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Found 6,453 Skills
Expert prompt optimization for LLMs and AI systems. Use when building AI features, improving agent performance, crafting system prompts, or optimizing LLM interactions. Masters prompt patterns and techniques.
Divide-and-conquer implementation from specs/plans. Decomposes a reference document into independent tasks, assigns each to a builder agent, executes in parallel waves respecting dependencies, then integrates results. Use when you have a spec, PRD, plan, or large feature to implement quickly with parallel execution.
Build and deploy autonomous AI agents using the OpenServ SDK (@openserv-labs/sdk). IMPORTANT - Always read the companion skill openserv-client alongside this skill, as both packages are required to build and run agents. openserv-client covers the full Platform API for multi-agent workflows and ERC-8004 on-chain identity. Read reference.md for the full API reference.
Guide for orchestrating Claude Code agent teams — multiple parallel Claude Code sessions coordinated by a team lead. Use this skill when the user mentions agent teams, teammates, parallel agents, multi-agent workflows, spawning agents, coordinating agents, delegate mode, plan approval for teammates, TeammateIdle or TaskCompleted hooks, or wants to break a task into parallel independent work streams. Also trigger on questions about tmux split-pane mode, in-process teammate mode, Shift+Up/Down agent switching, shared task lists, inter-agent messaging, or designing tasks for multi-agent decomposition. This is an experimental feature requiring CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS to be enabled.
[Tooling & Meta] Synchronize and update Claude Code and GitHub Copilot development tool configurations to work similarly. Use when asked to update Claude Code setup, update Copilot setup, sync AI dev tools, add new skills/prompts/agents across both platforms, or ensure Claude and Copilot configurations are aligned. Covers skills, prompts, agents, instructions, workflows, and chat modes.
Manage long-running agent sessions. Use for tracking progress in extended tasks, maintaining context across long sessions, and managing multi-step workflows.
Auto-Claude performance optimization and cost management. Use when optimizing token usage, reducing API costs, improving build speed, or tuning agent performance.
This skill should be used when creating custom agents for Claude Code, configuring specialized AI assistants, or when the user asks about agent creation, agent configuration, or delegating tasks to workers. Covers both file-based agents and teams delegation.
Set up the Pica CLI and MCP server so AI agents can interact with Gmail, Slack, HubSpot, Stripe, and 200+ platforms. Handles installation, initialization, and first connection.
Agent-first project documentation. Scaffolds and maintains a documentation architecture designed for AI agents — ROADMAP, design-docs, logs, and more. Use when the user says "/docs", asks to set up project documentation, wants to update docs, or when starting a new project that lacks documentation structure. Also use when the user asks to plan a feature (creates a design doc) or review what's been done (updates logs/roadmap).
Initialize, validate, and troubleshoot Deep Agents projects in Python or JavaScript using the `deepagents` package. Use when users need to create agents with built-in planning/filesystem/subagents, configure middleware/backends/checkpointing/HITL, migrate from `create_react_agent` or `create_agent`, scaffold projects with repo scripts, validate agent config files, and confirm compatibility with current LangChain/LangGraph/LangSmith docs.
Boilerplate templates for Claude Code extensions. Triggers on: create agent, new skill, command template, hook script, extension scaffold.