shader-slang/slangpy holds a health index of 91 out of 100, placing it in the Excellent band. It scores highest on Vitality (93/100) and lowest on Security (58/100). It was last updated today. 2 contributors account for most of its recent work.
91
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.
91
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)
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 77 is calibrated to 91 on the published index scale (record calibration 2026-08-02).
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
Inputs used
source
osv
advisories
0
affected_packages
0
assessed_packages
2
unassessed_packages
0
affected_by_severity
none
direct_affected_packages
0
Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:slangpy@0.43.1 runtime dependency closure — what installing the published package pulls in — 2 packages. Reachability is not analyzed.
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.
Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
More detail
Star and fork history 0 ★ / 43 ⇿
0Stars
43Forks
3Releases
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.
Major 0Minor 0Patch 3
Each point covers 2 days.
OpenSSF Scorecard 4.7 / 10
4.7aggregate
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 · 2026-07-24 10:54 UTC
Full resolved dependency set from the GitHub dependency graph: 2 direct and 19 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
autoflake
—
indirect
PyPI
cmake
3.31.6
indirect
PyPI
deepdiff
—
indirect
PyPI
furo
—
indirect
PyPI
imageio
—
indirect
PyPI
isort
—
indirect
PyPI
libcst
—
indirect
PyPI
nbsphinx
—
indirect
PyPI
pandoc
—
indirect
PyPI
pre-commit
—
indirect
PyPI
pymongo
—
indirect
PyPI
pyright
—
indirect
PyPI
pytest
—
indirect
PyPI
pytest-cov
—
indirect
PyPI
pytest-xdist
—
indirect
PyPI
setuptools
—
indirect
PyPI
slangpy-torch
0.7.0
indirect
PyPI
sphinx
—
indirect
PyPI
sphinx-copybutton
—
indirect
Dependency advisories 0
Installing pypi:slangpy@0.43.1 pulls in 2 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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"headline": "Change windows workflow to bridge (#1022)",
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"headline": "tweak workflow (#1021)",
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"headline": "test-workflow (#1020)",
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"headline": "Add device callbacks and recording ids (#1018)",
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"headline": "Add platform::set_current_thread_name (#1017)",
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"headline": "Downgrade slang to version 2026.5.2 (#1016)",
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"headline": "Add compilation reports API (#1015)",
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"headline": "Update slang to version 2026.10.2 (#1012)",
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"headline": "Add SGL_LOCAL_RHI cmake option to use a local slang-rhi checkout (#999)",
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"headline": "Native conversion (#989)",
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"headline": "Update slang-rhi (#988)",
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"headline": "Test format acknowledgement (#985)",
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"body": "* Test pre-commit failure comment\n\n* Apply automatic formatting\n\n* Post quick acknowledgement for format command\n\n---------\n\nCo-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>",
"is_bot": false,
"headline": "Test pre-commit failure comment (#984)",
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"headline": "Test remote formatting command (#982)",
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"headline": "Update slang-rhi, expose new callbacks+features lists (#973)",
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"body": "Mirrors shader-slang/slang's CodeRabbit config, adapted for slangpy:\ndisables PR description rewrites, auto-titles, poems, and unwanted\nfinishing touches; tunes path_instructions and tools for slangpy's\nPython + pybind11/C++ layout.\n\nCloses #912.",
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"headline": "Improve SHA1 performance (#971)",
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"headline": "Add ASTC format support to the format enumeration and info table (#953)",
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"body": "…age (#937)\n\nnp.flipud returns a view with negative strides, which copy_from_numpy\nrejects. Ensure the returned array is always C-contiguous.\n\nRelates to #928\n\nMade-with: Cursor\n\nCo-authored-by: Jay Kwak <82421531+jkwak-work@users.noreply.github.com>",
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"headline": "Fix flip_y producing non-contiguous array in load_buffer_data_from_im…",
"author_name": "James Helferty (NVIDIA)",
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"body": "…#858)\n\n* Expose low-level ImGui draw-data rendering in slangpy UI\n\n* Exclude imgui_bundle example from pyright type checking\n\n* Apply pre-commit formatting (black + clang-format)\n\n* Forward slangpy events to imgui_bundle.\n\n* Fix external ImGui texture and draw-data handling\n\n* Fix imgui_bundle font\n[…]\n* Refactor UI end_frame draw data path\n\n* Simplify example\n\n* Move texture registry to python\n\n* Use native ImDrawData\n\n* Clang build fix\n\n---------\n\nCo-authored-by: ccummingsNV <ccummings@nvidia.com>",
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"headline": "Add external ImGui draw data rendering and imgui_bundle integration (…",
"author_name": "Mykhailo Moroz",
"author_login": "MichaelMoroz",
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"oid": "e65840a0e80c5b625e7a416dc5f38ec852cb1f50",
"body": "* done\n\n* add tests\n\n* rename test\n\n* format\n\n---------\n\nCo-authored-by: ccummingsNV <ccummings@nvidia.com>",
"is_bot": false,
"headline": "Cursor: read ptrs as uint (#817)",
"author_name": "Lukas Lipp",
"author_login": "fknfilewalker",
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"body_truncated": false,
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"body": null,
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"headline": "Replace Slang address-of operator `&` usage with `__getAddress` (#955)",
"author_name": "aidanfnv",
"author_login": "aidanfnv",
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{
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}
],
"max_points": 60
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{
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},
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"note": null,
"notes": [],
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"readme_badges": null,
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{
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"code": "license_custom",
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{
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},
{
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{
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"points": 51.2,
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"count": 6931,
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}
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{
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"value": 72,
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{
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"details": [
{
"code": "top_contributor_share",
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}
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{
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{
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"status": "partial",
