Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-19 13:34 UTC

ansible / ansible-rulebook

PythonApache-2.0★ 224 stars⑂ 94 forkssince Feb 2022View on GitHub ↗
KindCommand-line toolLibraryhow this is determined

ansible/ansible-rulebook holds a health index of 88 out of 100, placing it in the Excellent band. It scores highest on Vitality (89/100) and lowest on Security (40/100). It was last updated 1 day ago. 2 contributors account for most of its recent work.

88
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.

88
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 74 is calibrated to 88 on the published index scale (record calibration 2026-08-02).

Ownership

AnsibleOrganization · verified domain
3,757 followers306 public repossince Mar 2012

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIansible_rulebook1.3.16,1603253 days agoansible-rulebook

Metrics by category

Vitality

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

89Excellent · 21% of overall
How it's scored
36/36Push recencylast push 1 days ago
24.2/36Commit cadence35/52 weeks with commits
18/18Commit volume100 commits in the last year
0/10OpenSSF Scorecard: Maintainedno data
Inputs used
commits_last_year100
human_commit_share0.47
days_since_last_push1
active_weeks_last_year35
How it's scored
27/27Ships releases28 releases published
36/36Release recencylatest release 53 days ago
19.8/27Release cadencea release every ~53.6 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count28
latest_release_tagv1.3.1
releases_from_tagsno
days_since_latest_release53
mean_days_between_releases53.6

Community & Adoption

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

70Good · 17% of overall
How it's scored
38.1/60Stars224 stars
16.4/25Forks94 forks
6.8/15Watchers18 watchers
Inputs used
forks94
stars224
watchers18
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

85Excellent
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (Apache-2.0)
18/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges10
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_servicescodecov.io, github.com, readthedocs.org, shields.io, sonarcloud.io
has_pull_request_templateno
How it's scored
50.5/80Monthly downloads6,160 downloads/month across pypi
0/20Registry dependentsnot reported by this ecosystem
Inputs used
packagesansible_rulebook
dependents
ecosystemspypi
total_downloads
monthly_downloads6,160
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?

79Good · 23% of overall
How it's scored
25.2/54Bus factor2 contributor(s) cover half of all commits
14.6/22.5Commit distributiontop contributor authored 35% of commits
13.5/13.5Contributor breadth41 contributors
0/10OpenSSF Scorecard: Contributorsno data
Inputs used
bus_factor2
contributors_sampled41
top_contributor_share0.35
How it's scored
22.4/42Issue resolution53% of issues closed
25.1/30PR acceptance756/902 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Reviewno data
Inputs used
merged_prs756
open_issues27
closed_issues31
prs_merged_7d0
prs_decided_7d1
prs_merged_30d0
prs_decided_30d1
issue_closed_ratio0.534
closed_unmerged_prs146
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.
How it's scored
30/30Ownership backingorganization-owned
20/20Verified domain
25/25Owner reach3,757 followers of ansible
25/25Track record306 public repos, account ~14 yr old
Inputs used
followers3,757
owner_typeOrganization
is_verifiedyes
owner_loginansible
public_repos306
account_age_days5,309

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable1 package(s) on pypi
35/35Publish recencylatest publish 53 days ago
20/20Version history32 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesansible_rulebook
ecosystemspypi
any_deprecatedno
min_days_since_publish53

Engineering Quality

Are baseline engineering and documentation practices in place?

86Excellent · 19% of overall

Engineering practices

100Exceptional
How it's scored
24/24CI workflows5 workflow(s)
24/24Tests present
16/16Linter configpyproject.toml ([tool.black], [tool.isort]), setup.cfg ([flake8]), tox.ini
9.6/9.6Pre-commit hooks
6.4/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Testsno data
Inputs used
has_ciyes
has_testsyes
has_editorconfigyes
has_linter_configyes
has_precommit_configyes
How it's scored
30/30README
25/25Documentation directory
0/15Documentation / homepage site
0/10Repository description
0/10Topics
10/10Wiki
Inputs used
topics
has_wikiyes
homepage
docs_site
has_readmeyes
has_docs_diryes
has_descriptionno

Security

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

40Weak · 16% of overall
How it's scored
0/30Security policy (SECURITY.md)
25/25Dependabot config
0/25Dependency lockfiles
0/20CodeQL workflow
Inputs used
sourcefile_signals
lockfiles
manifestsdocs/requirements.txt, pyproject.toml, requirements_dev.txt, requirements_lint.txt, requirements_test.txt, setup.cfg
has_codeql_workflowno
has_security_policyno
has_dependabot_configyes

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisoriesno direct dependency carries a known advisory
25/25Indirect dependencies free of known advisoriesno indirect dependency carries a known advisory
0/40No advisories left outstandingno advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages35
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:ansible_rulebook@1.3.1 runtime dependency closure — what installing the published package pulls in — 35 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.

