Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-19 01:59 UTC

cvs-health / uqlm

[JMLR 2026] "UQLM: A Python Package for Uncertainty Quantification in Large Language Models"

PythonApache-2.0★ 1,200 stars⑂ 132 forkssince Apr 2025View on GitHub ↗
KindLibraryhow this is determined
#ai-evaluation#ai-safety#hallucination#hallucination-detection#hallucination-evaluation#hallucination-mitigation#llm#llm-evaluation#llm-hallucination#llm-safety#uncertainty-estimation#uncertainty-quantification#confidence-estimation#confidence-score

cvs-health/uqlm holds a health index of 92 out of 100, placing it in the Excellent band. It scores highest on Engineering Quality (96/100) and lowest on Security (57/100). It was last updated 4 days ago. A single contributor accounts for most of its recent work.

92
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.

92
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 78 is calibrated to 92 on the published index scale (record calibration 2026-08-02).

Ownership

CVS HealthOrganization
118 followers16 public repossince Aug 2021

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIuqlm0.6.61,5917115 days agollmllm-evaluationhallucinationlarge-language-modeluncertainty-quantification

Metrics by category

Vitality

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

93Exceptional · 21% of overall

Development activity

95Exceptional
How it's scored
36/36Push recency — last push 4 days ago
31.2/36Commit cadence — 45/52 weeks with commits
18/18Commit volume — 838 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_year838
human_commit_share0.91
days_since_last_push4
active_weeks_last_year45

Release discipline

90Excellent
How it's scored
27/27Ships releases — 45 releases published
36/36Release recency — latest release 15 days ago
27/27Release cadence — a release every ~16.3 days
0/10OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases.
Inputs used
releases_count45
latest_release_tagv0.6.6
releases_from_tagsno
days_since_latest_release15
mean_days_between_releases16.3

Community & Adoption

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

75Good · 17% of overall

Popularity & adoption

73Good
How it's scored
49.9/60Stars — 1,200 stars
17.6/25Forks — 132 forks
5.3/15Watchers — 10 watchers
Inputs used
forks132
stars1,200
watchers10
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

92Excellent
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (Apache-2.0)
18/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges12
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_servicesbadge.fury.io, github.com, shields.io
has_pull_request_templateyes

Ecosystem adoption (downloads)

53Moderate
How it's scored
42.7/80Monthly downloads — 1,591 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesuqlm
dependents—
ecosystemspypi
total_downloads—
monthly_downloads1,591
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?

67Good · 23% of overall

Maintainer resilience (bus factor)

38Weak
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
6/22.5Commit distribution — top contributor authored 73% of commits
13.5/13.5Contributor breadth — 18 contributors
10/10OpenSSF Scorecard: Contributors — project has 4 contributing companies or organizations
Inputs used
bus_factor1
contributors_sampled18
top_contributor_share0.732

Issue & PR responsiveness

78Good
How it's scored
33.6/42Issue resolution — 80% of issues closed
23.8/30PR acceptance — 309/390 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
10.5/15OpenSSF Scorecard: Code-Review — Found 7/10 approved changesets -- score normalized to 7
Inputs used
merged_prs309
open_issues14
closed_issues56
prs_merged_7d0
prs_decided_7d0
prs_merged_30d9
prs_decided_30d11
issue_closed_ratio0.8
closed_unmerged_prs81
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

64Moderate
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
14.9/25Owner reach — 118 followers of cvs-health
19.1/25Track record — 16 public repos, account ~5 yr old
Inputs used
followers118
owner_typeOrganization
is_verifiedno
owner_logincvs-health
public_repos16
account_age_days1,850

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 15 days ago
20/20Version history — 71 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesuqlm
ecosystemspypi
any_deprecatedno
min_days_since_publish15

Engineering Quality

Are baseline engineering and documentation practices in place?

96Exceptional · 19% of overall

Engineering practices

94Exceptional
How it's scored
24/24CI workflows — 4 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 — 10 out of 10 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

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://cvs-health.github.io/uqlm/latest/index.html
10/10Repository description
10/10Topics — 14 topics
10/10Wiki
Inputs used
topicsai-evaluation, ai-safety, hallucination, hallucination-detection, hallucination-evaluation, hallucination-mitigation, llm, llm-evaluation, llm-hallucination, llm-safety, uncertainty-estimation, uncertainty-quantification, confidence-estimation, confidence-score
has_wikiyes
homepagehttps://cvs-health.github.io/uqlm/latest/index.html
docs_sitehttps://cvs-health.github.io/uqlm/latest/index.html
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

57Moderate · 16% of overall

Security posture

55Moderate
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 — 10 out of 10 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
5.2/7.5Code-Review — Found 7/10 approved changesets -- score normalized to 7
2.5/2.5Contributors — project has 4 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
7.5/7.5Maintained — 30 commit(s) and 8 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
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
5/5Security-Policy — security policy file 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
2.2/7.5Vulnerabilities — 7 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated18
scorecard_versionv5.5.0
checks_inconclusive0
scorecard_aggregate5.5

Dependency advisories

65Good
How it's scored
7.6/35Direct dependencies free of known advisories — 2 affected: transformers 4.57.6 (critical 9.6), datasets 4.8.5 (unknown)
25/25Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
32.3/40No advisories left outstanding — 1 advisory-carrying package(s) unaddressed past 90 days; oldest published 269 days ago
Inputs used
sourceosv
advisories10
affected_packages2
assessed_packages137
unassessed_packages0
affected_by_severitycritical 1, unknown 1
direct_affected_packages2
Matched the pypi:uqlm@0.6.6 runtime dependency closure — what installing the published package pulls in — 137 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.

