How does it handle tool errors?

It provides patterns for returning explicit, descriptive errors that help the AI agent understand what went wrong and how to fix its input to recover successfully without human intervention.

Why are tool descriptions more important than implementation?

Since LLMs only see the schema and description, not the underlying code, a clear description is vital to prevent hallucinations and ensure the agent knows exactly when and how to use a tool.

Can it help reduce token usage?

Yes, by designing more precise schemas and avoiding 'tool loops' caused by vague documentation, it minimizes unnecessary token consumption and improves response speed.

Does this support the Model Context Protocol (MCP)?

Yes, it includes best practices for the emerging MCP standard, helping you build tools that are compatible with the broader AI tool ecosystem.

What is the Agent Tool Builder skill?

It is a specialized capability for Claude Code focused on designing high-quality interfaces (tools) that allow AI agents to interact reliably with external APIs and systems.

AI Agent Tool Architect

Name: AI Agent Tool Architect
Author: claudiodearaujo

byclaudiodearaujo

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API 개발

Optimizes AI agent performance by designing high-precision tool schemas, clear documentation, and robust error-handling interfaces.

This skill empowers developers to build reliable interfaces between LLMs and external systems by focusing on the critical interface layer. It provides expert guidance on JSON Schema design, the Model Context Protocol (MCP), and strategic tool descriptions that prevent agent hallucinations. By prioritizing clarity in schema definition and error messaging over raw implementation, it ensures that AI agents can interact with the real world without silent failures or inefficient token usage, making it indispensable for anyone building autonomous agentic workflows.

주요 기능

01Input validation and example-based guidance for LLMs

02Strategic tool description writing to minimize LLM hallucinations

03Model Context Protocol (MCP) standardization and implementation

041 GitHub stars

05Advanced JSON Schema design for unambiguous tool calling

06Robust error-handling patterns for autonomous agent recovery

사용 사례

01Designing complex API integrations for autonomous AI agents

02Standardizing custom tools for Model Context Protocol (MCP) servers

03Optimizing existing function-calling systems to reduce token costs and errors

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add claudiodearaujo/sistema-de-narra-o-de-livro agent-tool-builder

For use in Claude.ai and ChatGPT

Download Skill