Public record
Software health reportschema 0.27.0 · metrics 2.10.0 · 2026-07-23 16:07 UTC

Genesis-Embodied-AI / gs-madrona

A fork from the official Madrona. The fork will be used for Genesis's own Madrona integration.

C++MIT★ 27 stars⑂ 9 forkssince Jun 2025View on GitHub ↗

Genesis-Embodied-AI/gs-madrona holds a health index of 65 out of 100, placing it in the Good band. It scores highest on Vitality (81/100) and lowest on AI Readiness (33/100). It was last updated today. A single contributor accounts for most of its recent work.

65
overall / 100
Good

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.

65
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 60 is calibrated to 65 on the published index scale (record calibration 2026-08-02).

Ownership

Genesis AIOrganization
1,930 followers16 public repossince Oct 2023

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIgs-madrona0.0.10-130 days agorenderinggraphics3dvulkanvisualizationraytracing

Metrics by category

Vitality

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

81Excellent · 21% of overall
How it's scored
36/36Push recencylast push 0 days ago
9/36Commit cadence13/52 weeks with commits
14/18Commit volume35 commits in the last year
10/10OpenSSF Scorecard: Maintained14 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year35
human_commit_share1
days_since_last_push0
active_weeks_last_year13

Release discipline

100Exceptional
How it's scored
27/27Ships releases11 releases published
36/36Release recencylatest release 0 days ago
27/27Release cadencea release every ~39.1 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count11
latest_release_tagv0.0.10
releases_from_tagsno
days_since_latest_release0
mean_days_between_releases39.1
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?

39Weak · 17% of overall
How it's scored
23/60Stars27 stars
7.5/25Forks9 forks
0/15Watchers1 watchers
Inputs used
forks9
stars27
watchers1
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (MIT)
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_services
has_pull_request_templateno

Sustainability & Governance

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

74Good · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
7.2/22.5Commit distributiontop contributor authored 68% of commits
13.5/13.5Contributor breadth17 contributors
10/10OpenSSF Scorecard: Contributorsproject has 4 contributing companies or organizations
Inputs used
bus_factor1
contributors_sampled17
top_contributor_share0.678
How it's scored
42/42Issue resolution100% of issues closed
26.8/30PR acceptance59/66 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
4.5/15OpenSSF Scorecard: Code-ReviewFound 11/30 approved changesets -- score normalized to 3
Inputs used
merged_prs59
open_issues0
closed_issues3
prs_merged_7d
prs_decided_7d
prs_merged_30d
prs_decided_30d
issue_closed_ratio1
closed_unmerged_prs7
first_time_authors_30d
first_time_prs_merged_30d
first_time_prs_decided_30d
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
23.6/25Owner reach1,930 followers of Genesis-Embodied-AI
14.4/25Track record16 public repos, account ~2 yr old
Inputs used
followers1,930
owner_typeOrganization
is_verified
owner_loginGenesis-Embodied-AI
public_repos16
account_age_days997
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 0 days ago
20/20Version history13 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesgs-madrona
ecosystemspypi
any_deprecatedno
min_days_since_publish0

Engineering Quality

Are baseline engineering and documentation practices in place?

52Moderate · 19% of overall
How it's scored
24/24CI workflows1 workflow(s)
0/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests30 out of 30 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsno
has_editorconfigno
has_linter_configno
has_precommit_configno
How it's scored
30/30README
25/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
0/10Topics
0/10Wiki
Inputs used
topics
has_wikino
homepage
docs_site
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

52Moderate · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
3.8/7.5Branch-Protectionbranch protection is not maximal on development and all release branches
2.5/2.5CI-Tests30 out of 30 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
2.2/7.5Code-ReviewFound 11/30 approved changesets -- score normalized to 3
2.5/2.5Contributorsproject has 4 contributing companies or organizations
10/10Dangerous-Workflowno dangerous workflow patterns detected
0/7.5Dependency-Update-Toolno update tool detected
0/5Fuzzingproject is not fuzzed
2.5/2.5Licenselicense file detected
7.5/7.5Maintained14 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
5/5Packagingpackaging workflow detected
0/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0/5SASTSAST tool is not run on all commits -- score normalized to 0
0/5Security-Policysecurity policy file not detected
0/7.5Signed-Releasesno data
0/7.5Token-Permissionsdetected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate5.2
Excluded from scoring (no data or not applicable): Signed-Releases. Remaining weights renormalized.

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.

33At Risk · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
26.7/40Legible commit history50 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.5
agent_instruction_files
agent_instruction_max_bytes
How it's scored
0/18One-command bootstrap
0/22Automated tests
0/11Lint / format config
11/11Static type checkingC++ (statically typed)
0/10Reproducible environment
2/10Demonstrated agent practice1 of the last 100 commits agent-authored or agent-credited
0/8Automated maintenanceno automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsno
lockfiles
has_dockerfileno
typed_languageyes
bootstrap_files
has_devcontainerno
has_linter_configno
typecheck_configs
agent_commit_share0.01
toolchain_manifests
dependency_bot_commit_share0
How it's scored
45/45Type-checkable codeC++ (statically typed)
54/55Manageable file sizes3/164 source files over 60KB
Inputs used
primary_languageC++
largest_source_bytes101,946
source_files_sampled164
oversized_source_files3

Key facts

27GitHub stars
17contributors
35commits, last 12 months
0days since last push
11releases
1bus factor
0open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • deps.dev does not index pypi:gs-madrona@0.0.10; advisories assessed against the repository dependency graph instead
  • No resolved dependencies carried a version and a supported ecosystem

More detail

Star and fork history 0 ★ / 9 ⇿
0Stars
9Forks
8Releases

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.

0246810912025-072026-012026-07
Major 0Minor 0Patch 5
OpenSSF Scorecard 5.2 / 10
5.2aggregate

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 · 2026-07-23 16:06 UTC

10Binary-Artifactsno binaries found in the repo
5Branch-Protectionbranch protection is not maximal on development and all release branches
10CI-Tests30 out of 30 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
3Code-ReviewFound 11/30 approved changesets -- score normalized to 3
10Contributorsproject has 4 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained14 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
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
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 2
RegistryPackageVersion constraintManifest
PyPInvidia-cuda-nvrtc-cu12>=12.8pyproject.toml
PyPInvidia-nvjitlink-cu12>=12.8pyproject.toml
All dependencies 5

Full resolved dependency set from the GitHub dependency graph: 2 direct and 3 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPInvidia-cuda-nvrtc-cu12direct
PyPInvidia-nvjitlink-cu12direct
PyPInanobindindirect
PyPIscikit-build-coreindirect
PyPIsetuptools-scmindirect
Dependency advisories not assessed

Advisory matching could not run for this report: No resolved dependencies carried a version and a supported ecosystem

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 v0.27.0 — full methodology · metrics wiki.

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