Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-10-24 03:39 UTC

gepa-ai / gepa

Optimize prompts, code, and more with AI-powered Reflective Optimization

Jupyter Notebook · PythonMIT★ 7,122 stars⑂ 590 forkssince Aug 2025View on GitHub ↗
KindLibraryhow this is determined

gepa-ai/gepa holds a health index of 90 out of 100, placing it in the Excellent band. It scores highest on Vitality (93/100) and lowest on Security (46/100). It was last updated 1 day ago. A single contributor accounts for most of its recent work.

90
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.

90
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 76 is calibrated to 90 on the published index scale (record calibration 2026-08-02).

Ownership

GEPAOrganization
102 followers6 public repossince Aug 2025

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIgepa0.1.47,733,52736100 days ago

Metrics by category

Vitality

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

93Exceptional · 21% of overall

Development activity

95Exceptional
How it's scored
36/36Push recency — last push 1 days ago
31.2/36Commit cadence — 45/52 weeks with commits
18/18Commit volume — 507 commits in the last year
0/10OpenSSF Scorecard: Maintained — no data
Inputs used
commits_last_year507
human_commit_share0.91
days_since_last_push1
active_weeks_last_year45

Release discipline

90Excellent
How it's scored
27/27Ships releases — 45 releases published
27/36Release recency — latest release 100 days ago
27/27Release cadence — a release every ~22.1 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count45
latest_release_tagv0.1.4
releases_from_tagsno
days_since_latest_release100
mean_days_between_releases22.1

Community & Adoption

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

86Excellent · 17% of overall

Popularity & adoption

91Excellent
How it's scored
60/60Stars — 7,122 stars
23.1/25Forks — 590 forks
8/15Watchers — 28 watchers
Inputs used
forks590
stars7,122
watchers28
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

70Good
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
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges4
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_servicesbadgen.net, shields.io
has_pull_request_templateno

Ecosystem adoption (downloads)

100Exceptional
How it's scored
80/80Monthly downloads — 7,733,527 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesgepa
dependents—
ecosystemspypi
total_downloads—
monthly_downloads7,733,527
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?

61Moderate · 23% of overall

Maintainer resilience (bus factor)

36Weak
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
9.5/22.5Commit distribution — top contributor authored 58% of commits
13.5/13.5Contributor breadth — 58 contributors
0/10OpenSSF Scorecard: Contributors — no data
Inputs used
bus_factor1
contributors_sampled58
top_contributor_share0.577

Issue & PR responsiveness

67Good
How it's scored
19.1/42Issue resolution — 46% of issues closed
25.4/30PR acceptance — 271/320 decided PRs merged
12.1/13Newcomer PR acceptance — 13/14 first-time contributors' PRs merged in 30d
0/15OpenSSF Scorecard: Code-Review — no data
Inputs used
merged_prs271
open_issues73
closed_issues61
prs_merged_7d16
prs_decided_7d17
prs_merged_30d26
prs_decided_30d28
issue_closed_ratio0.455
closed_unmerged_prs49
first_time_authors_30d10
first_time_prs_merged_30d13
first_time_prs_decided_30d14

Ownership & stewardship

53Moderate
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
14.5/25Owner reach — 102 followers of gepa-ai
8.6/25Track record — 6 public repos, account ~1 yr old
Inputs used
followers102
owner_typeOrganization
is_verifiedno
owner_logingepa-ai
public_repos6
account_age_days445

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 100 days ago
20/20Version history — 36 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesgepa
ecosystemspypi
any_deprecatedno
min_days_since_publish100

Engineering Quality

Are baseline engineering and documentation practices in place?

