Public record
Software health reportschema 0.12.0 · metrics 2.10.0 · 2026-07-18 13:15 UTC

Lightning-AI / utilities

Common Python utilities and GitHub Actions in Lightning Ecosystem

PythonApache-2.0★ 62 stars⑂ 23 forkssince Apr 2022View on GitHub ↗
KindLibraryhow this is determined
#ci-cd#developer-tools#github-actions

Lightning-AI/utilities holds a health index of 89 out of 100, placing it in the Excellent band. It scores highest on Sustainability & Governance (87/100) and lowest on Community & Adoption (50/100). It was last updated 4 days ago. 2 contributors account for most of its recent work.

89
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.

89
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 75 is calibrated to 89 on the published index scale (record calibration 2026-08-02).

Ownership

⚡️ Lightning AI Organization
6,836 followers29 public repossince Dec 2019

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIlightning-utilities0.15.3-37145 days agoutilitiesdevopsci-cd

Metrics by category

Vitality

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

78Good · 21% of overall

Development activity

76Good
How it's scored
36/36Push recency — last push 4 days ago
14.5/36Commit cadence — 21/52 weeks with commits
17/18Commit volume — 77 commits in the last year
8/10OpenSSF Scorecard: Maintained — 10 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 8
Inputs used
commits_last_year77
human_commit_share—
days_since_last_push4
active_weeks_last_year21

Release discipline

81Excellent
How it's scored
27/27Ships releases — 35 releases published
27/36Release recency — latest release 157 days ago
27/27Release cadence — a release every ~38.2 days
0/10OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases.
Inputs used
releases_count35
latest_release_tagv0.15.3
releases_from_tagsno
days_since_latest_release157
mean_days_between_releases38.2

Community & Adoption

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

50Moderate · 17% of overall

Popularity & adoption

44Weak
How it's scored
29/60Stars — 62 stars
11.2/25Forks — 23 forks
4.3/15Watchers — 7 watchers
Inputs used
forks23
stars62
watchers7
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

57Moderate
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (Apache-2.0)
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges—
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_services—
has_pull_request_templateyes

Sustainability & Governance

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

87Excellent · 23% of overall

Maintainer resilience (bus factor)

62Moderate
How it's scored
25.2/54Bus factor — 2 contributor(s) cover half of all commits
13.2/22.5Commit distribution — top contributor authored 42% of commits
13.5/13.5Contributor breadth — 25 contributors
10/10OpenSSF Scorecard: Contributors — project has 11 contributing companies or organizations
Inputs used
bus_factor2
contributors_sampled25
top_contributor_share0.415

Issue & PR responsiveness

96Exceptional
How it's scored
41/42Issue resolution — 98% of issues closed
27.7/30PR acceptance — 423/458 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
15/15OpenSSF Scorecard: Code-Review — all changesets reviewed
Inputs used
merged_prs423
open_issues1
closed_issues40
prs_merged_7d—
prs_decided_7d—
prs_merged_30d—
prs_decided_30d—
issue_closed_ratio0.976
closed_unmerged_prs35
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

97Exceptional
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain — verified-domain status not read for this organization
25/25Owner reach — 6,836 followers of Lightning-AI
22.8/25Track record — 29 public repos, account ~6 yr old
Inputs used
followers6,836
owner_typeOrganization
is_verified—
owner_loginLightning-AI
public_repos29
account_age_days2,421
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 145 days ago
20/20Version history — 37 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packageslightning-utilities
ecosystemspypi
any_deprecatedno
min_days_since_publish145

Engineering Quality

Are baseline engineering and documentation practices in place?

