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Found 1,304 Skills
Apply Model-First Reasoning (MFR) to code generation tasks. Use when the user requests "model-first", "MFR", "formal modeling before coding", "model then implement", or when tasks involve complex logic, state machines, constraint systems, or any implementation requiring formal correctness guarantees. Enforces strict separation between modeling and implementation phases.
AI 도입 전략, Build vs Buy, 우선순위 설정, 거버넌스/보안, 6개월 확장 로드맵을 다루는 모듈.
Anthropic's method for training harmless AI through self-improvement. Two-phase approach - supervised learning with self-critique/revision, then RLAIF (RL from AI Feedback). Use for safety alignment, reducing harmful outputs without human labels. Powers Claude's safety system.
Build Model Context Protocol servers and implementations. Creates protocol-compliant tools and integrations for AI-powered applications.
Fully autonomous research pipeline that turns a topic idea into a complete academic paper with real citations, experiments, and conference-ready LaTeX.
A validation framework that ensures Claude's responses are current, accurate, complete, and clear. Use this skill whenever the user asks a factual or research question, requests analysis or recommendations (e.g., "What's the best framework for X?", "Compare options for Y"), or any prompt where recency and accuracy matter. Also trigger when the user explicitly asks for validated, verified, or fact-checked answers. This skill should activate broadly — if the answer depends on facts that could have changed in the last few months, use it. Even questions that seem straightforward ("Is X still the recommended approach?") benefit from this skill's validation pipeline. Do NOT trigger for purely creative writing, casual chat, or tasks that are entirely opinion-based with no factual claims.
Provides rules for handling multi-language documentation. Use this when configuring agent skill documents using starlight-skills on an i18n-enabled project. Do not use this for standard single-language sites or plugin configuration options.
Engineer system prompts for LiveKit voice agents with multilingual support. Use when creating or optimizing AI agent conversation flows.
Intelligent system governor that continuously shadow-tests APIs for performance while enforcing strict financial and security guardrails against runaway costs.
Use when bootstrapping a new personal wiki for any knowledge domain — research, codebase documentation, reading notes, competitive analysis, or any long-term knowledge accumulation project.
Run the corpus benchmark — booster locally, optional Gemini/Sonnet/Opus baselines — and persist a verifiable measured-vs-claimed table
Systematic approach to exploring the TensorRT-LLM codebase before implementing new features or optimizations. Teaches how to discover existing infrastructure, trace code paths, and avoid reimplementing what already exists. Derived from real mistakes where ~250 lines of code were written and deleted because existing forward methods weren't discovered upfront. Use when starting any new feature, optimization, or code modification in TRT-LLM.