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Found 731 Skills
Integrate Claude Agent SDK with You.com HTTP MCP server for Python and TypeScript. Use when developer mentions Claude Agent SDK, Anthropic Agent SDK, or integrating Claude with MCP tools.
Validate and optimize CLAUDE.md files using Anthropic's best practices for focused sessions. Detects contradictions, redundancy, excessive length (200+ lines), emphasis overuse (2%+ density), broken links, and orphaned sections. Scores health 0-50 points. Suggests safe automated fixes and extraction opportunities. Use when editing CLAUDE.md, before commits, when document grows past 200 lines, user says "optimize CLAUDE.md", "check contradictions", "validate documentation", or during quarterly reviews. Works with project and global CLAUDE.md files (.md extension). Based on Anthropic 2025 context engineering best practices.
Build AI agents with in-process agent loops using Anthropic or OpenAI APIs, custom tools, MCP servers, and multi-turn conversations
Converts any Claude Code skills repository into an official plugin marketplace. Analyzes existing skills, generates .claude-plugin/marketplace.json conforming to the Anthropic spec, validates with `claude plugin validate`, tests real installation, and creates a PR to the upstream repo. Encodes hard-won anti-patterns from real marketplace development (schema traps, version semantics, description pitfalls). Use when the user mentions: marketplace, plugin support, one-click install, marketplace.json, plugin distribution, auto-update, or wants a skills repo installable via `claude plugin install`. Also trigger when the user has a skills repo and asks about packaging, distribution, or making it installable.
Edit opencode.json, AGENTS.md, and config files. Use proactively for provider setup, permission changes, model config, formatter rules, or environment variables. Examples: - user: "Add Anthropic as a provider" → edit opencode.json providers, add API key baseEnv var, verify with opencode run test - user: "Restrict this agent's permissions" → add permission block to agent config, set deny/allow for tools/fileAccess - user: "Set GPT-5 as default model" → edit global or agent-level model preference, verify model name format - user: "Disable gofmt formatter" → edit formatters section, set languages.gofmt.enabled = false
Add new LLM model pricing entries to Langfuse's default-model-prices.json. Use when adding model prices, updating model pricing, creating model entries, adding Claude/OpenAI/Anthropic/Google/Gemini/AWS Bedrock/Azure/Vertex AI model pricing, working with matchPattern regex, pricingTiers, or model cost configuration. Covers model price JSON structure, regex patterns for multi-provider matching, tiered pricing with conditions, cache pricing, and validation rules.
Write a high-quality prompt for any LLM or AI assistant — Claude, Claude Code, ChatGPT, Gemini, Cursor, Windsurf, Copilot, or any coding / chat agent. Use this skill whenever the user asks to write, improve, refine, shorten, or rewrite a prompt; asks "how should I phrase this for [model]" or "what's a good prompt for [task]"; describes a task they want an AI to do but hasn't yet formulated it as a prompt; or pastes an existing prompt and asks for revision. Based on Boris's (Anthropic, Claude Code creator) prompt methodology — short and accurate prompts, plan-before-code, feedback loops, persistent context in files. The universal principles (short, plan-first, feedback-loop, no-padding) apply to any LLM; the Claude-Code-specific anchors (CLAUDE.md, @file, slash commands) only apply when the target is Claude Code. If the user's intent is unclear (target model, deliverable, scope, or whether the AI has a way to self-verify is missing), ask 1–3 targeted clarifying questions via AskUserQuestion before writing the prompt.
Build LLM-powered chat apps with the right SDK — Anthropic SDK / Claude API (prompt caching, thinking, tool use, batch, files, citations, memory, model migrations) AND Vercel AI SDK (useChat, streamText, tool calls, UIMessage, ChatStatus, addToolOutput). Use when implementing chat interfaces, tuning Claude features, migrating between Claude model versions, or wiring up streaming with @ai-sdk/react.
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.
Audit and automatically optimize a lovstudio skill against repo conventions and official Anthropic skill-creator best practices, then bump the semver version and append a CHANGELOG entry. Checks SKILL.md frontmatter/trigger quality, script CLI hygiene, directory naming, README badge, and progressive disclosure structure. Prioritizes issues raised in the current conversation (e.g. bugs the user just hit) over a generic sweep. Use when the user asks to "optimize", "refine", "audit", or "polish" an existing skill, or when they say "bump version", "update changelog", or "fix this skill". Also trigger when the user mentions "优化 skill", "skill 审计", "刷一遍 skill", "skill-optimizer", "bump skill version", "update skill changelog".
A live, growing registry of agent skills published by Anthropic, OpenAI, Vercel, Microsoft, Cloudflare, Stripe, HashiCorp, Supabase, and many others. Search it before starting any non-trivial task, fetch the top result, follow it instead of going freehand. After using a skill, report back so the registry ranks it correctly for the next agent. If you build something reusable, ask the user, then upload it.
Design and scaffold the code execution pattern for MCP-based agent systems. Use when building agents that interact with many MCP tools, when intermediate data is too large for model context, when you need loops/conditionals across tool calls, or when PII must stay out of the model context. Based on Anthropic's engineering guidance.