Public recordExcellent
Software health reportschema 0.12.0 · metrics 1.13.0 · 2026-07-18 13:54 UTC
ml-explore / mlx
MLX: An array framework for Apple silicon
ml-explore/mlx holds a health index of 89 out of 100, placing it in the Excellent band. It scores highest on Vitality (100/100) and lowest on AI Readiness (51/100). It was last updated today. 3 contributors account for most of its recent work.
89
overall / 100Software health index
Metrics are grouped into weighted categories on one standardized 1–100 scale. Overall starts as their weighted mean; when public evidence triggers the High-Risk Jurisdiction Policy, the rating is adjusted and receives an At risk ceiling of 49. AI Readiness sits outside the overall score.
89
Excellent85-100Exemplary; meets essentially all checked criteria
Good70-84Healthy; minor gaps
Moderate50-69Acceptable with notable gaps; review recommended
At risk30-49Significant weaknesses; adoption warrants caution
Critical1-29Severe problems (abandoned, single-maintainer, no hygiene)
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.
Ownership
ml-exploreOrganization
5,148 followers10 public repossince Apr 2022
This repository is backed by an organization — shared, accountable stewardship that can outlive any single maintainer.
Package ecosystems
| Registry | Package | Version | Downloads / mo | Versions | Last publish |
|---|---|---|---|---|---|
| PyPI | mlx | 0.32.0 | - | 56 | 10 days ago |
Metrics by category
Vitality
Is the project alive — is code being written and are releases shipping?
100
Development activity
100Excellent
How it's scored
| 36/36 | Push recency — last push 0 days ago |
| 36/36 | Commit cadence — 52/52 weeks with commits |
| 18/18 | Commit volume — 703 commits in the last year |
| 10/10 | OpenSSF Scorecard: Maintained — 30 commit(s) and 5 issue activity found in the last 90 days -- score normalized to 10 |
Inputs used
| commits_last_year | 703 |
| human_commit_share | — |
| days_since_last_push | 0 |
| active_weeks_last_year | 52 |
Release discipline
100Excellent
How it's scored
| 27/27 | Ships releases — 74 releases published |
| 36/36 | Release recency — latest release 10 days ago |
| 27/27 | Release cadence — a release every ~25.6 days |
| 0/10 | OpenSSF Scorecard: Signed-Releases — no data |
Inputs used
| releases_count | 74 |
| latest_release_tag | v0.32.0 |
| releases_from_tags | no |
| days_since_latest_release | 10 |
| mean_days_between_releases | 25.6 |
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?
95
Popularity & adoption
98Excellent
How it's scored
| 60/60 | Stars — 27,591 stars |
| 25/25 | Forks — 2,018 forks |
| 12.8/15 | Watchers — 202 watchers |
Inputs used
| forks | 2,018 |
| stars | 27,591 |
| watchers | 202 |
| growth_state | unverified |
| growth_factor_pct | 100 |
| growth_unverified_reason | no_history |
Community health
92Excellent
How it's scored
| 22.5/22.5 | README |
| 22.5/22.5 | License — recognized license (MIT) |
| 18/18 | CONTRIBUTING guide |
| 13.5/13.5 | Code of conduct |
| 0/7.2 | Issue template |
| 6.3/6.3 | PR template |
Inputs used
| has_readme | yes |
| has_license | yes |
| has_contributing | yes |
| has_issue_template | no |
| has_code_of_conduct | yes |
| has_pull_request_template | yes |
Sustainability & Governance
Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?
