Public record
Software health reportschema 0.11.0 · metrics 2.10.0 · 2026-07-17 04:24 UTC

VirtusLab / git-machete

Probably the sharpest git repository organizer & rebase/merge workflow automation tool you've ever seen

PythonMIT★ 1,125 stars⑂ 65 forkssince Feb 2018View on GitHub ↗
KindLibraryhow this is determined
#git#cli#rebase#merge

VirtusLab/git-machete holds a health index of 87 out of 100, placing it in the Excellent band. It scores highest on Vitality (99/100) and lowest on Security (53/100). It was last updated 2 days ago. A single contributor accounts for most of its recent work.

87
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.

87
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 73 is calibrated to 87 on the published index scale (record calibration 2026-08-02).

Ownership

VirtusLabOrganization
144 followers194 public repossince Aug 2013

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIgit-machete3.44.1-1469 days agogit

Metrics by category

Vitality

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

99Exceptional · 21% of overall

Development activity

99Exceptional
How it's scored
36/36Push recency — last push 2 days ago
35.3/36Commit cadence — 51/52 weeks with commits
18/18Commit volume — 288 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 10 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year288
human_commit_share—
days_since_last_push2
active_weeks_last_year51

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 100 releases published
36/36Release recency — latest release 9 days ago
27/27Release cadence — a release every ~17.6 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count100
latest_release_tagv3.44.1
releases_from_tagsno
days_since_latest_release9
mean_days_between_releases17.6
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?

68Good · 17% of overall

Popularity & adoption

67Good
How it's scored
49.5/60Stars — 1,125 stars
15.1/25Forks — 65 forks
2.7/15Watchers — 4 watchers
Inputs used
forks65
stars1,125
watchers4
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_badges—
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_services—
has_pull_request_templateno

Sustainability & Governance

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

74Good · 23% of overall

Maintainer resilience (bus factor)

41Weak
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
8.7/22.5Commit distribution — top contributor authored 61% of commits
13.5/13.5Contributor breadth — 40 contributors
10/10OpenSSF Scorecard: Contributors — project has 6 contributing companies or organizations
Inputs used
bus_factor1
contributors_sampled40
top_contributor_share0.614

Issue & PR responsiveness

78Good
How it's scored
38.5/42Issue resolution — 92% of issues closed
27.7/30PR acceptance — 1,095/1,184 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
1.5/15OpenSSF Scorecard: Code-Review — Found 3/20 approved changesets -- score normalized to 1
Inputs used
merged_prs1,095
open_issues46
closed_issues503
prs_merged_7d—
prs_decided_7d—
prs_merged_30d—
prs_decided_30d—
issue_closed_ratio0.916
closed_unmerged_prs89
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

88Excellent
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain — verified-domain status not read for this organization
15.5/25Owner reach — 144 followers of VirtusLab
25/25Track record — 194 public repos, account ~12 yr old
Inputs used
followers144
owner_typeOrganization
is_verified—
owner_loginVirtusLab
public_repos194
account_age_days4,706
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 9 days ago
20/20Version history — 146 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesgit-machete
ecosystemspypi
any_deprecatedno
min_days_since_publish9

Engineering Quality

Are baseline engineering and documentation practices in place?

66Good · 19% of overall

Engineering practices

60Moderate
How it's scored
0/24CI workflows
24/24Tests present
16/16Linter config — tox.ini
0/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 26 out of 26 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_cino
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno

Documentation

75Good
How it's scored
30/30README
25/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
10/10Topics — 4 topics
0/10Wiki
Inputs used
topicsgit, cli, rebase, merge
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?

