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Found 13,019 Skills
Agent skill for spec-mobile-react-native - invoke with $agent-spec-mobile-react-native
Agent skill for v3-queen-coordinator - invoke with $agent-v3-queen-coordinator
Adds Wasp knowledge, LLM-friendly documentation fetching instructions, and best practices to your project's CLAUDE.md or AGENTS.md file
General-purpose web search using DuckDuckGo and AI-synthesized search engines. Use this skill for web searches, current information, fact-checking, news, and research on any topic where live internet data is needed. Supports all languages. Three modes: fast web results, AI-synthesized answers (IAsk.ai, great for deep questions and academic research), and Monica AI synthesis. Trigger on: "search for", "look up", "find information about", "what is the latest", "search the web", "find out about", "what happened with", "current status of", "recent news", "is X still true", "查一下", "搜索", "查资料", "上网查", "検索して", "調べて", any question requiring real-time or post-training web data. Do NOT trigger for: code exploration, local file analysis, codebase-internal questions, or well-established facts fully covered by training knowledge. Note: if the `agent-reach` skill is also available, prefer `ddg-search` for pure web search tasks; prefer `agent-reach` when the task involves social platforms (Twitter, Reddit, YouTube, WeChat, Bilibili, etc.) or platform-specific APIs.
Core standards for all GitHub workflow agents. Covers authentication, smart defaults, repository discovery, dual MD+HTML output, screen-reader-compliant HTML accessibility standards, safety rules, progress announcements, parallel execution, and output quality. Apply when building any GitHub workflow agent - issues, PRs, briefings, analytics, community reports, team management.
Scoring formulas and analytical frameworks for GitHub workflow agents. Covers repository health scoring (0-100, A-F grades), priority scoring for issues/PRs/discussions, confidence levels for analytics findings, delta tracking (Fixed/New/Persistent/Regressed), velocity metrics, contributor metrics, bottleneck detection, and trend classification. Use when computing scores, tracking remediation progress, building prioritized dashboards, or detecting workflow bottlenecks.
Use when managing project memory, initializing .agent-memory/, saving session learnings, or running memory maintenance. Handles cross-interface persistent memory for any project.
Vercel Agent guidance — AI-powered code review, incident investigation, and SDK installation. Automates PR analysis and anomaly debugging. Use when configuring or understanding Vercel's AI development tools.
Analyse agent execution to find wasted tool calls, wrong turns, and blind alleys. Optimise agents to reach their goal in the fewest turns, tokens, and least time. Recommend harness/model changes — never apply without user approval.
Master dispatcher for all MLflow workflows. Use this skill when the user wants to do anything with MLflow — tracing, evaluating, debugging, or improving an agent. Routes to the right MLflow sub-skill automatically. Triggers on: "use mlflow", "help with mlflow", "mlflow agent", "add mlflow to my project", "trace my agent", "evaluate my agent", or any MLflow task without a specific skill in mind.
Senior Multi-Agent Systems (MAS) Architect for 2026. Specialized in Model Context Protocol (MCP) orchestration, Agent-to-Agent (A2A) communication, and recursive delegation frameworks. Expert in managing complex task handoffs, shared memory state, and parallel subagent execution for high-autonomy engineering missions.
Test-Driven Development enforces the RED-GREEN-REFACTOR discipline on every code change an agent produces.