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Found 135 Skills
Meta-skill for improving and optimizing prompts using Anthropic's prompt engineering best practices. Provides the 4-step improvement workflow (example identification, initial draft, chain of thought refinement, example enhancement), keyword registries for documentation lookup, and decision trees for improvement strategies. Use when improving prompts, optimizing for accuracy, adding chain of thought reasoning, structuring with XML tags, enhancing examples, or iterating on prompt quality. Delegates to docs-management skill for official prompt engineering documentation.
Comprehensive guide for skill development based on Anthropic's official best practices - use for complex skills requiring detailed structure
Orchestrates end-to-end interview preparation for senior ML/AI engineers targeting Anthropic and peer companies. Use for prep timeline generation, story coherence across rounds, mock scheduling, and debrief analysis. Activate on "interview prep", "interview loop", "Anthropic interview", "prep timeline". NOT for resume writing, career narratives, or individual round-type practice.
Run an Anthropic Claude Managed Agent — a cloud agent harness (container + filesystem + tools), the cloud counterpart of the local wasm-agent runtime
Applies Anthropic's official brand colors and typography to any sort of artifact that may benefit from having Anthropic's look-and-feel. Use it when brand colors or style guidelines, visual formatting, or company design standards apply. Taken from https://github.com/anthropics/skills/blob/main/skills/brand-guidelines/SKILL.md
添加和配置第三方 API 中转站供应商到 OpenClaw。当用户需要添加新的 API 供应商、配置中转站、设置自定义模型端点时使用此技能。支持 Anthropic 兼容和 OpenAI 兼容的 API 格式。
Apply Anthropic's official brand colors and typography to artifacts for consistent visual identity and professional design standards. A reference for shaping your own.
Creates and configures Claude Code hooks for lifecycle automation. Covers all 17 hook events, 4 hook types (command, prompt, agent, http), matchers, input/output formats, and exit codes. Follows official Anthropic best practices. USE WHEN: user mentions "hook", "hooks", "auto-format", "pre tool use", "post tool use", "session start", "notification hook", "block command", "validate tool", "lifecycle event", "PostToolUse", "PreToolUse" DO NOT USE FOR: creating skills - use `skill-authoring`; creating agents - use `agent-authoring`; webhook endpoints - different concept
Answer questions about the AI SDK and help build AI-powered features. Use when developers: (1) Ask about AI SDK functions like generateText, streamText, ToolLoopAgent, embed, or tools, (2) Want to build AI agents, chatbots, RAG systems, or text generation features, (3) Have questions about AI providers (OpenAI, Anthropic, Google, etc.), streaming, tool calling, structured output, or embeddings, (4) Use React hooks like useChat or useCompletion. Triggers on: "AI SDK", "Vercel AI SDK", "generateText", "streamText", "add AI to my app", "build an agent", "tool calling", "structured output", "useChat".
Build production-ready AI workflows using Firebase Genkit. Use when creating flows, tool-calling agents, RAG pipelines, multi-agent systems, or deploying AI to Firebase/Cloud Run. Supports TypeScript, Go, and Python with Gemini, OpenAI, Anthropic, Ollama, and Vertex AI plugins.
Access Claude, Gemini, Kimi, GLM and 100+ LLMs via inference.sh CLI using OpenRouter. Models: Claude Opus 4.5, Claude Sonnet 4.5, Claude Haiku 4.5, Gemini 3 Pro, Kimi K2, GLM-4.6, Intellect 3. One API for all models with automatic fallback and cost optimization. Use for: AI assistants, code generation, reasoning, agents, chat, content generation. Triggers: claude api, openrouter, llm api, claude sonnet, claude opus, gemini api, kimi, language model, gpt alternative, anthropic api, ai model api, llm access, chat api, claude alternative, openai alternative
Framework for building LLM-powered applications with agents, chains, and RAG. Supports multiple providers (OpenAI, Anthropic, Google), 500+ integrations, ReAct agents, tool calling, memory management, and vector store retrieval. Use for building chatbots, question-answering systems, autonomous agents, or RAG applications. Best for rapid prototyping and production deployments.