Public recordModerate
Software health reportschema 0.27.0 · metrics 1.13.0 · 2026-07-26 18:18 UTC
shader-slang / slangpy-samples
shader-slang/slangpy-samples holds a health index of 53 out of 100, placing it in the Moderate band. It scores highest on Vitality (63/100) and lowest on AI Readiness (36/100). It was last updated 2 days ago. 2 contributors account for most of its recent work.
53
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.
53
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
The Slang Shading LanguageOrganization
330 followers35 public repossince Jun 2017
This repository is backed by an organization — shared, accountable stewardship that can outlive any single maintainer.
Metrics by category
Vitality
Is the project alive — is code being written and are releases shipping?
63
Development activity
71Good
How it's scored
| 36/36 | Push recency — last push 2 days ago |
| 11.1/36 | Commit cadence — 16/52 weeks with commits |
| 14.3/18 | Commit volume — 38 commits in the last year |
| 10/10 | OpenSSF Scorecard: Maintained — 14 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10 |
Inputs used
| commits_last_year | 38 |
| human_commit_share | 0.99 |
| days_since_last_push | 2 |
| active_weeks_last_year | 16 |
Release discipline
50Moderate
How it's scored
| 16.2/27 | Ships releases — 1 version tags (no GitHub releases) |
| 16.2/36 | Release recency — latest release 227 days ago |
| 12.6/27 | Release cadence — cadence unknown (single release) |
| 0/10 | OpenSSF Scorecard: Signed-Releases — no data |
Inputs used
| releases_count | 1 |
| latest_release_tag | v0.38.1 |
| releases_from_tags | yes |
| days_since_latest_release | 227 |
| mean_days_between_releases | — |
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?
41
Popularity & adoption
30At risk
How it's scored
| 18.1/60 | Stars — 14 stars |
| 8.7/25 | Forks — 12 forks |
| 3.3/15 | Watchers — 5 watchers |
Inputs used
| forks | 12 |
| stars | 14 |
| watchers | 5 |
| growth_state | unverified |
| growth_factor_pct | 100 |
| growth_unverified_reason | no_history |
Community health
54Moderate
How it's scored
| 0/22.5 | README |
| 16.9/22.5 | License — license file present, not a recognized license |
| 18/18 | CONTRIBUTING guide |
| 13.5/13.5 | Code of conduct |
| 0/7.2 | Issue template |
| 0/6.3 | PR template |
Inputs used
| has_readme | no |
| has_license | yes |
| has_contributing | yes |
| has_issue_template | no |
| has_code_of_conduct | yes |
| has_pull_request_template | no |
Sustainability & Governance
Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?
58
Maintainer resilience (bus factor)
55Moderate
How it's scored
| 25.2/54 | Bus factor — 2 contributor(s) cover half of all commits |
| 13.5/22.5 | Commit distribution — top contributor authored 40% of commits |
| 13.5/13.5 | Contributor breadth — 17 contributors |
| 3/10 | OpenSSF Scorecard: Contributors — project has 1 contributing companies or organizations -- score normalized to 3 |
Inputs used
| bus_factor | 2 |
| contributors_sampled | 17 |
| top_contributor_share | 0.398 |
Issue & PR responsiveness
49At risk
How it's scored
| 13.4/46.8 | Issue resolution — 29% of issues closed |
| 34/38.3 | PR acceptance — 40/45 decided PRs merged |
| 1.5/15 | OpenSSF Scorecard: Code-Review — Found 4/25 approved changesets -- score normalized to 1 |
Inputs used
| merged_prs | 40 |
| open_issues | 5 |
| closed_issues | 2 |
| issue_closed_ratio | 0.286 |
| closed_unmerged_prs | 5 |
Ownership & stewardship
71Good
How it's scored
| 30/30 | Ownership backing — organization-owned |
| 0/20 | Verified domain |
| 18.1/25 | Owner reach — 330 followers of shader-slang |
| 23.3/25 | Track record — 35 public repos, account ~9 yr old |
Inputs used
| followers | 330 |
| owner_type | Organization |
| is_verified | — |
| owner_login | shader-slang |
| public_repos | 35 |
| account_age_days | 3,338 |
Engineering Quality
Are baseline engineering and documentation practices in place?
