Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-17 15:14 UTC

dottxt-ai / outlines

Structured Outputs

PythonApache-2.0★ 15,824 stars⑂ 879 forkssince Mar 2023View on GitHub ↗
KindLibraryhow this is determined
#generative-ai#llms#prompt-engineering#symbolic-ai#cfg#json#regex#structured-generation

dottxt-ai/outlines holds a health index of 96 out of 100, placing it in the Exceptional band. It scores highest on Engineering Quality (96/100) and lowest on Security (59/100). It was last updated 7 days ago. 2 contributors account for most of its recent work.

96
overall / 100
Exceptional

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.

96
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 83 is calibrated to 96 on the published index scale (record calibration 2026-08-02).

Ownership

.txtOrganization · verified domain
347 followers15 public repossince Aug 2023

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIoutlines1.3.31,383,8058442 days agomachine-learningdeep-learninglanguage-modelsstructured-generation

Metrics by category

Vitality

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

94Exceptional · 21% of overall

Development activity

90Excellent
How it's scored
36/36Push recency — last push 7 days ago
25.6/36Commit cadence — 37/52 weeks with commits
18/18Commit volume — 202 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year202
human_commit_share1
days_since_last_push7
active_weeks_last_year37

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 90 releases published
36/36Release recency — latest release 42 days ago
27/27Release cadence — a release every ~31.5 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count90
latest_release_tag1.3.3
releases_from_tagsno
days_since_latest_release42
mean_days_between_releases31.5
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?

87Excellent · 17% of overall

Popularity & adoption

94Exceptional
How it's scored
60/60Stars — 15,824 stars
24.5/25Forks — 879 forks
9.9/15Watchers — 61 watchers
Inputs used
forks879
stars15,824
watchers61
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 (Apache-2.0)
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges0
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_services—
has_pull_request_templateno

Ecosystem adoption (downloads)

100Exceptional
How it's scored
80/80Monthly downloads — 1,383,805 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesoutlines
dependents—
ecosystemspypi
total_downloads—
monthly_downloads1,383,805
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?

78Good · 23% of overall

Maintainer resilience (bus factor)

62Moderate
How it's scored
25.2/54Bus factor — 2 contributor(s) cover half of all commits
13.3/22.5Commit distribution — top contributor authored 41% of commits
13.5/13.5Contributor breadth — 100 contributors
10/10OpenSSF Scorecard: Contributors — project has 32 contributing companies or organizations
Inputs used
bus_factor2
contributors_sampled100
top_contributor_share0.41

Issue & PR responsiveness

75Good
How it's scored
37.3/42Issue resolution — 89% of issues closed
24.4/30PR acceptance — 721/885 decided PRs merged
0/13Newcomer PR acceptance — 0/6 first-time contributors' PRs merged in 30d
13.5/15OpenSSF Scorecard: Code-Review — Found 23/24 approved changesets -- score normalized to 9
Inputs used
merged_prs721
open_issues100
closed_issues803
prs_merged_7d0
prs_decided_7d1
prs_merged_30d1
prs_decided_30d15
issue_closed_ratio0.889
closed_unmerged_prs164
first_time_authors_30d4
first_time_prs_merged_30d0
first_time_prs_decided_30d6

Ownership & stewardship

83Excellent
How it's scored
30/30Ownership backing — organization-owned
20/20Verified domain
18.3/25Owner reach — 347 followers of dottxt-ai
14.9/25Track record — 15 public repos, account ~3 yr old
Inputs used
followers347
owner_typeOrganization
is_verifiedyes
owner_logindottxt-ai
public_repos15
account_age_days1,129

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 42 days ago
20/20Version history — 84 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesoutlines
ecosystemspypi
any_deprecatedno
min_days_since_publish42

Engineering Quality

Are baseline engineering and documentation practices in place?