70Good · 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 history47 of 47 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share1
agent_instruction_files
agent_instruction_max_bytes
How it's scored
18/18One-command bootstrapMakefile, docs/Makefile
22/22Automated tests
11/11Lint / format configpyproject.toml ([tool.black], [tool.isort]), setup.cfg ([flake8]), tox.ini
0/11Static type checking
10/10Reproducible environmentDockerfile
10/10Demonstrated agent practice8 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance53 of the last 100 commits are automated dependency updates
0/10OpenSSF Scorecard: Pinned-Dependenciesno data
Inputs used
has_nixno
has_testsyes
lockfiles
has_dockerfileyes
typed_languageno
bootstrap_filesMakefile, docs/Makefile
has_devcontainerno
has_linter_configyes
typecheck_configs
agent_commit_share0.08
toolchain_manifests
dependency_bot_commit_share0.53
How it's scored
0/45Type-checkable codePython without a type-check config
54.7/55Manageable file sizes1/160 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes84,245
source_files_sampled160
oversized_source_files1
How it's scored
0/40API schema (OpenAPI/GraphQL/proto)not applicable to this kind of software
0/20MCP servernot applicable to this kind of software
40/40Runnable examplesdemos, examples
Inputs used
example_dirsdemos, examples
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

224GitHub stars
41contributors
100commits, last 12 months
1days since last push
28releases
2bus factor
27open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • OpenSSF Scorecard timed out after 240s; skipping Scorecard checks

More detail

Star and fork history 0 ★ / 94 ⇿
0Stars
94Forks
27Releases

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.

0204060801009242022-102024-082026-07
Major 1Minor 6Patch 20

Each point covers 4 days.

Direct dependencies 16
RegistryPackageVersion constraintManifest
PyPIaiohttp>=3.9,<4setup.cfg
PyPIaiohttp-retry>=2.9,<3setup.cfg
PyPIaiofiles>=23,<26setup.cfg
PyPItenacity>=9,<10setup.cfg
PyPIpyparsing>= 3.0,<4setup.cfg
PyPIjsonschema>=4,<5setup.cfg
PyPIjinja2>=3,<4setup.cfg
PyPIdpath>= 2.1.4,<3setup.cfg
PyPIjanus>=1,<2setup.cfg
PyPIansible-runner>=2,<3setup.cfg
PyPIwebsockets>=15,<15.1setup.cfg
PyPIdrools_jpy== 0.4.1setup.cfg
PyPIwatchdog>=3,<7setup.cfg
PyPIxxhash>=3,<4setup.cfg
PyPIpyyaml>=6,<7setup.cfg
PyPIpsycopg>=3,<4setup.cfg
All dependencies 53

Full resolved dependency set from the GitHub dependency graph: 16 direct and 37 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIaiofilesdirect
PyPIaiohttpdirect
PyPIaiohttp-retrydirect
PyPIansible-runnerdirect
PyPIdpathdirect
PyPIdrools-jpy0.4.1direct
PyPIjanusdirect
PyPIjinja2direct
PyPIjsonschemadirect
PyPIpsycopgdirect
PyPIpyparsingdirect
PyPIpyyamldirect
PyPItenacitydirect
PyPIwatchdogdirect
PyPIwebsocketsdirect
PyPIxxhashdirect
PyPIaioresponsesindirect
PyPIansibleindirect
PyPIansible-builderindirect
PyPIansible-coreindirect
PyPIanyioindirect
PyPIblack22.12.0indirect
PyPIbuildindirect
PyPIcoverageindirect
PyPIdocoptindirect
PyPIdynaconfindirect
PyPIflake85.0.4indirect
PyPIflake8-bugbearindirect
PyPIfreezegunindirect
PyPIhttpieindirect
PyPIisortindirect
PyPIjmespathindirect
PyPIkubernetesindirect
PyPImarshmallow3.26.1indirect
PyPIoauthlibindirect
PyPIpexpectindirect
PyPIpre-commitindirect
PyPIpsutilindirect
PyPIpytestindirect
PyPIpytest-asyncioindirect
PyPIpytest-checkindirect
PyPIpytest-covindirect
PyPIpytest-jiraindirect
PyPIpytest-timeoutindirect
PyPIpytest-xdistindirect
PyPIrequestsindirect
PyPIsetuptoolsindirect
PyPIsetuptools-scmindirect
PyPIsphinxindirect
PyPIsphinx-ansible-theme0.10.1indirect
PyPItoxindirect
PyPItwineindirect
PyPIurllib3indirect
Dependency advisories 0

Installing pypi:ansible_rulebook@1.3.1 pulls in 35 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

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.