Orchestrate a keep/revert optimization loop for CST metamaterial tuning.
npx skills add https://github.com/DaryLu0v0/MetaClaw --skill cst-tuning-loop
Please help me install this Agent Skill. Skill: CST Tuning Loop Source: https://github.com/DaryLu0v0/MetaClaw/tree/main/skills/cst-tuning Command: npx skills add https://github.com/DaryLu0v0/MetaClaw --skill cst-tuning-loop
Automates CST tuning by orchestrating a keep/revert optimization loop: read state, propose parameter changes, validate constraints, run CST, score results, and decide to keep or revert.
Load your current design state and run the CST tuning loop to propose changes, validate constraints, execute simulations, score results, and keep or revert automatically.
High-intent search queries and answers about installing and using this skill.
Automate CST tuning by running a keep/revert optimization loop that reads state, proposes parameter changes, validates constraints, executes CST simulations, scores results, and keeps or reverts automatically.
The keep/revert optimization loop is an automated process that proposes parameter changes, runs CST simulations, scores results, and decides whether to keep new parameters or revert to previous ones.
Yes, automated CST tuning supports broadband, narrowband, and multiband targets in metamaterial designs, applying the keep/revert optimization loop across different frequency band configurations.
You need a TargetConfig, GeneralRunner, GeneralEvaluator, a CST interface, and a structured logging workflow to record version, score, parameters, changes, and decisions to results.tsv.
Yes, automated CST tuning supports topology changes, material overrides, and script-driven experiments within the auto_cst framework to explore structural variations during the optimization loop.
Automated CST tuning logs version, score, parameters, changes, and decisions to a results.tsv file, providing best-so-far tracking and seed data for downstream ML design or template generation.
Rafael-RuedaGenerate project artifacts following established patterns via the /generate command.
maslennikov-igParse npm, pnpm, TypeScript, Jest, and build logs into structured JSON reports.
bbl21Automate CST parameter tuning, simulation, and result validation via CLI commands.
ScientiaCapitalTrack experiment results and generate reusable workflow templates.