87Excellent · 19% of overall

Engineering practices

92Excellent
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
0/20OpenSSF Scorecard: CI-Tests — no data
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

80Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://gepa-ai.github.io/gepa/
10/10Repository description
0/10Topics
0/10Wiki
Inputs used
topics—
has_wikino
homepagehttps://gepa-ai.github.io/gepa/
docs_sitehttps://gepa-ai.github.io/gepa/
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

Security posture

33At Risk
How it's scored
0/30Security policy (SECURITY.md)
25/25Dependabot config
0/25Dependency lockfiles — published library — lockfiles are an application concern, not expected
0/20CodeQL workflow
Inputs used
sourcefile_signals
lockfilesuv.lock
manifestsdocs/requirements.txt, pyproject.toml
has_codeql_workflowno
has_security_policyno
has_dependabot_configyes
Excluded from scoring (no data or not applicable): Dependency lockfiles. 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
advisories284
affected_packages28
assessed_packages218
unassessed_packages29
affected_by_severitycritical 4, high 15, moderate 8, low 1
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 218 resolved dependencies against OSV. 29 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list. 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.

89Excellent · 4% of overall

Agent context & guidance

100Exceptional
How it's scored
45/45Agent instructions — AGENTS.md, CLAUDE.md
15/15Machine-readable docs (llms.txt) — llms.txt served by the project website (https://mlflow.org/llms.txt)
40/40Legible commit history — 87 of 91 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtyes
llms_txt_urlhttps://mlflow.org/llms.txt
legible_history_share0.956
agent_instruction_filesAGENTS.md, CLAUDE.md
agent_instruction_max_bytes1,730

Verify loop (build / test / typecheck)

80Excellent
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff])
11/11Static type checking — pyrightconfig.json, src/gepa/py.typed
10/10Reproducible environment — lockfile
10/10Demonstrated agent practice — 40 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance — 9 of the last 100 commits are automated dependency updates
0/10OpenSSF Scorecard: Pinned-Dependencies — no data
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileno
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configyes
typecheck_configspyrightconfig.json, src/gepa/py.typed
agent_commit_share0.4
toolchain_manifests—
dependency_bot_commit_share0.09

Code legibility for models

81Excellent
How it's scored
27/45Type-checkable code — Jupyter Notebook with type-check config (pyrightconfig.json, src/gepa/py.typed)
54.3/55Manageable file sizes — 3/238 source files over 60KB
Inputs used
primary_languageJupyter Notebook
largest_source_bytes143,180
source_files_sampled238
oversized_source_files3

Machine-readable interfaces

100Exceptional
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 — examples, notebooks
Inputs used
example_dirsexamples, notebooks
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

7,122GitHub stars
58contributors
507commits, last 12 months
1days since last push
45releases
1bus factor
73open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • First-time contributor figures cover 12 of 15 authors (cap 12)
  • OpenSSF Scorecard did not return a usable result (killed by SIGKILL — most likely the container's memory limit; 2026/10/24 03:38:26 Warning: PATs stored in env variables GITHUB_AUTH_TOKEN and GITHUB_TOKEN differ. Scorecard will use the former.); skipping Scorecard checks

More detail

Star and fork history 0 ★ / 590 ⇿
0Stars
590Forks
45Releases

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.

0100200300400500600586132025-082026-032026-10
Major 0Minor 1Patch 27

Each point covers 2 days.

