Save CST tuning results as reusable templates and score new hypotheses.
npx skills add https://github.com/DaryLu0v0/MetaClaw --skill template-library
Please help me install this Agent Skill. Skill: template-library Source: https://github.com/DaryLu0v0/MetaClaw/tree/main/skills/template-library Command: npx skills add https://github.com/DaryLu0v0/MetaClaw --skill template-library
Solves the problem of losing proven CST designs by saving them as reusable templates. The library grows with each tuned CST design, helping researchers reuse proven configurations and quickly assess new ideas.
Save a completed CST tuning result to the library, then query templates to assess readiness for a new hypothesis.
High-intent search queries and answers about installing and using this skill.
Save proven CST designs as reusable templates by storing completed tuning runs in a standardized library. The system writes target_config.json, design-best.json, and absorption data artifacts to preserve configurations for future metamaterial experimentation.
Query existing CST templates by scoring new hypotheses against the saved library index. This retrieval mechanism evaluates design readiness, guiding metamaterial design decisions by comparing new ideas against proven configurations.
You can browse saved CST templates by topology, frequency range, and performance metrics. The library provides a browseable index that accelerates exploration by filtering proven designs based on these specific structural parameters.
Saving CST tuning results requires standardized file formats including target_config.json, design-best.json, results-summary.json, and absorption data files. These artifacts ensure proven configurations are consistently stored and retrieved across projects.
Proven CST configurations are often lost after successful tuning runs without a storage mechanism. A template library solves this by capturing designs as standardized artifacts, growing with each tuned result to enable future reuse.
The CST template library supports retrieval across different projects by maintaining a browseable index of standardized artifacts. This cross-project capability allows researchers to query proven designs regardless of the original project scope.
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