54
Engineering practices
90Excellent
How it's scored
| 24/24 | CI workflows — 2 workflow(s) |
| 24/24 | Tests present |
| 16/16 | Linter config |
| 9.6/9.6 | Pre-commit hooks |
| 0/6.4 | .editorconfig |
| 16/20 | OpenSSF Scorecard: CI-Tests — 15 out of 17 merged PRs checked by a CI test -- score normalized to 8 |
Inputs used
| has_ci | yes |
| has_tests | yes |
| has_editorconfig | no |
| has_linter_config | yes |
| has_precommit_config | yes |
Documentation
1Critical
How it's scored
| 0/30 | README |
| 0/25 | Documentation directory |
| 0/15 | Documentation / homepage site |
| 0/10 | Repository description |
| 0/10 | Topics |
| 0/10 | Wiki |
Inputs used
| topics | — |
| has_wiki | no |
| homepage | — |
| has_readme | no |
| has_docs_dir | no |
| has_description | no |
Security
Are visible security and supply-chain practices strong, without unresolved high-risk jurisdiction exposure?
41
Security posture
41At risk
How it's scored
| 7.5/7.5 | Binary-Artifacts — no binaries found in the repo |
| 0/7.5 | Branch-Protection — branch protection not enabled on development/release branches |
| 2/2.5 | CI-Tests — 15 out of 17 merged PRs checked by a CI test -- score normalized to 8 |
| 0/2.5 | CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected |
| 0.8/7.5 | Code-Review — Found 4/25 approved changesets -- score normalized to 1 |
| 0.8/2.5 | Contributors — project has 1 contributing companies or organizations -- score normalized to 3 |
| 10/10 | Dangerous-Workflow — no dangerous workflow patterns detected |
| 0/7.5 | Dependency-Update-Tool — no update tool detected |
| 0/5 | Fuzzing — project is not fuzzed |
| 2.2/2.5 | License — license file detected |
| 7.5/7.5 | Maintained — 14 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10 |
| 0/5 | Packaging — no data |
| 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 |
| 0/7.5 | Token-Permissions — detected GitHub workflow tokens with excessive permissions |
| 7.5/7.5 | Vulnerabilities — 0 existing vulnerabilities detected |
Inputs used
| source | openssf_scorecard |
| checks_evaluated | 16 |
| scorecard_version | v5.5.0 |
| checks_inconclusive | 2 |
| scorecard_aggregate | 4.1 |
Excluded from scoring (no data or not applicable): packaging, 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.
36
Agent context & guidance
22Critical
How it's scored
| 0/45 | Agent instructions — no CLAUDE.md / AGENTS.md / editor rules |
| 0/15 | Machine-readable docs (llms.txt) |
| 22.1/40 | Legible commit history — 41 of 99 human commits state their intent (structured subject or explanatory body) |
Inputs used
| has_llms_txt | no |
| legible_history_share | 0.414 |
| agent_instruction_files | — |
| agent_instruction_max_bytes | — |
How it's scored
| 0/18 | One-command bootstrap |
| 22/22 | Automated tests |
| 11/11 | Lint / format config |
| 0/11 | Static type checking |
| 0/10 | Reproducible environment |
| 4/10 | Demonstrated agent practice — 2 of the last 100 commits agent-authored or agent-credited |
| 0/8 | Automated maintenance — no automated dependency updates observed |
| 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 | no |
| bootstrap_files | — |
| has_devcontainer | no |
| has_linter_config | yes |
| typecheck_configs | — |
| agent_commit_share | 0.02 |
| toolchain_manifests | — |
| dependency_bot_commit_share | 0 |
Code legibility for models
55Moderate
How it's scored
| 0/45 | Type-checkable code — Jupyter Notebook without a type-check config |
| 55/55 | Manageable file sizes — 0/84 source files over 60KB |
Inputs used
| primary_language | Jupyter Notebook |
| largest_source_bytes | 20,875 |
| source_files_sampled | 84 |
| oversized_source_files | 0 |
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, notebooks |
Inputs used
| example_dirs | examples, notebooks |
| has_mcp_signal | no |
| api_schema_files | — |
Key facts
14GitHub stars
17contributors
38commits, last 12 months
2days since last push
1releases
2bus factor
5open issues
PyPIpackage ecosystems
Data collection warnings
- Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
- No resolved dependencies carried a version and a supported ecosystem
More detail
Star and fork history 0 ★ / 12 ⇿
0Stars
12Forks
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.
