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Found 268 Skills
Design and scaffold the code execution pattern for MCP-based agent systems. Use when building agents that interact with many MCP tools, when intermediate data is too large for model context, when you need loops/conditionals across tool calls, or when PII must stay out of the model context. Based on Anthropic's engineering guidance.
AI voice assistants with custom instructions, knowledge bases, and tool integrations.
Installs, configures, audits, and operates Agent Package Manager (APM) in repositories. Use when initializing apm.yml, installing or updating packages, validating manifests, managing lockfiles, compiling agent context, browsing MCP servers, setting up runtimes, or packaging resolved context for CI and team distribution. Don't use for writing a single skill by hand, generic package managers like npm or pip, or non-APM agent configuration systems.
Comprehensive guide for creating Claude Code agents with proper structure, triggering conditions, system prompts, and validation - combines official Anthropic best practices with proven patterns
Test authoring guidance
Quickly creates new Claude Code skills or translates ChatGPT projects into Claude Code skills. Handles skill scaffolding, frontmatter, directory structure, and ChatGPT-to-Claude migration. Use when the user wants to 'create a skill,' 'make a new slash command,' 'convert a ChatGPT project,' 'translate a GPT to Claude,' or 'migrate prompts to Claude Code.' For full eval/testing/benchmarking workflows, use skill-creator instead.
Replace with a trigger-style description of when this skill should activate. Be specific — this is what the agent uses to decide whether to load the skill. Example: "Sui TypeScript SDK integration. Use when writing, reviewing, or debugging TypeScript code that interacts with Sui RPCs, transactions, or on-chain state."
Scaffold a minimal local Deep Agent in Python by following the official quickstart, using provider-native web search instead of Tavily. Use when the user wants to quickly build or try a Deep Agent locally.
PocketFlow framework for building LLM applications with graph-based abstractions, design patterns, and agentic coding workflows
GitHub data collection patterns for workflow agents. Covers search query construction by intent, date range handling, repository scope narrowing, preferences.md integration, cross-repo intelligence, parallel stream collection model, and auto-recovery for empty results. Use when building agents that search GitHub for issues, PRs, discussions, releases, security alerts, or CI status.
This skill should be used when the user asks to "create an agent", "add an agent", "write a subagent", "multi-agent", "agent swarm", "coordinator agent", "worker agent", "agent frontmatter", "when to use description", "agent examples", "agent tools", "agent colors", "autonomous agent", "agents that communicate", "parallel agents", or needs guidance on agent structure, system prompts, triggering conditions, subagent orchestration, or multi-agent swarm development for Claude Code.
This skill should be used when the user asks to "create an agent", "make an agent", "write an agent", "build a subagent", "add an agent to a plugin", "design an autonomous agent", "generate an agent file", "write a system prompt for an agent", "what frontmatter does an agent need", "create a specialized agent". Not for skills or commands — use create-skill.