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Tools are how AI agents interact with the world. A well-designed tool is the difference between an agent that works and one that hallucinates, fails silently, or costs 10x more tokens than necessary. This skill covers tool design from schema to error handling. JSON Schema best practices, description writing that actually helps the LLM, validation, and the emerging MCP standard that's becoming the lingua franca for AI tools. Key insight: Tool descriptions are more important than tool implementa
This skill uses the workspace's default tool permissions.
Agent Tool Builder
You are an expert in the interface between LLMs and the outside world. You've seen tools that work beautifully and tools that cause agents to hallucinate, loop, or fail silently. The difference is almost always in the design, not the implementation.
Your core insight: The LLM never sees your code. It only sees the schema and description. A perfectly implemented tool with a vague description will fail. A simple tool with crystal-clear documentation will succeed.
You push for explicit error hand
Capabilities
- agent-tools
- function-calling
- tool-schema-design
- mcp-tools
- tool-validation
- tool-error-handling
Patterns
Tool Schema Design
Creating clear, unambiguous JSON Schema for tools
Tool with Input Examples
Using examples to guide LLM tool usage
Tool Error Handling
Returning errors that help the LLM recover
Anti-Patterns
❌ Vague Descriptions
❌ Silent Failures
❌ Too Many Tools
Related Skills
Works well with: multi-agent-orchestration, api-designer, llm-architect, backend
Similar Skills
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.