All dependencies 247

Full resolved dependency set from the GitHub dependency graph: 0 direct and 247 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIaiohappyeyeballs2.6.1indirect
PyPIaiohttp3.14.3indirect
PyPIaiosignal1.4.0indirect
PyPIalembic1.16.5indirect
PyPIannotated-types0.7.0indirect
PyPIanyio4.10.0indirect
PyPIasync-timeout5.0.1indirect
PyPIattrs25.3.0indirect
PyPIbackports-tarfile1.2.0indirect
PyPIbeautifulsoup44.13.5indirect
PyPIblinker1.9.0indirect
PyPIboto31.43.107indirect
PyPIbotocore1.43.107indirect
PyPIbuild1.3.0indirect
PyPIcachetools5.5.2indirect
PyPIcertifi2025.8.3indirect
PyPIcffi1.17.1indirect
PyPIcfgv3.4.0indirect
PyPIcharset-normalizer3.4.3indirect
PyPIchromadb—indirect
PyPIclick8.2.1indirect
PyPIcloudpickle3.1.2indirect
PyPIcolorama—indirect
PyPIcolorama0.4.6indirect
PyPIconfigargparse—indirect
PyPIcontourpy1.3.2indirect
PyPIcontourpy1.3.3indirect
PyPIcryptography45.0.6indirect
PyPIcvxpy1.7.3indirect
PyPIcycler0.12.1indirect
PyPIcython3.1.4indirect
PyPIdask2024.8.0indirect
PyPIdatabricks-sdk0.65.0indirect
PyPIdatasets5.0.1indirect
PyPIdill0.3.8indirect
PyPIdistlib0.4.0indirect
PyPIdistro1.9.0indirect
PyPIdocker7.2.0indirect
PyPIdocutils0.22indirect
PyPIduckdb1.4.1indirect
PyPIexceptiongroup1.3.0indirect
PyPIfastapi0.116.1indirect
PyPIfastapi0.121.1indirect
PyPIfastuuid0.14.0indirect
PyPIfilelock—indirect
PyPIfilelock3.19.1indirect
PyPIflask3.1.2indirect
PyPIflask-cors6.0.5indirect
PyPIfonttools4.59.2indirect
PyPIfrozenlist1.7.0indirect
PyPIfsspec2025.3.0indirect
PyPIgepa0.1.4indirect
PyPIgitdb4.0.12indirect
PyPIgitpython3.1.45indirect
PyPIgoogle-auth—indirect
PyPIgoogle-auth2.40.3indirect
PyPIgoogleapis-common-protos1.75.5indirect
PyPIgraphene3.4.3indirect
PyPIgraphql-core3.2.6indirect
PyPIgraphql-relay3.2.0indirect
PyPIgreenlet3.2.4indirect
PyPIgunicorn23.0.0indirect
PyPIh110.16.0indirect
PyPIh24.4.1indirect
PyPIh5py3.14.0indirect
PyPIhf-xet1.1.8indirect
PyPIhpack4.2.0indirect
PyPIhttpcore1.0.9indirect
PyPIhttpx0.28.1indirect
PyPIhuey3.2.1indirect
PyPIhuggingface-hub0.34.4indirect
PyPIhyperframe6.1.0indirect
PyPIid1.5.0indirect
PyPIidentify2.6.13indirect
PyPIidna3.10indirect
PyPIimportlib-metadata8.7.0indirect
PyPIiniconfig2.1.0indirect
PyPIitsdangerous2.2.0indirect
PyPIjaraco-classes3.4.0indirect
PyPIjaraco-context6.0.1indirect
PyPIjaraco-functools4.3.0indirect
PyPIjeepney0.9.0indirect
PyPIjinja23.1.6indirect
PyPIjiter0.10.0indirect
PyPIjmespath1.1.0indirect
PyPIjoblib1.5.2indirect
PyPIjsonpatch1.33indirect
PyPIjsonpointer3.1.1indirect
PyPIjsonschema4.25.1indirect
PyPIjsonschema-specifications2025.4.1indirect
PyPIkeyring25.6.0indirect
PyPIkiwisolver1.4.9indirect
PyPIlancedb—indirect
PyPIlangchain1.4.2indirect
PyPIlangchain-core1.6.6indirect
PyPIlangchain-protocol0.0.18indirect
PyPIlanggraph1.2.12indirect
PyPIlanggraph-checkpoint4.1.1indirect
PyPIlanggraph-prebuilt1.1.0indirect
PyPIlanggraph-sdk0.4.2indirect
PyPIlangsmith0.10.3indirect
PyPIlark1.3.1indirect
PyPIlitellm—indirect
PyPIlitellm1.103.2indirect
PyPIlitellm1.93.2indirect
PyPIllm-structured-confidence0.4.5indirect
PyPImako1.3.10indirect
PyPImarkdown-it-py4.0.0indirect
PyPImarkupsafe3.0.2indirect
PyPImatplotlib3.10.6indirect
PyPImatplotlib3.7.5indirect
PyPImdurl0.1.2indirect
PyPImkdocs—indirect
PyPImkdocs-jupyter—indirect
PyPImkdocs-material—indirect
PyPImkdocs-redirects—indirect
PyPImkdocs-rss-plugin—indirect
PyPImkdocstrings—indirect
PyPImkdocstrings-python—indirect
PyPImlflow3.16.1indirect
PyPImlflow-skinny3.16.1indirect
