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Agent Tool Builder

Skills ai-research 415

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

Install Command
npx claude-code-templates@latest --skill ai-research/agent-tool-builder
View on GitHub
claude-code — agent-tool-builder

Content

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

Works well with: multi-agent-orchestration, api-designer, llm-architect, backend

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