This skill is used for directing LLM coding agents on substantial development tasks, such as establishing executable oracles or constraining output quality. It also helps systematically correct recurring quality or architecture issues in LLM-generated code.
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The exact command may vary by repository. Check the README on GitHub.
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Shows your skill is listed on Skillteca, generates a backlink and trackable traffic.
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Build, debug, and optimize Claude API / Anthropic SDK apps. Apps built with this skill should include prompt caching. Also handles migrating existing Claude API code between Claude model versions (4.5 → 4.6, 4.6 → 4.7, retired-model replacements). TRIGGER when: code imports `anthropic`/`@anthropic-ai/sdk`; user asks for the Claude API, Anthropic SDK, or Managed Agents; user adds/modifies/tunes a C
Create new skills, modify and improve existing ones, and measure their performance. Use this skill for developing, editing, optimizing, testing, and benchmarking skills, as well as refining their descriptions for better triggering.
This skill clusters GitHub issue backlogs by root cause into plan-master issues, redirects related children, and bundles architectural-fix PRs to close clusters atomically. It's ideal for triaging and consolidating numerous issues sharing underlying defects, or for building a plan series or roadmap.
Captures agent actions across sessions, compresses them with AI, and injects relevant context into future interactions. Compatible with Claude Code, OpenClaw, Codex, Gemini, Hermes, Copilot, OpenCode, and more.
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Eliminate the freedom to do the job badly. Every measurable dimension of code quality gets an executable oracle — an automated tool that programmatically validates output. Dimensions without oracles get human oversight checkpoints. No dimension is left to LLM judgment alone.
Based on John Regehr's Zero-Degree-of-Freedom LLM Coding.
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[Description truncada. Veja o README completo no GitHub.]
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