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Found 11,735 Skills
Configure the project's skill stack and supervision preferences. Reads the curated registry in `skillpacks/skill_dictionary.yaml`, asks a short preset-first set of questions about workflow, dependency tolerance, autonomy style, and resource policy, then writes or updates `.co-researcher/skills.yaml`. Trigger phrases: "customize my stack", "configure skillpacks", "set up my skills", "choose presets", "configure supervision and packs", "personalize this project".
Guided, section-by-section Art Bible authoring. Creates the visual identity specification that gates all asset production. Run after /brainstorm is approved and before /map-systems or any GDD authoring begins.
Orchestrate the polish team: coordinates performance-analyst, technical-artist, sound-designer, and qa-tester to optimize, polish, and harden a feature or area for release quality.
Persistent memory system for Claude Code. Two-layer architecture (hot cache + knowledge wiki), safety hooks, /close-day end-of-day synthesis. Zero external dependencies.
Add an MCP server to pi. Use when asked to "add mcp server", "configure mcp", "add mcp", "new mcp server", "setup mcp", "connect mcp server", or "register mcp server". Handles both global and project-local configurations.
Assistant for ZenTao project management system via JS scripts. Use when the user asks about ZenTao, lists/creates/updates projects, products, users, tasks, bugs, or manages project workflow via natural language commands.
Diagnose why a GAIA question failed — extract trace, classify failure mode, and propose a fix
Universal CLI client for Model Context Protocol (MCP) with persistent sessions, OAuth, tasks, and JSON output for shell scripting
Use when reviewing how skills performed during a session, when the user wants to analyze skill invocations and identify improvements, or when the user says "skill retro", "review skills", "how did skills do", "improve this skill", or "skill retrospective".
Manage Model Context Protocol (MCP) servers - discover, analyze, and execute tools/prompts/resources from configured MCP servers. Use when working with MCP integrations, need to discover available MCP capabilities, filter MCP tools for specific tasks, execute MCP tools programmatically, access MCP prompts/resources, or implement MCP client functionality. Supports intelligent tool selection, multi-server management, and context-efficient capability discovery.
Set up and run Ralph Wiggum loop - autonomous AI coding with clean slate iterations, PRD-driven features, and CI quality gates. Use for long-running autonomous coding tasks.
Room-based exploration with narrative evidence collection