OpenSSF Scorecard 4.1 / 10
4.1aggregate
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).
| 10 | Binary-Artifacts | no binaries found in the repo |
| 0 | Branch-Protection | branch protection not enabled on development/release branches |
| 8 | CI-Tests | 15 out of 17 merged PRs checked by a CI test -- score normalized to 8 |
| 0 | CII-Best-Practices | no effort to earn an OpenSSF best practices badge detected |
| 1 | Code-Review | Found 4/25 approved changesets -- score normalized to 1 |
| 3 | Contributors | project has 1 contributing companies or organizations -- score normalized to 3 |
| 10 | Dangerous-Workflow | no dangerous workflow patterns detected |
| 0 | Dependency-Update-Tool | no update tool detected |
| 0 | Fuzzing | project is not fuzzed |
| 9 | License | license file detected |
| 10 | Maintained | 14 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10 |
| n/a | Packaging | packaging workflow not 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 |
| 0 | Token-Permissions | detected GitHub workflow tokens with excessive permissions |
| 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 | imageio | — | indirect |
| PyPI | matplotlib | — | indirect |
| PyPI | numpy | — | indirect |
| PyPI | pillow | — | indirect |
| PyPI | scipy | — | indirect |
| PyPI | slangpy | — | indirect |
| PyPI | tqdm | — | indirect |
| PyPI | trimesh | — | indirect |
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
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"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": 6
},
"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": "at_risk",
"name": "AI Readiness",
"value": 36,
"weight": 0,
"metrics": [
{
"key": "ai_agent_context",
"band": "critical",
"name": "Agent context & guidance",
"note": null,
"notes": [],
"value": 22,
"inputs": {
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"legible_history_share": 0.414,
"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": "41 of 99 human commits state their intent (structured subject or explanatory body)",
"points": 22.1,
"status": "partial",
"details": [
{
"code": "legible_history",
"params": {
"legible": 41,
"sampled": 99
}
}
],
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}
]
},
{
"key": "ai_verify_loop",
"band": "at_risk",
"name": "Verify loop (build / test / typecheck)",
"note": null,
"notes": [],
"value": 37,
"inputs": {
"has_nix": false,
"has_tests": true,
"lockfiles": [],
"has_dockerfile": false,
"typed_language": false,
"bootstrap_files": [],
"has_devcontainer": false,
"has_linter_config": true,
"typecheck_configs": [],
"agent_commit_share": 0.02,
"toolchain_manifests": [],
"dependency_bot_commit_share": 0
},
"components": [
{
"key": "one_command_bootstrap",
"name": "One-command bootstrap",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"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": null,
"points": 0,
"status": "missed",
"details": [],
"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": "2 of the last 100 commits agent-authored or agent-credited",
"points": 4,
"status": "partial",
"details": [
{
"code": "agent_authored_commits",
"params": {
"count": 2,
"sampled": 100
}
}
],
"max_points": 10
},
{
"key": "automated_maintenance",
"name": "Automated maintenance",
"detail": "no automated dependency updates observed",
"points": 0,
"status": "missed",
"details": [
{
"code": "no_dependency_automation",
"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": "moderate",
"name": "Code legibility for models",
"note": null,
"notes": [],
"value": 55,
"inputs": {
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"largest_source_bytes": 20875,
"source_files_sampled": 84,
"oversized_source_files": 0
},
"components": [
{
"key": "type_checkable_code",
"name": "Type-checkable code",
"detail": "Jupyter Notebook without a type-check config",
"points": 0,
"status": "missed",
"details": [
{
"code": "no_typecheck_config_language",
"params": {
"language": "Jupyter Notebook"
}
}
],
"max_points": 45
},
{
"key": "manageable_file_sizes",
"name": "Manageable file sizes",
"detail": "0/84 source files over 60KB",
"points": 55,
"status": "met",
"details": [
{
"code": "oversized_source_files",
"params": {
"kb": 60,
"sampled": 84,
"oversized": 0
}
}
],
"max_points": 55
}
]
},
{
"key": "ai_interfaces",
"band": "at_risk",
"name": "Machine-readable interfaces",
"note": null,
"notes": [],
"value": 40,
"inputs": {
"example_dirs": [
"examples",
"notebooks"
],
"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, notebooks",
"points": 40,
"status": "met",
"details": [
{
"code": "file_list",
"params": {
"files": "examples, notebooks"
}
}
],
"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": [
"Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token",
"No resolved dependencies carried a version and a supported ecosystem"
],
"report_type": "repository",
"generated_at": "2026-07-26T18:18:18.488764Z",
"schema_version": "0.27.0",
"badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/s/shader-slang/slangpy-samples.svg",
"full_name": "shader-slang/slangpy-samples",
"license_state": "custom",
"license_spdx": null
}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 v0.27.0 — full methodology · metrics wiki.
How one result sits in the wider record: aggregate statistics.