66Good · 4% of overall

Agent context & guidance

48Weak
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
15/15Machine-readable docs (llms.txt) — llms.txt served by the project website (https://js.langchain.com/llms.txt)
33.4/40Legible commit history — 57 of 91 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtyes
llms_txt_urlhttps://js.langchain.com/llms.txt
legible_history_share0.626
agent_instruction_files—
agent_instruction_max_bytes—

Verify loop (build / test / typecheck)

71Good
How it's scored
18/18One-command bootstrap — docs/Makefile
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff])
0/11Static type checking
10/10Reproducible environment — lockfile
2/10Demonstrated agent practice — 1 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance — 9 of the last 100 commits are automated dependency updates
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileno
typed_languageno
bootstrap_filesdocs/Makefile
has_devcontainerno
has_linter_configyes
typecheck_configs—
agent_commit_share0.01
toolchain_manifests—
dependency_bot_commit_share0.09

Code legibility for models

55Moderate
How it's scored
0/45Type-checkable code — Python without a type-check config
55/55Manageable file sizes — 0/146 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes36,354
source_files_sampled146
oversized_source_files0

Machine-readable interfaces

100Exceptional
How it's scored
0/40API schema (OpenAPI/GraphQL/proto) — not applicable to this kind of software
0/20MCP server — not applicable to this kind of software
40/40Runnable examples — examples, notebooks
Inputs used
example_dirsexamples, notebooks
has_mcp_signalno
api_schema_files—
interfaces_expected_of—
Excluded from scoring (no data or not applicable): API schema (OpenAPI/GraphQL/proto), MCP server. Remaining weights renormalized.

Key facts

1,200GitHub stars
18contributors
838commits, last 12 months
4days since last push
45releases
1bus factor
14open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token

More detail

Star and fork history 0 ★ / 132 ⇿
0Stars
132Forks
45Releases

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.

0255075100125150130282025-052026-012026-09
Major 0Minor 6Patch 39

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 · 2026-09-19 01:59 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
10CI-Tests10 out of 10 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
7Code-ReviewFound 7/10 approved changesets -- score normalized to 7
10Contributorsproject has 4 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate 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
10Packagingpackaging workflow detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0SASTSAST tool is not run on all commits -- score normalized to 0
10Security-Policysecurity policy file detected
0Signed-ReleasesProject has not signed or included provenance with any releases.
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
3Vulnerabilities7 existing vulnerabilities detected
Direct dependencies 17
RegistryPackageVersion constraintManifest
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All dependencies 249

Full resolved dependency set from the GitHub dependency graph: 20 direct and 229 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

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PyPIsphinxcontrib-devhelp2.0.0indirect
PyPIsphinxcontrib-htmlhelp2.1.0indirect
PyPIsphinxcontrib-jsmath1.0.1indirect
PyPIsphinxcontrib-qthelp2.0.0indirect
PyPIsphinxcontrib-serializinghtml2.0.0indirect
PyPIsqlalchemy2.0.52indirect
PyPIstack-data0.6.3indirect
PyPIsympy1.14.0indirect
PyPItenacity9.1.4indirect
PyPIthreadpoolctl3.6.0indirect
PyPItiktoken0.13.0indirect
PyPItinycss21.5.1indirect
PyPItokenizers0.22.2indirect
PyPItomli2.4.1indirect
PyPItornado6.5.8indirect
PyPItqdm4.70.0indirect
PyPItraitlets5.16.1indirect
PyPItriton3.7.1indirect
PyPItyping-extensions4.16.0indirect
PyPItyping-inspection0.4.4indirect
PyPItzdata2026.3indirect
PyPIuqlm0.6.5indirect
PyPIurllib32.7.0indirect
PyPIuuid-utils0.17.0indirect
PyPIvalidators0.35.0indirect
PyPIvirtualenv21.7.4indirect
PyPIwcwidth0.8.2indirect
PyPIwebencodings0.5.1indirect
PyPIwebsockets15.0.1indirect
PyPIwidgetsnbextension4.0.15indirect
PyPIxxhash4.0.0indirect
PyPIyarl1.24.5indirect
PyPIzstandard0.25.0indirect
Dependency advisories 2

Installing pypi:uqlm@0.6.6 pulls in 137 packages, direct and transitive: 2 carry known advisories, of which 2 are direct dependencies.

PackageVersionRelationSeverityAdvisoriesFixed in
transformers4.57.6directcritical95.10.0
datasets4.8.5directunknown15.0.1

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.

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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.