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Found 11,836 Skills
Agent spawning, lifecycle management, and coordination patterns. Manages 60+ agent types with specialized capabilities. Use when: spawning agents, coordinating multi-agent tasks, managing agent pools. Skip when: single-agent work, no coordination needed.
Agent skill for goal-planner - invoke with $agent-goal-planner
Agent skill for adaptive-coordinator - invoke with $agent-adaptive-coordinator
Agent skill for sparc-coordinator - invoke with $agent-sparc-coordinator
Use when you need to generate an AGENTS.md file for a Java repository — covering project conventions, tech stack, file structure, commands, Git workflow, and contributor boundaries — through a modular, step-based interactive process that adapts to your specific project needs. Part of the skills-for-java project
Overview The X Agent mpowers businesses, researchers, and marketers to move beyond surface-level monitoring to gain a comprehensive understanding of brand sentiment, competitor strategies, and communi
GitHub data collection patterns for workflow agents. Covers search query construction by intent, date range handling, repository scope narrowing, preferences.md integration, cross-repo intelligence, parallel stream collection model, and auto-recovery for empty results. Use when building agents that search GitHub for issues, PRs, discussions, releases, security alerts, or CI status.
This is used when users want to learn about industry hotspots, check topic challenge rankings, view recent hot search events or public domain popularity trends. It supports two dimensions: topic challenges and hot list events. Manual trigger: /trending
Build and deploy autonomous AI agents in-process using Open Agent SDK, an open-source alternative to @anthropic-ai/claude-agent-sdk that works anywhere without CLI dependencies.
Advanced AI agent benchmark scenarios that push Vercel's cutting-edge platform features — Workflow DevKit, AI Gateway, MCP, Chat SDK, Queues, Flags, Sandbox, and multi-agent orchestration. Designed to stress-test skill injection for complex, multi-system builds.
Core patterns for AI coding agents based on analysis of Claude Code, Codex, Cline, Aider, OpenCode. Triggers when: Building an AI coding agent or assistant, implementing tool-calling loops, managing context windows for LLMs, setting up agent memory or skill systems, or designing multi-provider LLM abstraction. Capabilities: Core agent loop with while(true) and tool execution, context management with pruning and compression and repo maps, tool safety with sandboxing and approval flows and doom loop detection, multi-provider abstraction with unified API for different LLMs, memory systems with project rules and auto-memory and skill loading, session persistence with SQLite vs JSONL patterns.
Runs a second-pass cleanup over AI-written code using the repo's style guide in style.md. Prefers parallel subagents to simplify recently modified files without changing behavior. Use when the user says "deslop", "clean this up", "make this less AI", "apply my style guide", "second pass", or asks to simplify generated code after implementation.