"details": [],
"max_points": 10
}
]
},
{
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"notes": [
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{
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"components": [
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"points": 28.1,
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"details": [
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"code": "issues_closed_share",
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}
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{
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{
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{
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]
},
{
"key": "stewardship",
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"components": [
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{
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{
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{
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],
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{
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{
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{
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]
},
{
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],
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{
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{
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{
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},
{
"key": "dependency_update_tool",
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"points": 0,
"status": "missed",
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},
{
"key": "fuzzing",
"name": "Fuzzing",
"detail": "project is not fuzzed",
"points": 0,
"status": "missed",
"details": [],
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},
{
"key": "license",
"name": "License",
"detail": "license file detected",
"points": 2.2,
"status": "partial",
"details": [],
"max_points": 2.5
},
{
"key": "maintained",
"name": "Maintained",
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"points": 7.5,
"status": "met",
"details": [],
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},
{
"key": "packaging",
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"points": 5,
"status": "met",
"details": [],
"max_points": 5
},
{
"key": "pinned_dependencies",
"name": "Pinned-Dependencies",
"detail": "dependency not pinned by hash detected -- score normalized to 0",
"points": 0,
"status": "missed",
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},
{
"key": "sast",
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"points": 0,
"status": "missed",
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},
{
"key": "security_policy",
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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": "Project has not signed or included provenance with any releases.",
"points": 0,
"status": "missed",
"details": [],
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},
{
"key": "token_permissions",
"name": "Token-Permissions",
"detail": "detected GitHub workflow tokens with excessive permissions",
"points": 0,
"status": "missed",
"details": [],
"max_points": 7.5
},
{
"key": "vulnerabilities",
"name": "Vulnerabilities",
"detail": "2 existing vulnerabilities detected",
"points": 6,
"status": "partial",
"details": [],
"max_points": 7.5
}
]
},
{
"key": "dependency_advisories",
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"note": "Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:slangpy@0.43.1 runtime dependency closure — what installing the published package pulls in — 2 packages. Reachability is not analyzed.",
"notes": [
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"code": "excluded_no_data",
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},
{
"code": "weights_renormalized",
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{
"code": "advisories_scope_published",
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},
{
"code": "advisories_reachability",
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],
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"inputs": {
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"affected_by_severity": "none",
"direct_affected_packages": 0
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"components": [
{
"key": "direct_dependencies_free_of_known_advisories",
"name": "Direct dependencies free of known advisories",
"detail": "no direct dependency carries a known advisory",
"points": 35,
"status": "met",
"details": [
{
"code": "no_direct_advisories",
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}
],
"max_points": 35
},
{
"key": "indirect_dependencies_free_of_known_advisories",
"name": "Indirect dependencies free of known advisories",
"detail": "no indirect dependency carries a known advisory",
"points": 25,
"status": "met",
"details": [
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"code": "no_indirect_advisories",
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}
],
"max_points": 25
},
{
"key": "no_advisories_left_outstanding",
"name": "No advisories left outstanding",
"detail": "no advisory carries a publication date",
"points": 0,
"status": "excluded",
"details": [
{
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}
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},
{
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"notes": [
{
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"status": "met",
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}
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{
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"metrics": [
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"note": null,
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{
"key": "legible_commit_history",
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"points": 40,
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"note": null,
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"details": [],
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{
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"points": 22,
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{
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{
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"points": 0,
"status": "missed",
"details": [],
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{
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"sampled": 100
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"points": 0,
"status": "missed",
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"params": {}
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],
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{
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{
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"points": 53.3,
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{
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"description": "How well is the repo equipped to be developed and maintained with AI coding agents? Carries a deliberately small weight: agent tooling is a real maintenance signal, but its absence must never gate the top of the scale (calibration saturates at raw 91, so 100/100 remains reachable with AI Readiness at zero)."
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"warnings": [
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],
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"generated_at": "2026-07-24T10:54:36.290227Z",
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}
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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 v2.5.0, schema v0.27.0 — full methodology · metrics wiki.
