calculix-sizing-optimization
calculix-sizing-optimization is a Physics, mathematics & simulation skill for AI agents, published by Cai-aa in the CAE-Agent-Hub repository on GitHub. Skillspace rates calculix-sizing-optimization D (68/100) and it passed the safety scan; the rating is based on static analysis only.
Workflow skill for two-stage sizing/parameter optimization on a CalculiX shell or beam deck via the optimize_structure tool — Latin Hypercube sweep plus coordinate descent to minimize mass subject to stress/displacement or natural-frequency constraints by tuning scalar section/material/load cards. Use when an agent must lighten a CalculiX shell or beam model while keeping stress and deflection within limits, or must thin a deck until its first modes clear a resonance floor (freq_1_hz constraint on a *FREQUENCY deck).
- Grade
- D
- Quality
- 68 / 100
- Safety
- Passed
- GitHub stars
- 889
Unproven: rated by static analysis only, not yet compared head-to-head.
Our two independent classifiers differ on this skill's category, so treat the placement as provisional.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 100 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
Not checked yet
- Category is a classifier prediction; no model has read this skill yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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