83
How it's scored
| 36/54 | Bus factor — 3 contributor(s) cover half of all commits |
| 16.7/22.5 | Commit distribution — top contributor authored 26% of commits |
| 13.5/13.5 | Contributor breadth — 100 contributors |
| 10/10 | OpenSSF Scorecard: Contributors — project has 22 contributing companies or organizations |
Inputs used
| bus_factor | 3 |
| contributors_sampled | 100 |
| top_contributor_share | 0.259 |
Issue & PR responsiveness
88Excellent
How it's scored
| 42.9/46.8 | Issue resolution — 92% of issues closed |
| 31.8/38.3 | PR acceptance — 1,958/2,353 decided PRs merged |
| 13.5/15 | OpenSSF Scorecard: Code-Review — Found 29/30 approved changesets -- score normalized to 9 |
Inputs used
| merged_prs | 1,958 |
| open_issues | 96 |
| closed_issues | 1,067 |
| issue_closed_ratio | 0.917 |
| closed_unmerged_prs | 395 |
Ownership & stewardship
71Good
How it's scored
| 30/30 | Ownership backing — organization-owned |
| 0/20 | Verified domain |
| 25/25 | Owner reach — 5,148 followers of ml-explore |
| 16.2/25 | Track record — 10 public repos, account ~4 yr old |
Inputs used
| followers | 5,148 |
| owner_type | Organization |
| is_verified | — |
| owner_login | ml-explore |
| public_repos | 10 |
| account_age_days | 1,568 |
Package maintenance
100Excellent
How it's scored
| 25/25 | Published & resolvable — 1 package(s) on pypi |
| 35/35 | Publish recency — latest publish 10 days ago |
| 20/20 | Version history — 56 published versions |
| 20/20 | Not deprecated — active, not deprecated or yanked |
Inputs used
| packages | mlx |
| ecosystems | pypi |
| any_deprecated | no |
| min_days_since_publish | 10 |
Engineering Quality
Are baseline engineering and documentation practices in place?
92
Engineering practices
94Excellent
How it's scored
| 24/24 | CI workflows — 3 workflow(s) |
| 24/24 | Tests present |
| 16/16 | Linter config |
| 9.6/9.6 | Pre-commit hooks |
| 0/6.4 | .editorconfig |
| 20/20 | OpenSSF Scorecard: CI-Tests — 29 out of 29 merged PRs checked by a CI test -- score normalized to 10 |
Inputs used
| has_ci | yes |
| has_tests | yes |
| has_editorconfig | no |
| has_linter_config | yes |
| has_precommit_config | yes |
Documentation
90Excellent
How it's scored
| 30/30 | README |
| 25/25 | Documentation directory |
| 15/15 | Documentation / homepage site — https://ml-explore.github.io/mlx/ |
| 10/10 | Repository description |
| 10/10 | Topics — 1 topics |
| 0/10 | Wiki |
Inputs used
| topics | mlx |
| has_wiki | no |
| homepage | https://ml-explore.github.io/mlx/ |
| has_readme | yes |
| has_docs_dir | yes |
| has_description | yes |
Security
Are visible security and supply-chain practices strong, without unresolved high-risk jurisdiction exposure?
72
Security posture
72Good
How it's scored
| 7.5/7.5 | Binary-Artifacts — no binaries found in the repo |
| 3.8/7.5 | Branch-Protection — branch protection is not maximal on development and all release branches |
| 2.5/2.5 | CI-Tests — 29 out of 29 merged PRs checked by a CI test -- score normalized to 10 |
| 0/2.5 | CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected |
| 6.8/7.5 | Code-Review — Found 29/30 approved changesets -- score normalized to 9 |
| 2.5/2.5 | Contributors — project has 22 contributing companies or organizations |
| 10/10 | Dangerous-Workflow — no dangerous workflow patterns detected |
| 7.5/7.5 | Dependency-Update-Tool — update tool detected |
| 0/5 | Fuzzing — project is not fuzzed |
| 2.5/2.5 | License — license file detected |
| 7.5/7.5 | Maintained — 30 commit(s) and 5 issue activity found in the last 90 days -- score normalized to 10 |
| 5/5 | Packaging — packaging workflow detected |
| 0/5 | Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0 |
| 0/5 | SAST — SAST tool is not run on all commits -- score normalized to 0 |
| 0/5 | Security-Policy — security policy file not detected |
| 0/7.5 | Signed-Releases — no data |
| 7.5/7.5 | Token-Permissions — GitHub workflow tokens follow principle of least privilege |
| 7.5/7.5 | Vulnerabilities — 0 existing vulnerabilities detected |
Inputs used
| source | openssf_scorecard |
| checks_evaluated | 17 |
| scorecard_version | v5.5.0 |
| checks_inconclusive | 1 |
| scorecard_aggregate | 7.2 |
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? An independent, experimental badge — weight 0.0, so it is surfaced on its own and does not affect the overall health score.
