Public record
Software health reportschema 0.12.0 · metrics 2.10.0 · 2026-07-18 00:32 UTC

griffithlab / VAtools

A set of tools to annotate VCF files with expression and readcount data

PythonMIT★ 31 stars⑂ 13 forkssince Apr 2018View on GitHub ↗
KindLibraryhow this is determined

griffithlab/VAtools holds a health index of 78 out of 100, placing it in the Good band. It scores highest on Vitality (80/100) and lowest on AI Readiness (33/100). It was last updated 5 days ago. A single contributor accounts for most of its recent work.

78
overall / 100
Good

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.

78
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 67 is calibrated to 78 on the published index scale (record calibration 2026-08-02).

Ownership

The Griffith LabOrganization
178 followers86 public repossince Jul 2014

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIvatools6.0.1-127 days agocancersequencingvariantvariantsgeneexpressionreadcountsvafallelefrequencyfpkmtpmtranscriptvcf

Metrics by category

Vitality

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

80Excellent · 21% of overall

Development activity

66Good
How it's scored
36/36Push recency — last push 5 days ago
3.5/36Commit cadence — 5/52 weeks with commits
16.6/18Commit volume — 70 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 8 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year70
human_commit_share—
days_since_last_push5
active_weeks_last_year5

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 12 releases published
36/36Release recency — latest release 7 days ago
27/27Release cadence — a release every ~1.1 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count12
latest_release_tagv6.0.1
releases_from_tagsno
days_since_latest_release7
mean_days_between_releases1.1
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?

53Moderate · 17% of overall

Popularity & adoption

39Weak
How it's scored
24/60Stars — 31 stars
9/25Forks — 13 forks
6.2/15Watchers — 14 watchers
Inputs used
forks13
stars31
watchers14
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?

75Good · 23% of overall

Maintainer resilience (bus factor)

31At Risk
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
6.3/22.5Commit distribution — top contributor authored 72% of commits
5.4/13.5Contributor breadth — 4 contributors
10/10OpenSSF Scorecard: Contributors — project has 5 contributing companies or organizations
Inputs used
bus_factor1
contributors_sampled4
top_contributor_share0.719

Issue & PR responsiveness

92Excellent
How it's scored
41.1/42Issue resolution — 98% of issues closed
30/30PR acceptance — 51/51 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
9/15OpenSSF Scorecard: Code-Review — Found 5/8 approved changesets -- score normalized to 6
Inputs used
merged_prs51
open_issues1
closed_issues44
prs_merged_7d—
prs_decided_7d—
prs_merged_30d—
prs_decided_30d—
issue_closed_ratio0.978
closed_unmerged_prs0
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

89Excellent
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain — verified-domain status not read for this organization
16.2/25Owner reach — 178 followers of griffithlab
25/25Track record — 86 public repos, account ~11 yr old
Inputs used
followers178
owner_typeOrganization
is_verified—
owner_logingriffithlab
public_repos86
account_age_days4,369
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 7 days ago
20/20Version history — 12 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesvatools
ecosystemspypi
any_deprecatedno
min_days_since_publish7

Engineering Quality

Are baseline engineering and documentation practices in place?

77Good · 19% of overall

Engineering practices

68Good
How it's scored
24/24CI workflows — 1 workflow(s)
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 5 out of 5 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configno
has_precommit_configno

Documentation

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — http://www.vatools.org
10/10Repository description
0/10Topics
10/10Wiki
Inputs used
topics—
has_wikiyes
homepagehttp://www.vatools.org
docs_sitehttp://www.vatools.org
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

48Weak · 16% of overall

Security posture

48Weak
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — branch protection not enabled on development/release branches
2.5/2.5CI-Tests — 5 out of 5 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
4.5/7.5Code-Review — Found 5/8 approved changesets -- score normalized to 6
2.5/2.5Contributors — project has 5 contributing companies or organizations
10/10Dangerous-Workflow — no dangerous workflow patterns detected
0/7.5Dependency-Update-Tool — no update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
7.5/7.5Maintained — 30 commit(s) and 8 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
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 — 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_aggregate4.8
Excluded from scoring (no data or not applicable): Packaging, Signed-Releases. 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.

33At Risk · 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)

49Weak
How it's scored
18/18One-command bootstrap — docs/Makefile
22/22Automated tests
0/11Lint / format config
0/11Static type checking
0/10Reproducible environment
0/10Demonstrated agent practice — no data
0/8Automated maintenance — no data
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfiles—
has_dockerfileno
typed_languageno
bootstrap_filesdocs/Makefile
has_devcontainerno
has_linter_configno
typecheck_configs—
agent_commit_share—
toolchain_manifests—
dependency_bot_commit_share—
Excluded from scoring (no data or not applicable): Demonstrated agent practice, Automated maintenance. Remaining weights renormalized.

Code legibility for models

55Moderate
How it's scored
0/45Type-checkable code — Python without a type-check config
55/55Manageable file sizes — 0/20 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes25,748
source_files_sampled20
oversized_source_files0

Key facts

31GitHub stars
4contributors
70commits, last 12 months
5days since last push
12releases
1bus factor
1open issues
PyPIpackage ecosystems

More detail

OpenSSF Scorecard 4.8 / 10
4.8aggregate

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 00:31 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
10CI-Tests5 out of 5 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
6Code-ReviewFound 5/8 approved changesets -- score normalized to 6
10Contributorsproject has 5 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 8 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
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
All dependencies 10

Full resolved dependency set from the GitHub dependency graph: 0 direct and 10 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIdistutils-strtobool—indirect
PyPIgtfparse2.7.1indirect
PyPIpandas—indirect
PyPIpysam—indirect
PyPIsphinx5.0.0indirect
PyPIsphinxcontrib-programoutput0.17indirect
PyPIsphinxjp-themes-basicstrap0.5.0indirect
PyPIstandard-imghdr—indirect
PyPItestfixtures—indirect
PyPIvcfpy0.14.2indirect
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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Related records

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95Clinical-Genomics/scoutVCF visualization interfaceExceptional71sigven/pcgrPersonal Cancer Genome Reporter (PCGR)Good91joshuaswarren/remnicOpen-source memory and context for user-aware agents: scoped memory, provenance, retrieval quality, correction, boundaries, evals, and MCP/HTTP access.Excellent86hail-is/hailCloud-native genomic dataframes and batch computingExcellent86vaaraio/vaaraAccountable Autonomy: open-source evidence layer that gates every AI agent tool call against your policy and writes a hash-chained record an auditor verifies offline, without trusting you. Root-agnostic; binds to TPM 2.0 / SEV-SNP when present. Your environment, no SaaS, no telemetry. AGPL-3.0.Excellent81helicalAI/helicalA framework for state-of-the-art pre-trained bio foundation models on genomics and transcriptomics modalities.Excellent

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.