53Moderate · 16% of overall

Security posture

53Moderate
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 — 26 out of 26 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
0.8/7.5Code-Review — Found 3/20 approved changesets -- score normalized to 1
2.5/2.5Contributors — project has 6 contributing companies or organizations
0/10Dangerous-Workflow — no data
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 10 issue activity found in the last 90 days -- score normalized to 10
0/5Packaging — no data
0.5/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 1
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 — no data
0/7.5Token-Permissions — no data
4.5/7.5Vulnerabilities — 4 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated13
scorecard_versionv5.5.0
checks_inconclusive5
scorecard_aggregate5.3
Excluded from scoring (no data or not applicable): Branch-Protection, Dangerous-Workflow, Packaging, Signed-Releases, Token-Permissions. 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.

72Good · 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_bytes6,862
Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.

Verify loop (build / test / typecheck)

67Good
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config — tox.ini
11/11Static type checking — mypy.ini
10/10Reproducible environment — Dockerfile
0/10Demonstrated agent practice — no data
5/8Automated maintenance — dependency automation configured, none observed in the sampled commits
1/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 1
Inputs used
has_nixno
has_testsyes
lockfiles—
has_dockerfileyes
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configyes
typecheck_configsmypy.ini
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

80Excellent
How it's scored
27/45Type-checkable code — Python with type-check config (mypy.ini)
53.1/55Manageable file sizes — 4/116 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes114,718
source_files_sampled116
oversized_source_files4

Key facts

1,125GitHub stars
40contributors
288commits, last 12 months
2days since last push
100releases
1bus factor
46open issues
PyPIpackage ecosystems

More detail

OpenSSF Scorecard 5.3 / 10
5.3aggregate

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 · 2026-07-17 04:24 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-Tests26 out of 26 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
1Code-ReviewFound 3/20 approved changesets -- score normalized to 1
10Contributorsproject has 6 contributing companies or organizations
n/aDangerous-Workflowno workflows found
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 10 issue activity found in the last 90 days -- score normalized to 10
n/aPackagingpackaging workflow not detected
1Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 1
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
n/aToken-PermissionsNo tokens found
6Vulnerabilities4 existing vulnerabilities detected
All dependencies 46

Full resolved dependency set from the GitHub dependency graph: 0 direct and 46 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIautoflake2.3.3indirect
PyPIautopep82.3.2indirect
PyPIbuild1.5.0indirect
PyPIcoverage6.2indirect
PyPIcoverage7.10.7indirect
PyPIcoverage7.15.0indirect
PyPIcoverage7.2.7indirect
PyPIcoverage7.6.1indirect
PyPIflake87.3.0indirect
PyPIflake8-plugin-utils1.3.3indirect
PyPIflake8-unused-arguments0.0.14indirect
PyPIflake8-use-fstring1.4indirect
PyPIisort8.0.1indirect
PyPImypy0.971indirect
PyPImypy1.14.1indirect
PyPImypy1.19.1indirect
PyPImypy1.4.1indirect
PyPImypy2.1.0indirect
PyPIpydata-sphinx-theme0.16.1indirect
PyPIpylint4.0.6indirect
PyPIpytest7.0.1indirect
PyPIpytest7.4.4indirect
PyPIpytest8.3.5indirect
PyPIpytest8.4.2indirect
PyPIpytest9.1.1indirect
PyPIpytest-clarity1.0.1indirect
PyPIpytest-cov4.0.0indirect
PyPIpytest-cov4.1.0indirect
PyPIpytest-cov5.0.0indirect
PyPIpytest-cov7.1.0indirect
PyPIpytest-mock3.11.1indirect
PyPIpytest-mock3.14.0indirect
PyPIpytest-mock3.15.1indirect
PyPIpytest-mock3.6.1indirect
PyPIpytest-xdist2.4.0indirect
PyPIpytest-xdist3.5.0indirect
PyPIpytest-xdist3.6.1indirect
PyPIpytest-xdist3.8.0indirect
PyPIsetuptools83.0.0indirect
PyPIsphinx9.1.0indirect
PyPIsphinx-book-theme1.2.0indirect
PyPItox4.56.1indirect
PyPItwine6.2.0indirect
PyPItypos1.48.0indirect
PyPIvulture2.16indirect
PyPIwheel0.47.0indirect
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.