible environment
0/10Demonstrated agent practiceno agent-authored commits among the last 70
0/8Automated maintenanceno automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfiles
has_dockerfileno
typed_languageno
bootstrap_filesMakefile
has_devcontainerno
has_linter_configyes
typecheck_configsconfig/mypy.ini, src/mkdocstrings_handlers/py.typed
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0
How it's scored
27/45Type-checkable codePython with type-check config (config/mypy.ini, src/mkdocstrings_handlers/py.typed)
55/55Manageable file sizes0/16 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes15,369
source_files_sampled16
oversized_source_files0

Key facts

3GitHub stars
3contributors
2commits, last 12 months
220days since last push
4releases
1bus factor
0open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token

More detail

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

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.

12233312022-022023-052024-09

Each point covers 3 days.

OpenSSF Scorecard 3.2 / 10
3.2aggregate

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 · 2026-08-22 11:10 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
0CI-Tests0 out of 1 merged PRs checked by a CI test -- score normalized to 0
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 1/30 approved changesets -- score normalized to 0
10Contributorsproject has 3 contributing companies or organizations -- score normalized to 10
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
0Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
n/aPackagingpackaging workflow not detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 3
RegistryPackageVersion constraintManifest
PyPImkdocstrings>=0.28.3pyproject.toml
PyPImkdocs-autorefs>=1.1pyproject.toml
PyPIpytkdocs>=0.14pyproject.toml
All dependencies 3

Full resolved dependency set from the GitHub dependency graph: 3 direct and 0 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPImkdocs-autorefsdirect
PyPImkdocstringsdirect
PyPIpytkdocsdirect
Dependency advisories 0

Installing pypi:mkdocstrings-python-legacy@0.2.7 pulls in 20 packages, direct and transitive: 0 carry known advisories, of which 0 are direct dependencies.

No known advisories affect the assessed dependencies.

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

Feedback

Spotted something off in this report, or have thoughts to share? Wrong measurements, missed tooling, ideas, questions — anything is welcome. Every message is read and gets a response.

The message is kept through sign-in.

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 statisticsPyPI.