51
Agent context & guidance
1Critical
How it's scored
| 0/45 | Agent instructions — no CLAUDE.md / AGENTS.md / editor rules |
| 0/15 | Machine-readable docs (llms.txt) |
| 0/40 | Legible commit history — no data |
Inputs used
| has_llms_txt | no |
| legible_history_share | — |
| agent_instruction_files | — |
| agent_instruction_max_bytes | — |
Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.
How it's scored
| 18/18 | One-command bootstrap — docs/Makefile |
| 22/22 | Automated tests |
| 11/11 | Lint / format config |
| 11/11 | Static type checking — python/mlx/py.typed |
| 0/10 | Reproducible environment |
| 0/10 | Demonstrated agent practice — no data |
| 5/8 | Automated maintenance — dependency automation configured, none observed in the sampled commits |
| 0/10 | OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0 |
Inputs used
| has_nix | no |
| has_tests | yes |
| lockfiles | — |
| has_dockerfile | no |
| typed_language | yes |
| bootstrap_files | docs/Makefile |
| has_devcontainer | no |
| has_linter_config | yes |
| typecheck_configs | python/mlx/py.typed |
| agent_commit_share | — |
| toolchain_manifests | — |
| dependency_bot_commit_share | 0 |
Excluded from scoring (no data or not applicable): Demonstrated agent practice. Remaining weights renormalized.
Code legibility for models
99Excellent
How it's scored
| 45/45 | Type-checkable code — C++ (statically typed) |
| 53.9/55 | Manageable file sizes — 12/590 source files over 60KB |
Inputs used
| primary_language | C++ |
| largest_source_bytes | 210,479 |
| source_files_sampled | 590 |
| oversized_source_files | 12 |
Machine-readable interfaces
40At risk
How it's scored
| 0/40 | API schema (OpenAPI/GraphQL/proto) |
| 0/20 | MCP server |
| 40/40 | Runnable examples — examples |
Inputs used
| example_dirs | examples |
| has_mcp_signal | no |
| api_schema_files | — |
Key facts
27,591GitHub stars
100contributors
703commits, last 12 months
0days since last push
74releases
3bus factor
96open issues
PyPIpackage ecosystems
More detail
OpenSSF Scorecard 7.2 / 10
7.2aggregate
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).
| 10 | Binary-Artifacts | no binaries found in the repo |
| 5 | Branch-Protection | branch protection is not maximal on development and all release branches |
| 10 | CI-Tests | 29 out of 29 merged PRs checked by a CI test -- score normalized to 10 |
| 0 | CII-Best-Practices | no effort to earn an OpenSSF best practices badge detected |
| 9 | Code-Review | Found 29/30 approved changesets -- score normalized to 9 |
| 10 | Contributors | project has 22 contributing companies or organizations |
| 10 | Dangerous-Workflow | no dangerous workflow patterns detected |
| 10 | Dependency-Update-Tool | update tool detected |
| 0 | Fuzzing | project is not fuzzed |
| 10 | License | license file detected |
| 10 | Maintained | 30 commit(s) and 5 issue activity found in the last 90 days -- score normalized to 10 |
| 10 | Packaging | packaging workflow detected |
| 0 | Pinned-Dependencies | dependency not pinned by hash detected -- score normalized to 0 |
| 0 | SAST | SAST tool is not run on all commits -- score normalized to 0 |
| 0 | Security-Policy | security policy file not detected |
| n/a | Signed-Releases | no releases found |
| 10 | Token-Permissions | GitHub workflow tokens follow principle of least privilege |
| 10 | Vulnerabilities | 0 existing vulnerabilities detected |
All dependencies 8
Full resolved dependency set from the GitHub dependency graph: 0 direct and 8 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.
