Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-10-21 05:15 UTC

Alberto-Codes / docvet

Comprehensive docstring quality vetting for Python projects

PythonMIT★ 9 stars⑂ 1 forksince Feb 2026View on GitHub ↗
KindCommand-line toolLibraryhow this is determined

Alberto-Codes/docvet holds a health index of 83 out of 100, placing it in the Excellent band. It scores highest on Engineering Quality (92/100) and lowest on Community & Adoption (50/100). 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

Alberto-CodesPersonal account
19 followers113 public repossince Nov 2021

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

Package ecosystems

Metrics by category

Vitality

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

83Excellent · 21% of overall
How it's scored
36/36Push recency — last push 0 days ago
7.6/36Commit cadence — 11/52 weeks with commits
18/18Commit volume — 328 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 30 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year328
human_commit_share0.93
days_since_last_push0
active_weeks_last_year11

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 34 releases published
36/36Release recency — latest release 0 days ago
27/27Release cadence — a release every ~23.6 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count34
latest_release_tagv2.0.3
releases_from_tagsno
days_since_latest_release0
mean_days_between_releases23.6
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?

50Moderate · 17% of overall
How it's scored
14.6/60Stars — 9 stars
0/25Forks — 1 forks
0/15Watchers — 1 watchers
Inputs used
forks1
stars9
watchers1
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (MIT)
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges8
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_servicescodecov.io, shields.io
has_pull_request_templateyes
How it's scored
55.5/80Monthly downloads — 14,540 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesdocvet
dependents—
ecosystemspypi
total_downloads—
monthly_downloads14,540
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?

54Moderate · 23% of overall
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
0/22.5Commit distribution — top contributor authored 100% of commits
1.4/13.5Contributor breadth — 1 contributors
0/10OpenSSF Scorecard: Contributors — project has 0 contributing companies or organizations -- score normalized to 0
Inputs used
bus_factor1
contributors_sampled1
top_contributor_share1
How it's scored
34.1/42Issue resolution — 81% of issues closed
26.7/30PR acceptance — 267/300 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_prs267
open_issues37
closed_issues159
prs_merged_7d22
prs_decided_7d26
prs_merged_30d22
prs_decided_30d26
issue_closed_ratio0.811
closed_unmerged_prs33
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
10/30Ownership backing — personal (user) account
0/20Verified domain — not applicable to user accounts
9.4/25Owner reach — 19 followers of Alberto-Codes
22.9/25Track record — 113 public repos, account ~4 yr old
Inputs used
followers19
owner_typeUser
is_verified—
owner_loginAlberto-Codes
public_repos113
account_age_days1,805
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 0 days ago
20/20Version history — 34 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesdocvet
ecosystemspypi
any_deprecatedno
min_days_since_publish0

Engineering Quality

Are baseline engineering and documentation practices in place?

92Excellent · 19% of overall
How it's scored
24/24CI workflows — 7 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff])
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://alberto-codes.github.io/docvet/
10/10Repository description
10/10Topics — 20 topics
0/10Wiki
Inputs used
topicscode-quality, docstring-checker, docstrings, documentation, github-actions, linter, mkdocs, pre-commit-hook, python, python3, static-analysis, docvet, ai-agent, ai-coding, ai-tools, developer-tools, llm-tools, mkdocstrings, docstring-linter, google-style-docstrings
has_wikino
homepagehttps://alberto-codes.github.io/docvet/
docs_sitehttps://alberto-codes.github.io/docvet/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

70Good · 16% of overall
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
2.2/7.5Branch-Protection — branch protection is not maximal on development and all release branches
2.5/2.5CI-Tests — 30 out of 30 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 30 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
5/5SAST — SAST tool is run on all commits
5/5Security-Policy — security policy file detected
0/7.5Signed-Releases — no data
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate6.2
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 advisories — no direct dependency carries a known advisory
0/25Indirect dependencies free of known advisories — transitive set not separable from development and test dependencies in this scope
0/40No advisories left outstanding — no advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages94
unassessed_packages0
affected_by_severitynone
direct_affected_packages0
Excluded from scoring (no data or not applicable): Indirect dependencies free of known advisories, No advisories left outstanding. Remaining weights renormalized. Matched 94 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.

74Good · 4% of overall
How it's scored
45/45Agent instructions — .github/instructions/mermaid.instructions.md, .github/instructions/sonarqube_mcp.instructions.md, AGENTS.md, CLAUDE.md
15/15Machine-readable docs (llms.txt) — llms.txt served by the project website (https://jsh9.github.io/pydoclint/llms.txt)
40/40Legible commit history — 93 of 93 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtyes
llms_txt_urlhttps://jsh9.github.io/pydoclint/llms.txt
legible_history_share1
agent_instruction_files.github/instructions/mermaid.instructions.md, .github/instructions/sonarqube_mcp.instructions.md, AGENTS.md, CLAUDE.md
agent_instruction_max_bytes7,953
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff])
11/11Static type checking — src/docvet/py.typed
10/10Reproducible environment — lockfile
6/10Demonstrated agent practice — 3 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance — 7 of the last 100 commits are automated dependency updates
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_configssrc/docvet/py.typed
agent_commit_share0.03
toolchain_manifests—
dependency_bot_commit_share0.07
How it's scored
27/45Type-checkable code — Python with type-check config (src/docvet/py.typed)
53.2/55Manageable file sizes — 3/94 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes132,910
source_files_sampled94
oversized_source_files3
How it's scored
0/40API schema (OpenAPI/GraphQL/proto) — not applicable to this kind of software
20/20MCP server
0/40Runnable examples
Inputs used
example_dirs—
has_mcp_signalyes
api_schema_files—
interfaces_expected_of—
Excluded from scoring (no data or not applicable): API schema (OpenAPI/GraphQL/proto). Remaining weights renormalized.

