Skills your agents can run

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Orchestrates design workflows by routing work through brainstorming, multi-agent review, and execution readiness in the correct order.

Join The Colony — a collaborative intelligence platform for AI agents and humans. Post findings, discuss ideas, complete tasks, earn karma, and build your reputation.

Comprehensive guide to integrating DSPy with Microsoft Agent Framework in AgenticFleet, covering typed signatures, assertions, routing cache, GEPA optimization, and agent handoffs.

Orchestrate multiple AI models (GLM, MiniMax, etc.) as workers using Pi Coding Agent with Claude as coordinator.

Social presence layer for AI coding agents. See who's coding right now and share ephemeral vibes.

Use when working with *.excalidraw or *.excalidraw.json files, when the user mentions diagrams or flowcharts, or requests architecture visualization. Delegates all Excalidraw operations to subagents to prevent context exhaustion from verbose JSON (single files often 4k–22k tokens and can exceed read limits).

Use when executing implementation plans with independent tasks in the current session

Advanced Hive Mind collective intelligence system for queen-led multi-agent coordination with consensus mechanisms and persistent memory

Virtual Pub for AI Agents

Orchestrate parallel Claude Code worker swarms with protocol-based behavioral governance. Use for complex features, large refactors, or multi-step tasks. Supports behavioral constraints, parallel workers, and persistent state across context compactions.

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

Jeffrey Emanuel's multi-agent implementation workflow using NTM, Agent Mail, Beads, and BV. The execution phase that follows planning and bead creation. Includes exact prompts used.

The agent-only marketplace. Post jobs, complete work, earn $OPENWORK tokens on Base. Competitive bidding — multiple agents submit, poster picks the winner.

Create high-quality MCP servers that enable LLMs to effectively interact with external services. Use when building MCP integrations for APIs or services in Python (FastMCP) or Node/TypeScript (MCP SDK).

A GAN (Generative Adversarial Network)-style evaluation harness, image-generation patterns, and quality metrics.

Provides MoAI-ADK foundational principles including the TRUST 5 quality framework, SPEC-First DDD methodology, delegation patterns, progressive disclosure, agent catalog reference, and token budget management (absorbed from moai-foundation-context). Use when referencing TRUST 5 gates, SPEC workflow, or context window optimization.

This skill should be used when the user asks to "add MCP server", "integrate MCP", "configure MCP in plugin", "use .mcp.json", "set up Model Context Protocol", "connect external service", mentions "${CLAUDE_PLUGIN_ROOT} with MCP", or discusses MCP server types (SSE, stdio, HTTP, WebSocket). Provides comprehensive guidance for integrating Model Context Protocol servers into Claude Code plugins for external tool and service integration.

Coordinates multi-AI-agent and task-aggregation workflows. Distributes work across multiple workers, handles errors, and merges results.

Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies