Public record
Software health reportschema 0.31.0 · metrics 2.10.0 · 2026-08-13 02:11 UTC

Farama-Foundation / Arcade-Learning-Environment

A simple framework that allows researchers and hobbyists to develop AI agents for Atari 2600 games

C++ · IDLGPL-2.0★ 2,441 stars⑂ 477 forkssince Sep 2012View on GitHub ↗

Farama-Foundation/Arcade-Learning-Environment holds a health index of 91 out of 100, placing it in the Excellent band. It scores highest on Sustainability & Governance (88/100) and lowest on Security (46/100). It was last updated 2 days ago. 3 contributors account for most of its recent work.

91
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.

91
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 77 is calibrated to 91 on the published index scale (record calibration 2026-08-02).

Ownership

Farama FoundationOrganization
2,002 followers45 public repossince Mar 2020

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIale-py0.12.0-2374 days agoreinforcement-learningarcade-learning-environmentatari

Metrics by category

Vitality

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

79Good · 21% of overall
How it's scored
36/36Push recencylast push 2 days ago
15.2/36Commit cadence22/52 weeks with commits
16.4/18Commit volume66 commits in the last year
0/10OpenSSF Scorecard: Maintainedno data
Inputs used
commits_last_year66
human_commit_share0.78
days_since_last_push2
active_weeks_last_year22
How it's scored
27/27Ships releases22 releases published
36/36Release recencylatest release 75 days ago
12.6/27Release cadencea release every ~133.1 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count22
latest_release_tagv0.12.0
releases_from_tagsno
days_since_latest_release75
mean_days_between_releases133.1

Community & Adoption

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

80Excellent · 17% of overall
How it's scored
54.9/60Stars2,441 stars
22.3/25Forks477 forks
10.4/15Watchers76 watchers
Inputs used
forks477
stars2,441
watchers76
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (GPL-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_badges2
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_servicesshields.io
has_pull_request_templateno

Sustainability & Governance

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

88Excellent · 23% of overall
How it's scored
36/54Bus factor3 contributor(s) cover half of all commits
16.1/22.5Commit distributiontop contributor authored 28% of commits
13.5/13.5Contributor breadth60 contributors
0/10OpenSSF Scorecard: Contributorsno data
Inputs used
bus_factor3
contributors_sampled60
top_contributor_share0.283
How it's scored
37/42Issue resolution88% of issues closed
25/30PR acceptance357/428 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Reviewno data
Inputs used
merged_prs357
open_issues34
closed_issues250
prs_merged_7d2
prs_decided_7d3
prs_merged_30d8
prs_decided_30d11
issue_closed_ratio0.88
closed_unmerged_prs71
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
0/20Verified domainverified-domain status not read for this organization
23.7/25Owner reach2,002 followers of Farama-Foundation
24.1/25Track record45 public repos, account ~6 yr old
Inputs used
followers2,002
owner_typeOrganization
is_verified
owner_loginFarama-Foundation
public_repos45
account_age_days2,325
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable1 package(s) on pypi
35/35Publish recencylatest publish 74 days ago
20/20Version history23 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesale-py
ecosystemspypi
any_deprecatedno
min_days_since_publish74

Engineering Quality

Are baseline engineering and documentation practices in place?

87Excellent · 19% of overall
How it's scored
24/24CI workflows7 workflow(s)
24/24Tests present
16/16Linter config
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Testsno data
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

80Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage sitehttps://ale.farama.org/
10/10Repository description
0/10Topics
0/10Wiki
Inputs used
topics
has_wikino
homepagehttps://ale.farama.org/
docs_sitehttps://ale.farama.org/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

46Weak · 16% of overall
How it's scored
0/30Security policy (SECURITY.md)
25/25Dependabot config
0/25Dependency lockfilespublished library — lockfiles are an application concern, not expected
0/20CodeQL workflow
Inputs used
sourcefile_signals
lockfiles
manifestsdocs/requirements.txt, pyproject.toml
has_codeql_workflowno
has_security_policyno
has_dependabot_configyes
Excluded from scoring (no data or not applicable): Dependency lockfiles. Remaining weights renormalized.

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_packages1
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:ale-py@0.12.0 runtime dependency closure — what installing the published package pulls in — 1 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.

74Good · 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 history60 of 78 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.769
agent_instruction_files
agent_instruction_max_bytes
How it's scored
18/18One-command bootstrapJustfile, docs/Makefile, mise.toml
22/22Automated tests
11/11Lint / format config
11/11Static type checkingsrc/ale/python/py.typed
0/10Reproducible environment
10/10Demonstrated agent practice7 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance22 of the last 100 commits are automated dependency updates
0/10OpenSSF Scorecard: Pinned-Dependenciesno data
Inputs used
has_nixno
has_testsyes
lockfiles
has_dockerfileno
typed_languageyes
bootstrap_filesJustfile, docs/Makefile, mise.toml
has_devcontainerno
has_linter_configyes
typecheck_configssrc/ale/python/py.typed
agent_commit_share0.07
toolchain_manifests
dependency_bot_commit_share0.22
How it's scored
45/45Type-checkable codeC++ (statically typed)
55/55Manageable file sizes0/277 source files over 60KB
Inputs used
primary_languageC++
largest_source_bytes29,723
source_files_sampled277
oversized_source_files0

Key facts

2,441GitHub stars
60contributors
66commits, last 12 months
2days since last push
22releases
3bus factor
34open 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 ★ / 477 ⇿
0Stars
477Forks
22Releases

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.

010020030040050043172013-062020-012026-08
Major 0Minor 8Patch 14

Each point covers 13 days.

Direct dependencies 2
RegistryPackageVersion constraintManifest
PyPInumpy>1.20pyproject.toml
PyPItyping-extensionspyproject.toml
All dependencies 11

Full resolved dependency set from the GitHub dependency graph: 2 direct and 9 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPInumpydirect
PyPItyping-extensionsdirect
PyPIcelshastindirect
PyPIgymnasiumindirect
PyPImoviepyindirect
PyPImyst-parserindirect
PyPIpygameindirect
PyPIsphinxindirect
PyPIsphinx-autobuildindirect
PyPIsphinx-galleryindirect
PyPIsphinx-github-changelogindirect
Dependency advisories 0

Installing pypi:ale-py@0.12.0 pulls in 1 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 v0.31.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statisticsPyPI.