Public record
Software health reportschema 0.11.0 · metrics 2.10.0 · 2026-07-16 23:43 UTC

tox-dev / python-discovery

Python interpreter discovery

PythonMIT★ 13 stars⑂ 11 forkssince Dec 2023View on GitHub ↗
KindLibraryhow this is determined

tox-dev/python-discovery holds a health index of 88 out of 100, placing it in the Excellent band. It scores highest on Engineering Quality (87/100) and lowest on AI Readiness (44/100). It was last updated today. 2 contributors account for most of its recent work.

88
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.

88
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 74 is calibrated to 88 on the published index scale (record calibration 2026-08-02).

Ownership

tox development teamOrganization
138 followers49 public repossince Jul 2016

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIpython-discovery1.4.4-168 days agodiscoveryinterpreterpython

Metrics by category

Vitality

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

85Excellent · 21% of overall

Development activity

75Good
How it's scored
36/36Push recency — last push 0 days ago
14.5/36Commit cadence — 21/52 weeks with commits
16.7/18Commit volume — 71 commits in the last year
0/10OpenSSF Scorecard: Maintained — no data
Inputs used
commits_last_year71
human_commit_share—
days_since_last_push0
active_weeks_last_year21

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 16 releases published
36/36Release recency — latest release 8 days ago
27/27Release cadence — a release every ~11.1 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count16
latest_release_tag1.4.4
releases_from_tagsno
days_since_latest_release8
mean_days_between_releases11.1

Community & Adoption

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

44Weak · 17% of overall

Popularity & adoption

26At Risk
How it's scored
17.5/60Stars — 13 stars
8.3/25Forks — 11 forks
0/15Watchers — 2 watchers
Inputs used
forks11
stars13
watchers2
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

65Good
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (MIT)
0/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges—
has_contributingno
has_issue_templateno
has_code_of_conductyes
readme_badge_services—
has_pull_request_templateno

Sustainability & Governance

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

82Excellent · 23% of overall

Maintainer resilience (bus factor)

55Moderate
How it's scored
25.2/54Bus factor — 2 contributor(s) cover half of all commits
13.2/22.5Commit distribution — top contributor authored 41% of commits
10.8/13.5Contributor breadth — 8 contributors
0/10OpenSSF Scorecard: Contributors — no data
Inputs used
bus_factor2
contributors_sampled8
top_contributor_share0.412

Issue & PR responsiveness

97Exceptional
How it's scored
42/42Issue resolution — 100% of issues closed
28/30PR acceptance — 84/90 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — no data
Inputs used
merged_prs84
open_issues0
closed_issues12
prs_merged_7d—
prs_decided_7d—
prs_merged_30d—
prs_decided_30d—
issue_closed_ratio1
closed_unmerged_prs6
first_time_authors_30d—
first_time_prs_merged_30d—
first_time_prs_decided_30d—
Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.

Ownership & stewardship

87Excellent
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain — verified-domain status not read for this organization
15.4/25Owner reach — 138 followers of tox-dev
24.4/25Track record — 49 public repos, account ~10 yr old
Inputs used
followers138
owner_typeOrganization
is_verified—
owner_logintox-dev
public_repos49
account_age_days3,661
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 8 days ago
20/20Version history — 16 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagespython-discovery
ecosystemspypi
any_deprecatedno
min_days_since_publish8

Engineering Quality

Are baseline engineering and documentation practices in place?

87Excellent · 19% of overall

Engineering practices

92Excellent
How it's scored
24/24CI workflows — 3 workflow(s)
24/24Tests present
16/16Linter config
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://python-discovery.readthedocs.io/en/latest/#
10/10Repository description
0/10Topics
0/10Wiki
Inputs used
topics—
has_wikino
homepagehttps://python-discovery.readthedocs.io/en/latest/#
docs_sitehttps://python-discovery.readthedocs.io/en/latest/#
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

73Good · 16% of overall

Security posture

73Good
How it's scored
30/30Security 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
lockfiles—
manifestspyproject.toml
has_codeql_workflowno
has_security_policyyes
has_dependabot_configyes
Excluded from scoring (no data or not applicable): Dependency lockfiles. 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.

44Weak · 4% of overall

Agent context & guidance

1Critical
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
0/40Legible commit history — no data
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share—
agent_instruction_files—
agent_instruction_max_bytes—
Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.

Verify loop (build / test / typecheck)

61Moderate
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config
11/11Static type checking — src/python_discovery/py.typed
0/10Reproducible environment
0/10Demonstrated agent practice — no data
5/8Automated maintenance — dependency automation configured, none observed in the sampled commits
0/10OpenSSF Scorecard: Pinned-Dependencies — no data
Inputs used
has_nixno
has_testsyes
lockfiles—
has_dockerfileno
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configyes
typecheck_configssrc/python_discovery/py.typed
agent_commit_share—
toolchain_manifests—
dependency_bot_commit_share0
Excluded from scoring (no data or not applicable): Demonstrated agent practice. Remaining weights renormalized.

Code legibility for models

82Excellent
How it's scored
27/45Type-checkable code — Python with type-check config (src/python_discovery/py.typed)
55/55Manageable file sizes — 0/29 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes36,974
source_files_sampled29
oversized_source_files0

Key facts

13GitHub stars
8contributors
71commits, last 12 months
0days since last push
16releases
2bus factor
0open issues
PyPIpackage ecosystems

Data collection warnings

  • OpenSSF Scorecard did not return a usable result (Skipping github.com/tox-dev/python-discovery: run: repo unreachable: GET https://api.github.com/repos/tox-dev/python-discovery: 503 []); skipping Scorecard checks

More detail

Direct dependencies 2
RegistryPackageVersion constraintManifest
PyPIfilelock>=3.15.4pyproject.toml
PyPIplatformdirs<5,>=4.3.6pyproject.toml
All dependencies 18

Full resolved dependency set from the GitHub dependency graph: 2 direct and 16 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIfilelock—direct
PyPIplatformdirs—direct
PyPIcovdefaults—indirect
PyPIcoverage—indirect
PyPIfuro—indirect
PyPIgitpython—indirect
PyPIhatch-vcs—indirect
PyPIhatchling—indirect
PyPIpackaging—indirect
PyPIpre-commit—indirect
PyPIpytest—indirect
PyPIpytest-mock—indirect
PyPIsetuptools—indirect
PyPIsphinx—indirect
PyPIsphinx-autodoc-typehints—indirect
PyPIsphinxcontrib-mermaid—indirect
PyPIsphinxcontrib-towncrier—indirect
PyPItowncrier—indirect
Raw JSON report machine-readable

Feedback

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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 v0.11.0 — full methodology · metrics wiki.

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