Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-12 10:46 UTC

PriorLabs / tabpfn_common_utils

Shared Python utilities used across the TabPFN ecosystem — data helpers, regression result handling, cost estimation, and optional telemetry.

PythonApache-2.0★ 0 stars⑂ 5 forkssince Aug 2023View on GitHub ↗
KindLibraryhow this is determined

PriorLabs/tabpfn_common_utils holds a health index of 73 out of 100, placing it in the Good band. It scores highest on Engineering Quality (76/100) and lowest on Community & Adoption (43/100). It was last updated 52 days ago. A single contributor accounts for most of its recent work.

73
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.

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

Ownership

Prior LabsOrganization
411 followers13 public repossince Sep 2023

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPItabpfn-common-utils0.2.23101,2803181 days agomachine-learningtabpfnutilities

Metrics by category

Vitality

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

65Good · 21% of overall

Development activity

56Moderate
How it's scored
18/36Push recency — last push 52 days ago
17.3/36Commit cadence — 25/52 weeks with commits
18/18Commit volume — 163 commits in the last year
3/10OpenSSF Scorecard: Maintained — 4 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 3
Inputs used
commits_last_year163
human_commit_share0.98
days_since_last_push52
active_weeks_last_year25

Release discipline

78Good
How it's scored
27/27Ships releases — 6 releases published
16.2/36Release recency — latest release 211 days ago
27/27Release cadence — a release every ~16.8 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count6
latest_release_tagv0.2.16
releases_from_tagsno
days_since_latest_release211
mean_days_between_releases16.8
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?

43Weak · 17% of overall

Popularity & adoption

5Critical
How it's scored
0/60Stars — 0 stars
5/25Forks — 5 forks
0/15Watchers — 2 watchers
Inputs used
forks5
stars0
watchers2
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_badges0
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_services—
has_pull_request_templateyes

Ecosystem adoption (downloads)

83Excellent
How it's scored
66.7/80Monthly downloads — 101,280 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagestabpfn-common-utils
dependents—
ecosystemspypi
total_downloads—
monthly_downloads101,280
unverified_packages_excluded—
Excluded from scoring (no data or not applicable): Registry dependents. Remaining weights renormalized.

Sustainability & Governance

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

69Good · 23% of overall

Maintainer resilience (bus factor)

36Weak
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
7/22.5Commit distribution — top contributor authored 69% of commits
13.5/13.5Contributor breadth — 14 contributors
6/10OpenSSF Scorecard: Contributors — project has 2 contributing companies or organizations -- score normalized to 6
Inputs used
bus_factor1
contributors_sampled14
top_contributor_share0.688

Issue & PR responsiveness

88Excellent
How it's scored
42/42Issue resolution — 100% of issues closed
27.3/30PR acceptance — 70/77 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
7.5/15OpenSSF Scorecard: Code-Review — Found 5/10 approved changesets -- score normalized to 5
Inputs used
merged_prs70
open_issues0
closed_issues1
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio1
closed_unmerged_prs7
first_time_authors_30d0
first_time_prs_merged_30d0
first_time_prs_decided_30d0
Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.

Ownership & stewardship

63Moderate
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
18.8/25Owner reach — 411 followers of PriorLabs
14.4/25Track record — 13 public repos, account ~3 yr old
Inputs used
followers411
owner_typeOrganization
is_verifiedno
owner_loginPriorLabs
public_repos13
account_age_days1,100

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 81 days ago
20/20Version history — 31 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagestabpfn-common-utils
ecosystemspypi
any_deprecatedno
min_days_since_publish81

Engineering Quality

Are baseline engineering and documentation practices in place?

76Good · 19% of overall

Engineering practices

94Exceptional
How it's scored
24/24CI workflows — 2 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff])
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 12 out of 12 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

50Moderate
How it's scored
30/30README
0/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
0/10Topics
10/10Wiki
Inputs used
topics—
has_wikiyes
homepage—
docs_site—
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

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

64Moderate · 16% of overall

Security posture

55Moderate
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
4.5/7.5Branch-Protection — branch protection is not maximal on development and all release branches
2.5/2.5CI-Tests — 12 out of 12 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
3.8/7.5Code-Review — Found 5/10 approved changesets -- score normalized to 5
1.5/2.5Contributors — project has 2 contributing companies or organizations -- score normalized to 6
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
2.2/7.5Maintained — 4 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 3
5/5Packaging — packaging workflow detected
0.5/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 1
1/5SAST — SAST tool is not run on all commits -- score normalized to 2
5/5Security-Policy — security policy file detected
0/7.5Signed-Releases — no data
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities — 11 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate5.5
Excluded from scoring (no data or not applicable): Signed-Releases. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisories — no direct dependency carries a known advisory
25/25Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
0/40No advisories left outstanding — no advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages22
unassessed_packages0
affected_by_severitynone
direct_affected_packages0
Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:tabpfn-common-utils@0.2.23 runtime dependency closure — what installing the published package pulls in — 22 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.