96Exceptional · 19% of overall

Engineering practices

100Exceptional
How it's scored
24/24CI workflows — 6 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff]), setup.cfg ([flake8])
9.6/9.6Pre-commit hooks
6.4/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 24 out of 24 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigyes
has_linter_configyes
has_precommit_configyes

Documentation

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://dottxt-ai.github.io/outlines/
10/10Repository description
10/10Topics — 8 topics
0/10Wiki
Inputs used
topicsgenerative-ai, llms, prompt-engineering, symbolic-ai, cfg, json, regex, structured-generation
has_wikino
homepagehttps://dottxt-ai.github.io/outlines/
docs_sitehttps://dottxt-ai.github.io/outlines/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

59Moderate · 16% of overall

Security posture

51Moderate
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 — 24 out of 24 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
6.8/7.5Code-Review — Found 23/24 approved changesets -- score normalized to 9
2.5/2.5Contributors — project has 32 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 0 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
1.5/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 3
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
0/7.5Vulnerabilities — 135 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate5.1
Excluded from scoring (no data or not applicable): Branch-Protection, Signed-Releases. Remaining weights renormalized.

Dependency advisories

89Excellent
How it's scored
26.6/35Direct dependencies free of known advisories — 1 affected: diskcache 5.6.3 (moderate)
25/25Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
37.2/40No advisories left outstanding — 1 advisory-carrying package(s) unaddressed past 90 days; oldest published 217 days ago
Inputs used
sourceosv
advisories2
affected_packages1
assessed_packages17
unassessed_packages0
affected_by_severitymoderate 1
direct_affected_packages1
Matched the pypi:outlines@1.3.3 runtime dependency closure — what installing the published package pulls in — 17 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.

82Excellent · 4% of overall

Agent context & guidance

94Exceptional
How it's scored
45/45Agent instructions — docs/features/models/gemini.md
15/15Machine-readable docs (llms.txt) — llms.txt served by the project website (https://docs.pydantic.dev/llms.txt)
33.6/40Legible commit history — 63 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtyes
llms_txt_urlhttps://docs.pydantic.dev/llms.txt
legible_history_share0.63
agent_instruction_filesdocs/features/models/gemini.md
agent_instruction_max_bytes6,461

Verify loop (build / test / typecheck)

67Good
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff]), setup.cfg ([flake8])
11/11Static type checking — src/outlines/py.typed
10/10Reproducible environment — devcontainer, Nix, lockfile
10/10Demonstrated agent practice — 9 of the last 100 commits agent-authored or agent-credited
0/8Automated maintenance — no automated dependency updates observed
3/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 3
Inputs used
has_nixyes
has_testsyes
lockfilesuv.lock
has_dockerfileno
typed_languageno
bootstrap_files—
has_devcontaineryes
has_linter_configyes
typecheck_configssrc/outlines/py.typed
agent_commit_share0.09
toolchain_manifests—
dependency_bot_commit_share0

Code legibility for models

82Excellent
How it's scored
27/45Type-checkable code — Python with type-check config (src/outlines/py.typed)
55/55Manageable file sizes — 0/122 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes44,704
source_files_sampled122
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

15,824GitHub stars
100contributors
202commits, last 12 months
7days since last push
90releases
2bus factor
100open 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 ★ / 879 ⇿
0Stars
879Forks
90Releases

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.

02004006008001,000876322023-052025-012026-09
Major 1Minor 5Patch 84

Each point covers 4 days.

OpenSSF Scorecard 5.1 / 10
5.1aggregate

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 · 2026-09-17 15:13 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-Tests24 out of 24 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
9Code-ReviewFound 23/24 approved changesets -- score normalized to 9
10Contributorsproject has 32 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 0 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
3Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 3
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
0Vulnerabilities135 existing vulnerabilities detected
Direct dependencies 9
RegistryPackageVersion constraintManifest
PyPIjinja2—pyproject.toml
PyPIcloudpickle—pyproject.toml
PyPIdiskcache—pyproject.toml
PyPIpydantic>=2.0pyproject.toml
PyPIjsonschema—pyproject.toml
PyPIpillow—pyproject.toml
PyPItyping_extensions—pyproject.toml
PyPIoutlines_core==0.2.14pyproject.toml
PyPIgenson—pyproject.toml
All dependencies 213