PyPImlflow-tracing3.16.1indirect
PyPImore-itertools10.7.0indirect
PyPImultidict6.6.4indirect
PyPImultiprocess0.70.16indirect
PyPInetworkx—indirect
PyPInetworkx3.2.1indirect
PyPInh30.3.0indirect
PyPInodeenv1.9.1indirect
PyPInumba0.60.0indirect
PyPInumpy—indirect
PyPInumpy2.2.6indirect
PyPInumpy2.3.2indirect
PyPInumpy2.5.1indirect
PyPIopenai2.45.0indirect
PyPIopenpyxl3.1.5indirect
PyPIopentelemetry-api1.45.0indirect
PyPIopentelemetry-exporter-http-transport0.66b0indirect
PyPIopentelemetry-exporter-otlp-common0.66b0indirect
PyPIopentelemetry-exporter-otlp-proto-common1.45.0indirect
PyPIopentelemetry-exporter-otlp-proto-http1.45.0indirect
PyPIopentelemetry-proto1.45.0indirect
PyPIopentelemetry-sdk1.45.0indirect
PyPIopentelemetry-semantic-conventions0.66b0indirect
PyPIoptuna—indirect
PyPIorjson3.11.9indirect
PyPIormsgpack1.12.2indirect
PyPIpackaging26.3indirect
PyPIpandas—indirect
PyPIpandas2.3.3indirect
PyPIpillow—indirect
PyPIpillow11.3.0indirect
PyPIplatformdirs4.3.8indirect
PyPIplaywright—indirect
PyPIpluggy1.6.0indirect
PyPIpolars1.33.1indirect
PyPIpre-commit4.6.2indirect
PyPIprettytable3.18.0indirect
PyPIpropcache0.3.2indirect
PyPIprotobuf7.36.2indirect
PyPIpsutil—indirect
PyPIpsutil7.2.2indirect
PyPIpulp3.3.0indirect
PyPIpyarrow—indirect
PyPIpyarrow25.0.1indirect
PyPIpyasn10.6.1indirect
PyPIpyasn1-modules0.4.2indirect
PyPIpycparser2.22indirect
PyPIpydantic2.13.5indirect
PyPIpydantic-core2.46.5indirect
PyPIpydantic-settings2.15.0indirect
PyPIpygments2.19.2indirect
PyPIpymilvus—indirect
PyPIpyomo6.9.5indirect
PyPIpyparsing3.2.3indirect
PyPIpyproject-hooks1.2.0indirect
PyPIpyright1.1.414indirect
PyPIpytest9.1.1indirect
PyPIpython-dateutil2.9.0.post0indirect
PyPIpython-dotenv1.2.3indirect
PyPIpytz2025.2indirect
PyPIpywin32311indirect
PyPIpywin32-ctypes0.2.3indirect
PyPIpyyaml—indirect
PyPIpyyaml6.0.3indirect
PyPIqdrant-client—indirect
PyPIreadme-renderer44.0indirect
PyPIreferencing0.36.2indirect
PyPIregex2025.7.34indirect
PyPIrequests2.34.2indirect
PyPIrequests-toolbelt1.0.0indirect
PyPIrfc39862.0.0indirect
PyPIrich15.0.0indirect
PyPIrpds-py0.27.0indirect
PyPIrsa4.9.1indirect
PyPIruff0.16.9indirect
PyPIs3transfer0.19.2indirect
PyPIscikit-learn1.6.1indirect
PyPIscikit-learn1.7.1indirect
PyPIscipy—indirect
PyPIscipy1.15.3indirect
PyPIscipy1.16.1indirect
PyPIscrapy2.13.3indirect
PyPIseaborn—indirect
PyPIsecretstorage3.3.3indirect
PyPIsemver3.1.0indirect
PyPIsetuptools80.9.0indirect
PyPIshapely2.0.7indirect
PyPIsix1.17.0indirect
PyPIskops0.14.0indirect
PyPIsmmap5.0.2indirect
PyPIsniffio1.3.1indirect
PyPIsqlalchemy2.0.43indirect
PyPIsqlalchemy2.0.44indirect
PyPIsqlparse0.5.3indirect
PyPIstarlette0.47.3indirect
PyPIstatsmodels0.14.5indirect
PyPIswesmith0.0.9indirect
PyPIsympy1.13.1indirect
PyPItenacity9.1.4indirect
PyPIthreadpoolctl3.6.0indirect
PyPItiktoken0.14.0indirect
PyPItokenizers0.21.4indirect
PyPItomli2.2.1indirect
PyPItqdm4.67.1indirect
PyPItqdm4.70.1indirect
PyPItwine7.0.0indirect
PyPItyping-extensions4.14.1indirect
PyPItyping-inspection0.4.2indirect
PyPItzdata2025.2indirect
PyPIurllib32.5.0indirect
PyPIuuid-utils0.17.0indirect
PyPIuvicorn0.35.0indirect
PyPIvirtualenv20.34.0indirect
PyPIwaitress3.0.2indirect
PyPIwandb—indirect
PyPIwandb0.30.0indirect
PyPIwcwidth0.8.2indirect
PyPIweaviate-client—indirect
PyPIwebsockets15.0.1indirect
PyPIwerkzeug3.1.3indirect
PyPIwheel0.45.1indirect
PyPIxarray2024.7.0indirect
PyPIxxhash3.5.0indirect
PyPIyarl1.20.1indirect
PyPIzipp3.23.0indirect
PyPIzstandard0.25.0indirect
Dependency advisories 28

