A simple framework that allows researchers and hobbyists to develop AI agents for Atari 2600 games
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.
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.
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).
This repository is backed by an organization — shared, accountable stewardship that can outlive any single maintainer.
| Registry | Package | Version | Downloads / mo | Versions | Last publish | Tags |
|---|---|---|---|---|---|---|
| PyPI | ale-py | 0.12.0 | - | 23 | 74 days ago | reinforcement-learningarcade-learning-environmentatari |
Is the project alive — is code being written and are releases shipping?
| 36/36 | Push recency — last push 2 days ago |
| 15.2/36 | Commit cadence — 22/52 weeks with commits |
| 16.4/18 | Commit volume — 66 commits in the last year |
| 0/10 | OpenSSF Scorecard: Maintained — no data |
| commits_last_year | 66 |
| human_commit_share | 0.78 |
| days_since_last_push | 2 |
| active_weeks_last_year | 22 |
| 27/27 | Ships releases — 22 releases published |
| 36/36 | Release recency — latest release 75 days ago |
| 12.6/27 | Release cadence — a release every ~133.1 days |
| 0/10 | OpenSSF Scorecard: Signed-Releases — no data |
| releases_count | 22 |
| latest_release_tag | v0.12.0 |
| releases_from_tags | no |
| days_since_latest_release | 75 |
| mean_days_between_releases | 133.1 |
Does the project have users, downloads, attention, and a welcoming setup for contributors?
| 54.9/60 | Stars — 2,441 stars |
| 22.3/25 | Forks — 477 forks |
| 10.4/15 | Watchers — 76 watchers |
| forks | 477 |
| stars | 2,441 |
| watchers | 76 |
| growth_state | unverified |
| growth_factor_pct | 100 |
| growth_unverified_reason | no_history |
| 22.5/22.5 | README |
| 22.5/22.5 | License — recognized license (GPL-2.0) |
| 18/18 | CONTRIBUTING guide |
| 0/13.5 | Code of conduct |
| 0/7.2 | Issue template |
| 0/6.3 | PR template |
| has_readme | yes |
| has_license | yes |
| readme_badges | 2 |
| has_contributing | yes |
| has_issue_template | no |
| has_code_of_conduct | no |
| readme_badge_services | shields.io |
| has_pull_request_template | no |
Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?
| 36/54 | Bus factor — 3 contributor(s) cover half of all commits |
| 16.1/22.5 | Commit distribution — top contributor authored 28% of commits |
| 13.5/13.5 | Contributor breadth — 60 contributors |
| 0/10 | OpenSSF Scorecard: Contributors — no data |
| bus_factor | 3 |
| contributors_sampled | 60 |
| top_contributor_share | 0.283 |
| 37/42 | Issue resolution — 88% of issues closed |
| 25/30 | PR acceptance — 357/428 decided PRs merged |
| 0/13 | Newcomer PR acceptance — no first-time contributor's PR decided in 30d |
| 0/15 | OpenSSF Scorecard: Code-Review — no data |
| merged_prs | 357 |
| open_issues | 34 |
| closed_issues | 250 |
| prs_merged_7d | 2 |
| prs_decided_7d | 3 |
| prs_merged_30d | 8 |
| prs_decided_30d | 11 |
| issue_closed_ratio | 0.88 |
| closed_unmerged_prs | 71 |
| first_time_authors_30d | 0 |
| first_time_prs_merged_30d | 0 |
| first_time_prs_decided_30d | 0 |
| 30/30 | Ownership backing — organization-owned |
| 0/20 | Verified domain — verified-domain status not read for this organization |
| 23.7/25 | Owner reach — 2,002 followers of Farama-Foundation |
| 24.1/25 | Track record — 45 public repos, account ~6 yr old |
| followers | 2,002 |
| owner_type | Organization |
| is_verified | — |
| owner_login | Farama-Foundation |
| public_repos | 45 |
| account_age_days | 2,325 |
| 25/25 | Published & resolvable — 1 package(s) on pypi |
| 35/35 | Publish recency — latest publish 74 days ago |
| 20/20 | Version history — 23 published versions |
| 20/20 | Not deprecated — active, not deprecated or yanked |
| packages | ale-py |
| ecosystems | pypi |
| any_deprecated | no |
| min_days_since_publish | 74 |
Are baseline engineering and documentation practices in place?
