optimizer
optimizer is a Physics, mathematics & simulation skill for AI agents, published by Arcadia-1 in the virtuoso-bridge-lite repository on GitHub. Skillspace rates optimizer D (68/100) and it passed the safety scan; the rating is based on static analysis only.
Black-box optimization of design parameters using TuRBO or scipy. TRIGGER when the user wants to optimize, tune, size, sweep, or explore a design space to meet specs. This includes circuit sizing (W/L, bias, passives), finding optimal operating points, minimizing power-delay or noise-power tradeoffs, or any task where multiple parameters need to be searched to hit a target. Also trigger when the user says things like 'find the best sizing', 'help me tune this', 'run an optimization', 'what values give me the best FOM', or 'sweep these parameters to meet spec'. Do NOT trigger for single-variable parametric sweeps or analytical calculations.
- Grade
- D
- Quality
- 68 / 100
- Safety
- Passed
- GitHub stars
- 555
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
- MIT
- Adoption
- Adopted by 0 other repositories, in 0 collections
Not checked 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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