86Excellent · 19% of overall

Engineering practices

94Exceptional
How it's scored
24/24CI workflows — 15 workflow(s)
24/24Tests present
16/16Linter config
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

75Good
How it's scored
30/30README
25/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
10/10Topics — 3 topics
0/10Wiki
Inputs used
topicsci-cd, developer-tools, github-actions
has_wikino
homepage—
docs_site—
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

65Good · 16% of overall

Security posture

65Good
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — no data
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
7.5/7.5Code-Review — all changesets reviewed
2.5/2.5Contributors — project has 11 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
6/7.5Maintained — 10 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 8
5/5Packaging — packaging workflow detected
5/5Pinned-Dependencies — all dependencies are pinned
0/5SAST — SAST tool is not run on all commits -- score normalized to 0
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — Project has not signed or included provenance with any releases.
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate6.5
Excluded from scoring (no data or not applicable): Branch-Protection. 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.

81Excellent · 4% of overall

Agent context & guidance

75Good
How it's scored
45/45Agent instructions — AGENTS.md
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_filesAGENTS.md
agent_instruction_max_bytes10,014
Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.

Verify loop (build / test / typecheck)

86Excellent
How it's scored
18/18One-command bootstrap — Makefile, docs/Makefile
22/22Automated tests
11/11Lint / format config
11/11Static type checking — src/lightning_utilities/py.typed
0/10Reproducible environment
0/10Demonstrated agent practice — no data
5/8Automated maintenance — dependency automation configured, none observed in the sampled commits
10/10OpenSSF Scorecard: Pinned-Dependencies — all dependencies are pinned
Inputs used
has_nixno
has_testsyes
lockfiles—
has_dockerfileno
typed_languageno
bootstrap_filesMakefile, docs/Makefile
has_devcontainerno
has_linter_configyes
typecheck_configssrc/lightning_utilities/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/lightning_utilities/py.typed)
55/55Manageable file sizes — 0/44 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes13,637
source_files_sampled44
oversized_source_files0

Key facts

62GitHub stars
25contributors
77commits, last 12 months
4days since last push
35releases
2bus factor
1open issues
PyPIpackage ecosystems

More detail

OpenSSF Scorecard 6.5 / 10
6.5aggregate

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 · 2026-07-18 13:15 UTC

10Binary-Artifactsno binaries found in the repo
n/aBranch-Protectioninternal error: error during branchesHandler.setup: internal error: some github tokens can't read classic branch protection rules: https://github.com/ossf/scorecard-action/blob/main/docs/authentication/fine-grained-auth-token.md
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
10Code-Reviewall changesets reviewed
10Contributorsproject has 11 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
8Maintained10 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 8
10Packagingpackaging workflow detected
10Pinned-Dependenciesall dependencies are pinned
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
0Signed-ReleasesProject has not signed or included provenance with any releases.
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
All dependencies 38

Full resolved dependency set from the GitHub dependency graph: 0 direct and 38 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIbuild—indirect
PyPIbuild1.5.*indirect
PyPIcheck-jsonschema—indirect
PyPIcheck-jsonschema0.37.*indirect
PyPIcoverage—indirect
PyPIcoverage7.14.*indirect
PyPIdocutils—indirect
PyPIimportlib-metadata—indirect
PyPIimportlib-metadata8.7.*indirect
PyPIipython—indirect
PyPIjsonargparse—indirect
PyPImypy—indirect
PyPImyst-parser—indirect
PyPInbsphinx—indirect
PyPIpackaging—indirect
PyPIpackaging26.2indirect
PyPIpandoc—indirect
PyPIpt-lightning-sphinx-theme—indirect
PyPIpygments—indirect
PyPIpytest—indirect
PyPIpytest9.0.*indirect
PyPIpytest-cov7.1.0indirect
PyPIpytest-timeout2.4.0indirect
PyPIrequests—indirect
PyPIsetuptools—indirect
PyPIsetuptools82.0.*indirect
PyPIsphinx—indirect
PyPIsphinx-autodoc-typehints—indirect
PyPIsphinx-copybutton—indirect
PyPIsphinx-paramlinks—indirect
PyPIsphinx-togglebutton—indirect
PyPItomlkit—indirect
PyPItwine—indirect
PyPItwine6.2.*indirect
PyPItypes-setuptools—indirect
PyPItyping-extensions—indirect
PyPIwheel—indirect
PyPIwheel0.46.*indirect
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.

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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 v0.12.0 — full methodology · metrics wiki.

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