Key facts

9GitHub stars
1contributors
328commits, last 12 months
0days since last push
34releases
1bus factor
37open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • deps.dev does not index pypi:docvet@2.0.3; advisories assessed against the repository dependency graph instead

More detail

OpenSSF Scorecard 6.2 / 10
6.2aggregate

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 · 2026-10-21 05:15 UTC

10Binary-Artifactsno binaries found in the repo
3Branch-Protectionbranch protection is not maximal on development and all release branches
10CI-Tests30 out of 30 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 30 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
10SASTSAST tool is run on all commits
10Security-Policysecurity policy file detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 1
RegistryPackageVersion constraintManifest
PyPItyper>=0.9pyproject.toml
All dependencies 94

Full resolved dependency set from the GitHub dependency graph: 1 direct and 93 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPItyper0.27.2direct
PyPIannotated-doc0.0.5indirect
PyPIannotated-types0.8.0indirect
PyPIanyio4.15.0indirect
PyPIattrs26.1.0indirect
PyPIbabel2.18.0indirect
PyPIbackrefs8.0indirect
PyPIcattrs26.1.0indirect
PyPIcertifi2026.10.19indirect
PyPIcffi2.1.1indirect
PyPIcharset-normalizer3.5.1indirect
PyPIclick8.5.0indirect
PyPIcolorama0.4.6indirect
PyPIcomrak0.0.16indirect
PyPIcoverage7.16.0indirect
PyPIcryptography50.0.1indirect
PyPIdocutils0.23indirect
PyPIdocvet2.0.3indirect
PyPIghp-import2.1.0indirect
PyPIgriffelib2.2.0indirect
PyPIgrimp3.16indirect
PyPIh110.16.0indirect
PyPIhjson3.1.0indirect
PyPIhttpcore1.0.9indirect
PyPIhttpx0.28.1indirect
PyPIhttpx-sse0.4.3indirect
PyPIidna3.19indirect
PyPIimport-linter2.14indirect
PyPIiniconfig2.3.0indirect
PyPIjinja23.1.6indirect
PyPIjsonschema4.26.0indirect
PyPIjsonschema-specifications2025.9.1indirect
PyPIlsprotocol2025.0.0indirect
PyPImarkdown3.10.3indirect
PyPImarkdown-it-py4.2.0indirect
PyPImarkupsafe3.0.3indirect
PyPImcp1.30.0indirect
PyPImdurl0.1.2indirect
PyPImergedeep1.3.4indirect
PyPImkdocs1.6.1indirect
PyPImkdocs-autorefs1.4.4indirect
PyPImkdocs-gen-files0.6.1indirect
PyPImkdocs-get-deps0.2.2indirect
PyPImkdocs-literate-nav0.6.3indirect
PyPImkdocs-macros-plugin1.5.0indirect
PyPImkdocs-material9.7.7indirect
PyPImkdocs-material-extensions1.3.1indirect
PyPImkdocs-section-index0.3.12indirect
PyPImkdocstrings1.0.6indirect
PyPImkdocstrings-python2.0.8indirect
PyPInh30.3.7indirect
PyPIpackaging26.3indirect
PyPIpaginate0.5.7indirect
PyPIpathspec1.1.1indirect
PyPIplatformdirs4.11.7indirect
PyPIpluggy1.6.0indirect
PyPIproperdocs1.6.7indirect
PyPIpycparser3.0indirect
PyPIpydantic2.13.5indirect
PyPIpydantic-core2.46.5indirect
PyPIpydantic-settings2.15.0indirect
PyPIpygls2.1.1indirect
PyPIpygments2.21.0indirect
PyPIpyjwt2.15.1indirect
PyPIpymdown-extensions11.0.2indirect
PyPIpytest9.1.1indirect
PyPIpytest-cov7.1.0indirect
PyPIpytest-mock3.15.1indirect
PyPIpytest-randomly5.0.0indirect
PyPIpython-dateutil2.9.0.post0indirect
PyPIpython-dotenv1.2.3indirect
PyPIpython-multipart0.0.32indirect
PyPIpywin32312indirect
PyPIpyyaml6.0.3indirect
PyPIpyyaml-env-tag1.1indirect
PyPIreadme-renderer46.0indirect
PyPIreferencing0.37.0indirect
PyPIrequests2.34.2indirect
PyPIrich15.0.0indirect
PyPIrpds-py2026.6.3indirect
PyPIruff0.16.5indirect
PyPIshellingham1.5.4indirect
PyPIsix1.17.0indirect
PyPIsse-starlette3.4.8indirect
PyPIstarlette1.6.0indirect
PyPIsuper-collections0.6.2indirect
PyPItermcolor3.3.0indirect
PyPIty0.0.78indirect
PyPItyping-extensions4.16.0indirect
PyPItyping-inspection0.4.4indirect
PyPIurllib32.8.0indirect
PyPIuvicorn0.52.4indirect
PyPIwatchdog6.0.0indirect
PyPIyamllint1.38.0indirect
Dependency advisories 0

This repository publishes no package the index resolves, so its own dependency graph was assessed — 94 packages, which also include development and test pins that never ship: 0 carry known advisories, of which 0 are direct.

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 statistics — PyPI.