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Found 9,880 Skills
Create, optimize, and maintain AGENTS.md and CLAUDE.md files using progressive disclosure. Use when: User wants to create AGENTS.md/CLAUDE.md, optimize existing AI documentation, implement progressive disclosure, detect project structure (monorepo/polyrepo), or prevent documentation bloat. Triggers on: "create agents.md", "update AGENTS.md", "AI documentation", "project context", "monorepo documentation", "progressive disclosure", "Claude Code context", or when AI repeatedly asks the same questions about the project.
Use when you need Teams-first multi-agent orchestration in Claude Code. Triggers on: omc, autopilot, ralph, ulw, ccg, team. 29+ specialized agents, smart model routing (Haiku→Opus), persistent execution loops, skill layers, real-time HUD.
Configure a PreToolUse hook to prevent AI agents from skipping git pre-commit hooks with --no-verify and other bypass flags. Use when setting up Claude Code projects that enforce commit quality gates.
Token-efficient persistent memory system for Claude Code that extends your session limits by 3-5x. Layered architecture with progressive loading, compact encoding, branch-aware context, smart compression, session diffing, conflict detection, session continuation protocol, and recovery mode. Activates at session start (if MEMORY.md exists), on "remember this", "pick up where we left off", "what were we doing", "wrap up", "save progress", "don't forget", "switch context", "hand off", "memory health", "save state", "continue where I left off", "context budget", "how much context left", or any session start on a project with existing memory files. This skill solves two problems at once: Claude forgetting everything between sessions, AND sessions hitting context limits too fast. It replaces thousands of wasted re-explanation tokens with a compact, structured memory load that gives Claude full project context in under 2,000 tokens.
Scaffold Claude Code hooks into a real project after auditing the project structure in detail. Use when a user wants Claude Code hook setup, hook refactors, full hook-event scaffolding, or managed updates to existing .claude hooks. This skill verifies the live official Claude Code hook docs first, audits the target repo, then generates a bash-first hook scaffold with a hooks README, repeatable merge behavior, and coverage for every current hook event. Trigger on: Claude Code hooks, scaffold hooks, hook events, update hooks, hook architecture, .claude/settings.json. Do NOT use for generic Git hooks, Husky-only setup, or non-Claude agents.
End-to-end Claude Design handoff to pull request: imports a handoff bundle from claude.ai/design, generates Storybook stories and Playwright tests, runs diff-aware browser verification, and opens a PR with the bundle URL, before/after screenshots, and coverage delta embedded in the body. The one-shot 'design URL in, reviewable PR out' workflow. Use when a designer or PM hands you a Claude Design URL and you want a PR back without intermediate steps.
Curates insights from reflections and critiques into CLAUDE.md using Agentic Context Engineering
Validate a Claude Code plugin structure, frontmatter, and MCP tool references
Reviews an AGENTS.md or CLAUDE.md file against best practices and reports concrete fixes. Use when the user asks to review, audit, lint, or improve an AGENTS.md / CLAUDE.md / context file, or says "review my agents file".
Curated collection of 1000+ agent skills compatible with Claude Code, Codex, Gemini CLI, Cursor, and more
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.
Converts Claude skills into ChatGPT Project format (prompt instructions + 1 knowledge file as .docx). Use when user mentions "convert to ChatGPT," "ChatGPT project," "export skill," "GPT instructions," "skill to prompt," or "skill to GPT."