| Registry | Package | Version | Relation |
|---|---|---|---|
| PyPI | breathe | — | indirect |
| PyPI | cmake | — | indirect |
| PyPI | mlx | — | indirect |
| PyPI | nanobind | 2.13.0 | indirect |
| PyPI | setuptools | — | indirect |
| PyPI | sphinx | — | indirect |
| PyPI | sphinx-book-theme | — | indirect |
| PyPI | sphinx-copybutton | — | indirect |
Raw JSON report machine-readable
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{
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{
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},
{
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{
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{
"name": "License",
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"documentation_url": "https://github.com/ossf/scorecard/blob/c395761df6afe1a69e476bc60a013a94bcbc153f/docs/checks.md#license"
},
{
"name": "Maintained",
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"documentation_url": "https://github.com/ossf/scorecard/blob/c395761df6afe1a69e476bc60a013a94bcbc153f/docs/checks.md#maintained"
},
{
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"documentation_url": "https://github.com/ossf/scorecard/blob/c395761df6afe1a69e476bc60a013a94bcbc153f/docs/checks.md#packaging"
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{
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{
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"detail": "security policy file not detected",
"points": 0,
"status": "missed",
"details": [],
"max_points": 5
},
{
"key": "signed_releases",
"name": "Signed-Releases",
"detail": "no releases found",
"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
"max_points": 7.5
},
{
"key": "token_permissions",
"name": "Token-Permissions",
"detail": "GitHub workflow tokens follow principle of least privilege",
"points": 7.5,
"status": "met",
"details": [],
"max_points": 7.5
},
{
"key": "vulnerabilities",
"name": "Vulnerabilities",
"detail": "0 existing vulnerabilities detected",
"points": 7.5,
"status": "met",
"details": [],
"max_points": 7.5
}
]
},
{
"key": "high_risk_jurisdiction_exposure",
"band": "excellent",
"name": "High-Risk Jurisdiction Exposure",
"note": "Only high-confidence self-published location evidence affects this multiplier. Ambiguous matches are review-only; country evidence is not proof of nationality, citizenship, legal registration, malicious intent, or sanctions status.",
"notes": [
{
"code": "jurisdiction_evidence_limits",
"params": {}
}
],
"value": 100,
"inputs": {
"meaning": "self-published location evidence; not nationality or citizenship",
"red_flag": false,
"exposures": [],
"policy_countries": [
"Russia",
"Iran",
"North Korea"
],
"review_only_matches": 0,
"assessed_self_published_locations": 7
},
"components": [
{
"key": "policy_exposure_multiplier",
"name": "Policy exposure multiplier",
"detail": "no confirmed policy-scope location match",
"points": 100,
"status": "met",
"details": [
{
"code": "jurisdiction_no_match",
"params": {}
}
],
"max_points": 100
}
]
}
],
"description": "Are visible security and supply-chain practices strong, with no malicious dependency and no unresolved high-risk jurisdiction exposure?"
},
{
"key": "ai_readiness",
"band": "moderate",
"name": "AI Readiness",
"value": 51,
"weight": 0,
"metrics": [
{
"key": "ai_agent_context",
"band": "critical",
"name": "Agent context & guidance",
"note": "Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.",
"notes": [
{
"code": "excluded_no_data",
"params": {
"components": [
"legible_commit_history"
]
}
},
{
"code": "weights_renormalized",
"params": {}
}
],
"value": 1,
"inputs": {
"has_llms_txt": false,
"legible_history_share": null,
"agent_instruction_files": [],
"agent_instruction_max_bytes": null
},
"components": [
{
"key": "agent_instructions",
"name": "Agent instructions",
"detail": "no CLAUDE.md / AGENTS.md / editor rules",
"points": 0,
"status": "missed",
"details": [
{
"code": "no_agent_instructions",
"params": {}
}
],
"max_points": 45
},
{
"key": "machine_readable_docs_llms_txt",
"name": "Machine-readable docs (llms.txt)",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 15
},
{
"key": "legible_commit_history",
"name": "Legible commit history",
"detail": "no data",
"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
"max_points": 40
}
]
},
{
"key": "ai_verify_loop",
"band": "good",
"name": "Verify loop (build / test / typecheck)",