| 24/24 | CI workflows — 7 workflow(s) |
| 24/24 | Tests present |
| 16/16 | Linter config |
| 9.6/9.6 | Pre-commit hooks |
| 0/6.4 | .editorconfig |
| 0/20 | OpenSSF Scorecard: CI-Tests — no data |
| has_ci | yes |
| has_tests | yes |
| has_editorconfig | no |
| has_linter_config | yes |
| has_precommit_config | yes |
| 30/30 | README |
| 25/25 | Documentation directory |
| 15/15 | Documentation / homepage site — https://ale.farama.org/ |
| 10/10 | Repository description |
| 0/10 | Topics |
| 0/10 | Wiki |
| topics | — |
| has_wiki | no |
| homepage | https://ale.farama.org/ |
| docs_site | https://ale.farama.org/ |
| has_readme | yes |
| has_docs_dir | yes |
| has_description | yes |
Are visible security and supply-chain practices strong, without unresolved high-risk jurisdiction exposure?
| 0/30 | Security policy (SECURITY.md) |
| 25/25 | Dependabot config |
| 0/25 | Dependency lockfiles — published library — lockfiles are an application concern, not expected |
| 0/20 | CodeQL workflow |
| source | file_signals |
| lockfiles | — |
| manifests | docs/requirements.txt, pyproject.toml |
| has_codeql_workflow | no |
| has_security_policy | no |
| has_dependabot_config | yes |
| 35/35 | Direct dependencies free of known advisories — no direct dependency carries a known advisory |
| 25/25 | Indirect dependencies free of known advisories — no indirect dependency carries a known advisory |
| 0/40 | No advisories left outstanding — no advisory carries a publication date |
| source | osv |
| advisories | 0 |
| affected_packages | 0 |
| assessed_packages | 1 |
| unassessed_packages | 0 |
| affected_by_severity | none |
| direct_affected_packages | 0 |
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.
| 0/45 | Agent instructions — no CLAUDE.md / AGENTS.md / editor rules |
| 0/15 | Machine-readable docs (llms.txt) |
| 40/40 | Legible commit history — 60 of 78 human commits state their intent (structured subject or explanatory body) |
| has_llms_txt | no |
| llms_txt_url | — |
| legible_history_share | 0.769 |
| agent_instruction_files | — |
| agent_instruction_max_bytes | — |
| 18/18 | One-command bootstrap — Justfile, docs/Makefile, mise.toml |
| 22/22 | Automated tests |
| 11/11 | Lint / format config |
| 11/11 | Static type checking — src/ale/python/py.typed |
| 0/10 | Reproducible environment |
| 10/10 | Demonstrated agent practice — 7 of the last 100 commits agent-authored or agent-credited |
| 8/8 | Automated maintenance — 22 of the last 100 commits are automated dependency updates |
| 0/10 | OpenSSF Scorecard: Pinned-Dependencies — no data |
| has_nix | no |
| has_tests | yes |
| lockfiles | — |
| has_dockerfile | no |
| typed_language | yes |
| bootstrap_files | Justfile, docs/Makefile, mise.toml |
| has_devcontainer | no |
| has_linter_config | yes |
| typecheck_configs | src/ale/python/py.typed |
| agent_commit_share | 0.07 |
| toolchain_manifests | — |
| dependency_bot_commit_share | 0.22 |
| 45/45 | Type-checkable code — C++ (statically typed) |
| 55/55 | Manageable file sizes — 0/277 source files over 60KB |
| primary_language | C++ |
| largest_source_bytes | 29,723 |
| source_files_sampled | 277 |
| oversized_source_files | 0 |
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.
Each point covers 13 days.
| Registry | Package | Version constraint | Manifest |
|---|---|---|---|
| PyPI | numpy | >1.20 | pyproject.toml |
| PyPI | typing-extensions | — | pyproject.toml |
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.
| Registry | Package | Version | Relation |
|---|---|---|---|
| PyPI | numpy | — | direct |
| PyPI | typing-extensions | — | direct |
| PyPI | celshast | — | indirect |
| PyPI | gymnasium | — | indirect |
| PyPI | moviepy | — | indirect |
| PyPI | myst-parser | — | indirect |
| PyPI | pygame | — | indirect |
| PyPI | sphinx | — | indirect |
| PyPI | sphinx-autobuild | — | indirect |
| PyPI | sphinx-gallery | — | indirect |
| PyPI | sphinx-github-changelog | — | indirect |
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.
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.
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 statistics — PyPI.