Guile-based library implementing flexible control files for scientific simulations
Jupyter Notebook · CGPL-2.0★ 24 stars⑂ 29 forkssince Mar 2014View on GitHub ↗
NanoComp/libctl holds a health index of 54 out of 100, placing it in the Moderate band. It scores highest on Vitality (64/100) and lowest on AI Readiness (31/100). It was last updated 19 days ago. A single contributor accounts for most of its recent work.
54
overall / 100
Moderate
Software 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.
54
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.
Direct dependencies free of known advisories — no direct dependency carries a known advisory
0/25
Indirect dependencies free of known advisories — transitive set not separable from development and test dependencies in this scope
0/40
No advisories left outstanding — no advisory carries a publication date
Inputs used
source
osv
advisories
0
affected_packages
0
assessed_packages
1
unassessed_packages
1
affected_by_severity
none
direct_affected_packages
0
Excluded from scoring (no data or not applicable): Indirect dependencies free of known advisories, No advisories left outstanding. Remaining weights renormalized. Matched 1 resolved dependencies against OSV. 1 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list. This repository publishes no package the index resolves, so the repository dependency graph was assessed instead. That graph mixes development and test pins with shipped dependencies, so only the declared runtime dependencies are scored; transitive findings are reported as context and excluded from the score. Reachability is not analyzed.
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.
Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
More detail
Star and fork history 0 ★ / 29 ⇿
0Stars
29Forks
13Releases
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 1Minor 5Patch 7
Each point covers 9 days.
OpenSSF Scorecard 3.5 / 10
3.5aggregate
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 · 2026-07-26 03:52 UTC
Full resolved dependency set from the GitHub dependency graph: 0 direct and 2 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.
Registry
Package
Version
Relation
PyPI
mkdocs
0.17.5
indirect
PyPI
python-markdown-math
—
indirect
Dependency advisories 0
This repository publishes no package the index resolves, so its own dependency graph was assessed — 1 packages, which also include development and test pins that never ship: 0 carry known advisories, of which 0 are direct. 1 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list.
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 v1.13.0, schema v0.27.0 — full methodology · metrics wiki.
