Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-10-03 23:18 UTC

instadeepai / jumanji

🕹️ A diverse suite of scalable reinforcement learning environments in JAX

PythonApache-2.0★ 865 stars⑂ 99 forkssince Aug 2022View on GitHub ↗
KindLibraryCommand-line toolhow this is determined
#jax#python#reinforcement-learning#research

instadeepai/jumanji holds a health index of 89 out of 100, placing it in the Excellent band. It scores highest on Engineering Quality (90/100) and lowest on Security (61/100). It was last updated 24 days ago. 3 contributors account for most of its recent work.

89
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.

89
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 75 is calibrated to 89 on the published index scale (record calibration 2026-08-02).

Ownership

InstaDeep LtdOrganization · verified domain
647 followers75 public repossince Feb 2018

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIjumanji1.1.27,0721564 days agojaxpythonreinforcement-learning

Metrics by category

Vitality

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

68Good · 21% of overall

Development activity

57Moderate
How it's scored
28.8/36Push recency — last push 24 days ago
6.2/36Commit cadence — 9/52 weeks with commits
11.7/18Commit volume — 19 commits in the last year
10/10OpenSSF Scorecard: Maintained — 11 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year19
human_commit_share0.96
days_since_last_push24
active_weeks_last_year9

Release discipline

84Excellent
How it's scored
27/27Ships releases — 16 releases published
36/36Release recency — latest release 64 days ago
12.6/27Release cadence — a release every ~139.4 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count16
latest_release_tagv1.1.2
releases_from_tagsno
days_since_latest_release64
mean_days_between_releases139.4
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?

68Good · 17% of overall

Popularity & adoption

70Good
How it's scored
47.6/60Stars — 865 stars
16.6/25Forks — 99 forks
5.6/15Watchers — 11 watchers
Inputs used
forks99
stars865
watchers11
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_badges6
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_servicesbadge.fury.io, github.com, shields.io
has_pull_request_templateno

Ecosystem adoption (downloads)

64Moderate
How it's scored
51.3/80Monthly downloads — 7,072 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesjumanji
dependents—
ecosystemspypi
total_downloads—
monthly_downloads7,072
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?

84Excellent · 23% of overall

Maintainer resilience (bus factor)

68Good
How it's scored
36/54Bus factor — 3 contributor(s) cover half of all commits
15.6/22.5Commit distribution — top contributor authored 31% of commits
13.5/13.5Contributor breadth — 45 contributors
3/10OpenSSF Scorecard: Contributors — project has 1 contributing companies or organizations -- score normalized to 3
Inputs used
bus_factor3
contributors_sampled45
top_contributor_share0.307

Issue & PR responsiveness

79Good
How it's scored
33.7/42Issue resolution — 80% of issues closed
24.6/30PR acceptance — 158/193 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
10.5/15OpenSSF Scorecard: Code-Review — Found 20/26 approved changesets -- score normalized to 7
Inputs used
merged_prs158
open_issues23
closed_issues93
prs_merged_7d0
prs_decided_7d0
prs_merged_30d1
prs_decided_30d1
issue_closed_ratio0.802
closed_unmerged_prs35
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

95Exceptional
How it's scored
30/30Ownership backing — organization-owned
20/20Verified domain
20.2/25Owner reach — 647 followers of instadeepai
25/25Track record — 75 public repos, account ~8 yr old
Inputs used
followers647
owner_typeOrganization
is_verifiedyes
owner_logininstadeepai
public_repos75
account_age_days3,145

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 64 days ago
20/20Version history — 15 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesjumanji
ecosystemspypi
any_deprecatedno
min_days_since_publish64

Engineering Quality

Are baseline engineering and documentation practices in place?