This repository publishes no package the index resolves, so its own dependency graph was assessed — 218 packages, which also include development and test pins that never ship: 28 carry known advisories, of which 0 are direct. 29 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list.

PackageVersionRelationSeverityAdvisoriesFixed in
anyio4.10.0indirectcritical44.14.2
cryptography45.0.6indirectcritical1350.0.0
gitpython3.1.45indirectcritical603.2.1
pillow11.3.0indirectcritical7613.0.0
aiohttp3.14.3indirecthigh83.14.4
certifi2025.8.3indirecthigh22026.10.19
fsspec2025.3.0indirecthigh22026.6.0
graphql-core3.2.6indirecthigh23.3.0rc1
jaraco-context6.0.1indirecthigh26.1.0
langgraph-sdk0.4.2indirecthigh20.4.4
mako1.3.10indirecthigh61.4.2
mlflow3.16.1indirecthigh23.17.2
pyasn10.6.1indirecthigh100.6.4
scrapy2.13.3indirecthigh82.17.0
sqlparse0.5.3indirecthigh110.6.0
starlette0.47.3indirecthigh121.3.1
urllib32.5.0indirecthigh122.8.0
virtualenv20.34.0indirecthigh2521.14.9
wheel0.45.1indirecthigh20.46.2
duckdb1.4.1indirectmoderate11.4.2
filelock3.19.1indirectmoderate43.20.3
flask3.1.2indirectmoderate23.1.3
fonttools4.59.2indirectmoderate24.60.2
idna3.10indirectmoderate23.15
opentelemetry-api1.45.0indirectmoderate11.45.1
setuptools80.9.0indirectmoderate384.1.0
werkzeug3.1.3indirectmoderate83.1.9
pygments2.19.2indirectlow22.20.0

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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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.

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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.