58Moderate · 4% of overall

Agent context & guidance

27At Risk
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
27.2/40Legible commit history — 50 of 98 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.51
agent_instruction_files—
agent_instruction_max_bytes—

Verify loop (build / test / typecheck)

73Good
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff])
11/11Static type checking — src/tabpfn_common_utils/py.typed
10/10Reproducible environment — lockfile
10/10Demonstrated agent practice — 13 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance — 2 of the last 100 commits are automated dependency updates
1/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 1
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileno
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configyes
typecheck_configssrc/tabpfn_common_utils/py.typed
agent_commit_share0.13
toolchain_manifests—
dependency_bot_commit_share0.02

Code legibility for models

82Excellent
How it's scored
27/45Type-checkable code — Python with type-check config (src/tabpfn_common_utils/py.typed)
55/55Manageable file sizes — 0/26 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes17,783
source_files_sampled26
oversized_source_files0

Key facts

0GitHub stars
14contributors
163commits, last 12 months
52days since last push
6releases
1bus factor
0open issues
PyPIpackage ecosystems

More detail

Star and fork history 0 ★ / 5 ⇿
0Stars
5Forks
6Releases

When each star and fork was added, collected from GitHub and bucketed by day. Cumulative growth sits directly above the daily additions it is made of, so the two read against each other: steady organic accretion looks nothing like an abrupt, short-lived burst. Where that difference is measurable, it is reported as growth authenticity.

12345512024-092025-092026-09
Major 0Minor 0Patch 6

Each point covers 2 days.

OpenSSF Scorecard 5.5 / 10
5.5aggregate

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 · 2026-09-12 10:45 UTC

10Binary-Artifactsno binaries found in the repo
6Branch-Protectionbranch protection is not maximal on development and all release branches
10CI-Tests12 out of 12 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
5Code-ReviewFound 5/10 approved changesets -- score normalized to 5
6Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
3Maintained4 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 3
10Packagingpackaging workflow detected
1Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 1
2SASTSAST tool is not run on all commits -- score normalized to 2
10Security-Policysecurity policy file detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0Vulnerabilities11 existing vulnerabilities detected
Direct dependencies 9
RegistryPackageVersion constraintManifest
PyPInumpy>=1.21.6pyproject.toml
PyPIpandas>=1.4.0pyproject.toml
PyPIscikit-learn>=1.2.0pyproject.toml
PyPItyping-extensions>=4.12pyproject.toml
PyPIposthog>=6.7pyproject.toml
PyPIplatformdirs>=4pyproject.toml
PyPIfilelock>=3.19.1pyproject.toml
PyPIrequests>=2.32.5pyproject.toml
PyPInvidia-ml-py>=13.590.48pyproject.toml
All dependencies 68

Full resolved dependency set from the GitHub dependency graph: 9 direct and 59 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIfilelock3.19.1direct
PyPInumpy2.0.2direct
PyPInvidia-ml-py13.595.45direct
PyPIpandas2.3.3direct
PyPIplatformdirs4.4.0direct
PyPIposthog6.9.3direct
PyPIrequests2.32.5direct
PyPIscikit-learn1.6.1direct
PyPItyping-extensions4.15.0direct
PyPIbackoff2.2.1indirect
PyPIbackports-tarfile1.2.0indirect
PyPIbuild1.4.3indirect
PyPIcertifi2026.2.25indirect
PyPIcffi2.0.0indirect
PyPIcharset-normalizer3.4.7indirect
PyPIcolorama0.4.6indirect
PyPIcoverage7.10.7indirect
PyPIcryptography46.0.7indirect
PyPIdistro1.9.0indirect
PyPIdocutils0.22.4indirect
PyPIexceptiongroup1.3.1indirect
PyPIhatch-vcs0.5.0indirect
PyPIhatchling1.27.0indirect
PyPIid1.6.1indirect
PyPIidna3.15indirect
PyPIimportlib-metadata8.7.1indirect
PyPIiniconfig2.1.0indirect
PyPIjaraco-classes3.4.0indirect
PyPIjaraco-context6.1.1indirect
PyPIjaraco-functools4.4.0indirect
PyPIjeepney0.9.0indirect
PyPIjoblib1.5.3indirect
PyPIkeyring25.7.0indirect
PyPImarkdown-it-py3.0.0indirect
PyPImdurl0.1.2indirect
PyPImore-itertools10.8.0indirect
PyPInh30.3.4indirect
PyPInodeenv1.10.0indirect
PyPIpackaging26.0indirect
PyPIpathspec1.0.4indirect
PyPIpluggy1.6.0indirect
PyPIpycparser2.23indirect
PyPIpygments2.20.0indirect
PyPIpyproject-hooks1.2.0indirect
PyPIpyright1.1.408indirect
PyPIpytest8.4.2indirect
PyPIpytest-cov7.1.0indirect
PyPIpython-dateutil2.9.0.post0indirect
PyPIpytz2026.1.post1indirect
PyPIpywin32-ctypes0.2.3indirect
PyPIreadme-renderer44.0indirect
PyPIrequests-toolbelt1.0.0indirect
PyPIrfc39862.0.0indirect
PyPIrich15.0.0indirect
PyPIruff0.15.10indirect
PyPIscipy1.13.1indirect
PyPIsecretstorage3.3.3indirect
PyPIsetuptools82.0.1indirect
PyPIsetuptools-scm9.2.2indirect
PyPIsix1.17.0indirect
PyPIthreadpoolctl3.6.0indirect
PyPItomli2.4.1indirect
PyPItrove-classifiers2026.1.14.14indirect
PyPItwine6.2.0indirect
PyPItzdata2026.1indirect
PyPIurllib32.6.3indirect
PyPIvcs-versioning1.1.1indirect
PyPIzipp3.23.1indirect
Dependency advisories 0

Installing pypi:tabpfn-common-utils@0.2.23 pulls in 22 packages, direct and transitive: 0 carry known advisories, of which 0 are direct dependencies.

No known advisories affect the assessed dependencies.

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

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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 v0.34.0 — full methodology · metrics wiki.

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