90Excellent · 19% of overall

Engineering practices

84Excellent
How it's scored
24/24CI workflows — 3 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff])
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
10/20OpenSSF Scorecard: CI-Tests — 17 out of 29 merged PRs checked by a CI test -- score normalized to 5
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://instadeepai.github.io/jumanji
10/10Repository description
10/10Topics — 4 topics
10/10Wiki
Inputs used
topicsjax, python, reinforcement-learning, research
has_wikiyes
homepagehttps://instadeepai.github.io/jumanji
docs_sitehttps://instadeepai.github.io/jumanji
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

61Moderate · 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
1.2/2.5CI-Tests — 17 out of 29 merged PRs checked by a CI test -- score normalized to 5
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
5.2/7.5Code-Review — Found 20/26 approved changesets -- score normalized to 7
0.8/2.5Contributors — project has 1 contributing companies or organizations -- score normalized to 3
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 — 11 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 10
0/5Packaging — no data
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
1/5SAST — SAST tool is not run on all commits -- score normalized to 2
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 — 49 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated15
scorecard_versionv5.5.0
checks_inconclusive3
scorecard_aggregate5.1
Excluded from scoring (no data or not applicable): Branch-Protection, Packaging, Signed-Releases. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisories — no direct dependency carries a known advisory
25/25Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
0/40No advisories left outstanding — no advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages46
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:jumanji@1.1.2 runtime dependency closure — what installing the published package pulls in — 46 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.

72Good · 4% of overall

Agent context & guidance

55Moderate
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://docs.ray.io/llms.txt)
40/40Legible commit history — 96 of 96 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtyes
llms_txt_urlhttps://docs.ray.io/llms.txt
legible_history_share1
agent_instruction_files—
agent_instruction_max_bytes—

Verify loop (build / test / typecheck)

70Good
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff])
11/11Static type checking — jumanji/py.typed
10/10Reproducible environment — lockfile
8/10Demonstrated agent practice — 4 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance — 4 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_files—
has_devcontainerno
has_linter_configyes
typecheck_configsjumanji/py.typed
agent_commit_share0.04
toolchain_manifests—
dependency_bot_commit_share0.04

Code legibility for models

82Excellent
How it's scored
27/45Type-checkable code — Python with type-check config (jumanji/py.typed)
55/55Manageable file sizes — 0/400 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes34,971
source_files_sampled400
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

865GitHub stars
45contributors
19commits, last 12 months
24days since last push
16releases
3bus factor
23open 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 ★ / 99 ⇿
0Stars
99Forks
16Releases

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.

0204060801009632022-082024-092026-09
Major 1Minor 3Patch 12

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 · 2026-10-03 23:17 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
5CI-Tests17 out of 29 merged PRs checked by a CI test -- score normalized to 5
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
7Code-ReviewFound 20/26 approved changesets -- score normalized to 7
3Contributorsproject has 1 contributing companies or organizations -- score normalized to 3
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained11 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 10
n/aPackagingpackaging workflow not detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
2SASTSAST tool is not run on all commits -- score normalized to 2
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0Vulnerabilities49 existing vulnerabilities detected
Direct dependencies 11
RegistryPackageVersion constraintManifest
PyPIchex>=0.1.3pyproject.toml
PyPIdm-env>=1.5pyproject.toml
PyPIesquilax>=2.0.0pyproject.toml
PyPIgymnasium>=1.0pyproject.toml
PyPIhuggingface-hub—pyproject.toml
PyPIjax>=0.4.27pyproject.toml
PyPImatplotlib>=3.8.0pyproject.toml
PyPInumpy>=1.19.5pyproject.toml
PyPIPillow>=9.0.0pyproject.toml
PyPIrequests>=2.32pyproject.toml
PyPItyping-extensions>=4.0.0pyproject.toml
All dependencies 206

Full resolved dependency set from the GitHub dependency graph: 14 direct and 192 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
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PyPItomli2.4.1indirect
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PyPItraitlets5.15.0indirect
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PyPItyper0.25.1indirect
PyPItzdata2026.2indirect
PyPIuri-template1.3.0indirect
PyPIurllib32.7.0indirect
PyPIvirtualenv21.4.2indirect
PyPIwatchdog6.0.0indirect
PyPIwcmatch10.1indirect
PyPIwcwidth0.7.0indirect
PyPIwebcolors25.10.0indirect
PyPIwebencodings0.5.1indirect
PyPIwebsocket-client1.9.0indirect
PyPIwrapt2.2.1indirect
Dependency advisories 0

Installing pypi:jumanji@1.1.2 pulls in 46 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

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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.