"note": "Excluded from scoring (no data or not applicable): Demonstrated agent practice. Remaining weights renormalized.",
"notes": [
{
"code": "excluded_no_data",
"params": {
"components": [
"demonstrated_agent_practice"
]
}
},
{
"code": "weights_renormalized",
"params": {}
}
],
"value": 74,
"inputs": {
"has_nix": false,
"has_tests": true,
"lockfiles": [],
"has_dockerfile": false,
"typed_language": true,
"bootstrap_files": [
"docs/Makefile"
],
"has_devcontainer": false,
"has_linter_config": true,
"typecheck_configs": [
"python/mlx/py.typed"
],
"agent_commit_share": null,
"toolchain_manifests": [],
"dependency_bot_commit_share": 0
},
"components": [
{
"key": "one_command_bootstrap",
"name": "One-command bootstrap",
"detail": "docs/Makefile",
"points": 18,
"status": "met",
"details": [
{
"code": "file_list",
"params": {
"files": "docs/Makefile"
}
}
],
"max_points": 18
},
{
"key": "automated_tests",
"name": "Automated tests",
"detail": null,
"points": 22,
"status": "met",
"details": [],
"max_points": 22
},
{
"key": "lint_format_config",
"name": "Lint / format config",
"detail": null,
"points": 11,
"status": "met",
"details": [],
"max_points": 11
},
{
"key": "static_type_checking",
"name": "Static type checking",
"detail": "python/mlx/py.typed",
"points": 11,
"status": "met",
"details": [
{
"code": "file_list",
"params": {
"files": "python/mlx/py.typed"
}
}
],
"max_points": 11
},
{
"key": "reproducible_environment",
"name": "Reproducible environment",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 10
},
{
"key": "demonstrated_agent_practice",
"name": "Demonstrated agent practice",
"detail": "no data",
"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
"max_points": 10
},
{
"key": "automated_maintenance",
"name": "Automated maintenance",
"detail": "dependency automation configured, none observed in the sampled commits",
"points": 5,
"status": "partial",
"details": [
{
"code": "dependency_bot_config_only",
"params": {}
}
],
"max_points": 8
},
{
"key": "openssf_scorecard_pinned_dependencies",
"name": "OpenSSF Scorecard: Pinned-Dependencies",
"detail": "dependency not pinned by hash detected -- score normalized to 0",
"points": 0,
"status": "missed",
"details": [],
"max_points": 10
}
]
},
{
"key": "ai_code_legibility",
"band": "excellent",
"name": "Code legibility for models",
"note": null,
"notes": [],
"value": 99,
"inputs": {
"primary_language": "C++",
"largest_source_bytes": 210479,
"source_files_sampled": 590,
"oversized_source_files": 12
},
"components": [
{
"key": "type_checkable_code",
"name": "Type-checkable code",
"detail": "C++ (statically typed)",
"points": 45,
"status": "met",
"details": [
{
"code": "statically_typed_language",
"params": {
"language": "C++"
}
}
],
"max_points": 45
},
{
"key": "manageable_file_sizes",
"name": "Manageable file sizes",
"detail": "12/590 source files over 60KB",
"points": 53.9,
"status": "partial",
"details": [
{
"code": "oversized_source_files",
"params": {
"kb": 60,
"sampled": 590,
"oversized": 12
}
}
],
"max_points": 55
}
]
},
{
"key": "ai_interfaces",
"band": "at_risk",
"name": "Machine-readable interfaces",
"note": null,
"notes": [],
"value": 40,
"inputs": {
"example_dirs": [
"examples"
],
"has_mcp_signal": false,
"api_schema_files": []
},
"components": [
{
"key": "api_schema_openapi_graphql_proto",
"name": "API schema (OpenAPI/GraphQL/proto)",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 40
},
{
"key": "mcp_server",
"name": "MCP server",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 20
},
{
"key": "runnable_examples",
"name": "Runnable examples",
"detail": "examples",
"points": 40,
"status": "met",
"details": [
{
"code": "file_list",
"params": {
"files": "examples"
}
}
],
"max_points": 40
}
]
}
],
"description": "How well is the repo equipped to be developed and maintained with AI coding agents? An independent, experimental badge — weight 0.0, so it is surfaced on its own and does not affect the overall health score."
}
],
"metrics_version": "1.13.0"
},
"warnings": [],
"report_type": "repository",
"generated_at": "2026-07-18T13:54:59.641051Z",
"schema_version": "0.12.0",
"badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/m/ml-explore/mlx.svg",
"full_name": "ml-explore/mlx",
"license_state": "standard",
"license_spdx": "MIT"
}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 v1.13.0, schema v0.12.0 — full methodology · metrics wiki.
How one result sits in the wider record: aggregate statistics — PyPI.