Full resolved dependency set from the GitHub dependency graph: 9 direct and 204 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
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PyPIdiskcache5.6.3direct
PyPIgenson1.3.0direct
PyPIjinja23.1.6direct
PyPIjsonschema4.26.0direct
PyPIoutlines-core0.2.14direct
PyPIpillow12.0.0direct
PyPIpydantic2.12.4direct
PyPItyping-extensions4.15.0direct
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PyPIattrs25.4.0indirect
PyPIbackports-asyncio-runner1.2.0indirect
PyPIbeartype0.15.0indirect
PyPIbentoml—indirect
PyPIcachetools6.2.2indirect
PyPIcertifi2025.11.12indirect
PyPIcfgv3.5.0indirect
PyPIchardet5.2.0indirect
PyPIcharset-normalizer3.4.4indirect
PyPIchex0.1.90indirect
PyPIchex0.1.91indirect
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PyPImarkupsafe3.0.3indirect
PyPImdurl0.1.2indirect
PyPImergedeep1.3.4indirect
PyPImike—indirect
PyPImistralai1.9.11indirect
PyPImkdocs—indirect
PyPImkdocs1.6.1indirect
PyPImkdocs-gen-files—indirect
PyPImkdocs-gen-files0.6.0indirect
PyPImkdocs-get-deps0.2.0indirect
PyPImkdocs-git-committers-plugin-2—indirect
PyPImkdocs-git-revision-date-localized-plugin—indirect
PyPImkdocs-literate-nav—indirect
PyPImkdocs-material—indirect
PyPImkdocs-mermaid2-plugin—indirect
PyPImkdocs-redirects—indirect
PyPImkdocs-section-index—indirect
PyPImkdocstrings—indirect
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PyPInvidia-cuda-runtime-cu1212.8.90indirect
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PyPInvidia-cufft-cu1211.3.3.83indirect
PyPInvidia-cufile-cu121.13.1.3indirect
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PyPInvidia-cusparselt-cu120.7.1indirect
PyPInvidia-nccl-cu122.27.5indirect
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PyPIpackaging25.0indirect
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PyPIpytest9.0.1indirect
PyPIpytest-asyncio1.3.0indirect
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PyPIpython-dateutil2.9.0.post0indirect
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PyPIrequests2.32.5indirect
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PyPIsetuptools80.9.0indirect
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PyPIsix1.17.0indirect
PyPIsniffio1.3.1indirect
PyPIsympy1.14.0indirect
PyPItenacity9.1.2indirect
PyPItensorboard2.20.0indirect
PyPItensorboard-data-server0.7.2indirect
PyPItensorflow2.20.0indirect
PyPItensorstore0.1.78indirect
PyPItensorstore0.1.79indirect
PyPItermcolor3.2.0indirect
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PyPItomli2.3.0indirect
PyPItoolz1.1.0indirect
PyPItorch2.9.0indirect
PyPItqdm4.67.1indirect
PyPItransformers4.38.2indirect
PyPItransformers4.57.1indirect
PyPItreescope0.1.10indirect
PyPItriton3.5.0indirect
PyPItyping-inspection0.4.2indirect
PyPItzdata2025.2indirect
PyPIurllib32.5.0indirect
PyPIvirtualenv20.35.4indirect
PyPIwatchdog6.0.0indirect
PyPIwebsockets15.0.1indirect
PyPIwerkzeug3.1.3indirect
PyPIwheel0.45.1indirect
PyPIwrapt2.0.1indirect
PyPIwsproto1.3.2indirect
PyPIxgrammar0.1.27indirect
PyPIxxhash3.6.0indirect
PyPIyarl1.22.0indirect
PyPIzipp3.23.0indirect
Dependency advisories 1

Installing pypi:outlines@1.3.3 pulls in 17 packages, direct and transitive: 1 carry known advisories, of which 1 are direct dependencies.

PackageVersionRelationSeverityAdvisoriesFixed in
diskcache5.6.3directmoderate2—

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

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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.