Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-20 16:52 UTC

IGVF-DACC / snovault-search

PythonMIT★ 0 stars⑂ 1 forksince Oct 2022View on GitHub ↗

IGVF-DACC/snovault-search holds a health index of 29 out of 100, placing it in the At Risk band. It scores highest on Sustainability & Governance (47/100) and lowest on Community & Adoption (24/100). It was last updated 281 days ago. A single contributor accounts for most of its recent work.

29
overall / 100
At Risk

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.

29
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 35 is calibrated to 29 on the published index scale (record calibration 2026-08-02).

Ownership

IGVF-DACCOrganization
13 followers58 public repossince Nov 2021

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIsnovault-searchpoints to another repo — not scored6.1.039710605 days ago

Metrics by category

Vitality

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

28At Risk · 21% of overall
How it's scored
3.6/36Push recencylast push 281 days ago
0.7/36Commit cadence1/52 weeks with commits
2.7/18Commit volume1 commits in the last year
0/10OpenSSF Scorecard: Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
Inputs used
commits_last_year1
human_commit_share1
days_since_last_push281
active_weeks_last_year1
How it's scored
27/27Ships releases9 releases published
7.2/36Release recencylatest release 605 days ago
19.8/27Release cadencea release every ~99 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count9
latest_release_tagv6.1.0
releases_from_tagsno
days_since_latest_release605
mean_days_between_releases99
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?

24At Risk · 17% of overall
How it's scored
0/60Stars0 stars
0/25Forks1 forks
0/15Watchers0 watchers
Inputs used
forks1
stars0
watchers0
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (MIT)
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges2
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_servicescircleci.com, coveralls.io
has_pull_request_templateno

Sustainability & Governance

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

47Weak · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
2.2/22.5Commit distributiontop contributor authored 90% of commits
2.7/13.5Contributor breadth2 contributors
3/10OpenSSF Scorecard: Contributorsproject has 1 contributing companies or organizations -- score normalized to 3
Inputs used
bus_factor1
contributors_sampled2
top_contributor_share0.9
How it's scored
0/42Issue resolutionno issues or no data
26.2/30PR acceptance21/24 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
4.5/15OpenSSF Scorecard: Code-ReviewFound 10/30 approved changesets -- score normalized to 3
Inputs used
merged_prs21
open_issues0
closed_issues0
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio
closed_unmerged_prs3
first_time_authors_30d0
first_time_prs_merged_30d0
first_time_prs_decided_30d0
Excluded from scoring (no data or not applicable): Issue resolution, Newcomer PR acceptance. Remaining weights renormalized.
How it's scored
30/30Ownership backingorganization-owned
0/20Verified domain
8.2/25Owner reach13 followers of IGVF-DACC
22.6/25Track record58 public repos, account ~4 yr old
Inputs used
followers13
owner_typeOrganization
is_verifiedno
owner_loginIGVF-DACC
public_repos58
account_age_days1,767

Engineering Quality

Are baseline engineering and documentation practices in place?

30At Risk · 19% of overall
How it's scored
0/24CI workflows
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests1 out of 21 merged PRs checked by a CI test -- score normalized to 0
Inputs used
has_cino
has_testsyes
has_editorconfigno
has_linter_configno
has_precommit_configno
How it's scored
30/30README
0/25Documentation directory
0/15Documentation / homepage site
0/10Repository description
0/10Topics
10/10Wiki
Inputs used
topics
has_wikiyes
homepage
docs_site
has_readmeyes
has_docs_dirno
has_descriptionno

Security

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

42Weak · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
0/7.5Branch-Protectionno data
0/2.5CI-Tests1 out of 21 merged PRs checked by a CI test -- score normalized to 0
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
2.2/7.5Code-ReviewFound 10/30 approved changesets -- score normalized to 3
0.8/2.5Contributorsproject has 1 contributing companies or organizations -- score normalized to 3
0/10Dangerous-Workflowno data
0/7.5Dependency-Update-Toolno update tool detected
0/5Fuzzingproject is not fuzzed
2.5/2.5Licenselicense file detected
0/7.5Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
0/5Packagingno data
0/5Pinned-Dependenciesno data
0/5SASTSAST tool is not run on all commits -- score normalized to 0
0/5Security-Policysecurity policy file not detected
0/7.5Signed-Releasesno data
0/7.5Token-Permissionsno data
7.5/7.5Vulnerabilities0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated12
scorecard_versionv5.5.0
checks_inconclusive6
scorecard_aggregate3.3
Excluded from scoring (no data or not applicable): Branch-Protection, Dangerous-Workflow, Packaging, Pinned-Dependencies, Signed-Releases, Token-Permissions. Remaining weights renormalized.
How it's scored
35/35Direct dependencies free of known advisoriesno direct dependency carries a known advisory
10/25Indirect dependencies free of known advisories1 affected: urllib3 1.26.20 (high 7.5)
33.7/40No advisories left outstanding1 advisory-carrying package(s) unaddressed past 90 days; oldest published 458 days ago
Inputs used
sourceosv
advisories10
affected_packages1
assessed_packages11
unassessed_packages0
affected_by_severityhigh 1
direct_affected_packages0
Matched the pypi:snovault-search@6.1.0 runtime dependency closure — what installing the published package pulls in — 11 packages. 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.

45Weak · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
40/40Legible commit history38 of 40 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.95
agent_instruction_files
agent_instruction_max_bytes
How it's scored
0/18One-command bootstrap
22/22Automated tests
0/11Lint / format config
11/11Static type checkingmypy.ini
0/10Reproducible environment
0/10Demonstrated agent practiceno agent-authored commits among the last 40
0/8Automated maintenanceno automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependenciesno data
Inputs used
has_nixno
has_testsyes
lockfiles
has_dockerfileno
typed_languageno
bootstrap_files
has_devcontainerno
has_linter_configno
typecheck_configsmypy.ini
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: Pinned-Dependencies. Remaining weights renormalized.
How it's scored
27/45Type-checkable codePython with type-check config (mypy.ini)
51.3/55Manageable file sizes2/30 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes257,714
source_files_sampled30
oversized_source_files2

Key facts

0GitHub stars
2contributors
1commits, last 12 months
281days since last push
9releases
1bus factor
0open issues
PyPIpackage ecosystems

Data collection warnings

  • pypi package 'snovault-search' points at a different repository (https://github.com/ENCODE-DCC/snovault-search); excluded from ecosystem scoring

More detail

OpenSSF Scorecard 3.3 / 10
3.3aggregate

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 · 2026-09-20 16:52 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
0CI-Tests1 out of 21 merged PRs checked by a CI test -- score normalized to 0
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
3Code-ReviewFound 10/30 approved changesets -- score normalized to 3
3Contributorsproject has 1 contributing companies or organizations -- score normalized to 3
n/aDangerous-Workflowno workflows found
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
0Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
n/aPackagingpackaging workflow not detected
n/aPinned-Dependenciesno dependencies found
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
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 4
RegistryPackageVersion constraintManifest
PyPIantlr4-python3-runtime==4.9.3setup.cfg
PyPIopensearch-py==2.3.0setup.cfg
PyPIopensearch-dsl==2.1.0setup.cfg
PyPIlucenequery==0.1setup.cfg
All dependencies 0

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

RegistryPackageVersionRelation
Dependency advisories 1

Installing pypi:snovault-search@6.1.0 pulls in 11 packages, direct and transitive: 1 carry known advisories, of which 0 are direct dependencies.

PackageVersionRelationSeverityAdvisoriesFixed in
urllib31.26.20indirecthigh102.7.0

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

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.

The message is kept through sign-in.

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 statisticsPyPI.