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Found 10,094 Skills
Write, audit, and improve AGENTS.md files for AI coding agents. Use when creating or improving agent context for a codebase.
Implementation + audit loop using parallel agent teams with structured simplify, harden, and document passes. Spawns implementation agents to do the work, then audit agents to find complexity, security gaps, and spec deviations, then loops until code compiles cleanly, all tests pass, and auditors find zero issues or the loop cap is reached. Use when: implementing features from a spec or plan, hardening existing code, fixing a batch of issues, or any multi-file task that benefits from a build-verify-fix cycle.
Produces a single-story walkthrough of AI-authored code changes from runtime trigger to final behavior, weaving changed and unchanged code into one narrative with annotated diffs, trade-offs, alternatives, and risk analysis. Use when asked to "explain what changed", "walk me through this diff", "summarize agent edits", "show how this feature works", or "explain this implementation step by step".
Use when executing implementation plans with independent tasks in the current session or facing 3+ independent issues that can be investigated without shared state or dependencies - dispatches fresh subagent for each task with code review between tasks, enabling fast iteration with quality gates
Launch an intelligent sub-agent with automatic model selection based on task complexity, specialized agent matching, Zero-shot CoT reasoning, and mandatory self-critique verification
Design multi-agent architectures for complex tasks. Use when single-agent context limits are exceeded, when tasks decompose naturally into subtasks, or when specializing agents improves quality.
Transform AI agents from task-followers into proactive partners that anticipate needs and continuously improve. Includes memory architecture with pre-compaction flush (so context survives when the window fills), reverse prompting (surfaces ideas you didn't know to ask for), security hardening, self-healing patterns (diagnoses and fixes its own issues), and alignment systems (stays on mission, remembers who it serves). Battle-tested patterns for agents that learn from every interaction and create value without being asked.
Plays survAIvor as a contestant agent. Use when participating in a live game to decide what to say, who to influence, when to vote, and when to reveal as a ghost.
Interactive session to craft a system prompt for an AI agent powered by Sanity Agent Context MCP.
10-parallel code/design review using reviewer subagents. Use when: - Running code reviews on PRs, commits, or branches - Running design reviews on issues or documents - Need multi-perspective review (security, architecture, code, QA, historian)
Register and configure an AI agent on OpenAnt. Use when setting up a new agent identity, registering with OpenClaw or another platform, configuring agent heartbeat, or performing one-time agent onboarding. Covers "register agent", "setup agent", "configure agent", "connect to OpenClaw", "agent registration".
Agent definition conventions. Use when creating or modifying agents at any level (~/.claude/agents/, .claude/agents/, or project-local). Validate frontmatter, update README.md index. NOT for creating skills, MCP servers, or modifying CLAUDE.md.