Agent Tool Builder

Most agent failures trace back to poorly described tools. The LLM never sees your implementation, just the schema and description, so a vague "gets stock price" fails while "retrieves current trade price in USD for valid NYSE/NASDAQ ticker symbols, not historical data" works. This walks through schema design, parameter descriptions, enum constraints, and error handling that actually helps Claude recover. The key insight is counterintuitive: you need fewer than 20 tools total or the agent gets confused, and every error must be instructive, never silent. Includes the emerging MCP standard and Anthropic's beta input examples feature, which apparently bumps accuracy from 72% to 90% on complex operations by showing concrete patterns schemas can't express.

skills.sh installs: 826
GitHub stars: 43.1K
last updated: Jul 14, 2026

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Install

$ npx -y skills add sickn33/antigravity-awesome-skills --skill agent-tool-builder --agent claude-code

Installs into .claude/skills of the current project.

Files

Agent Tool Builder

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 wastes tokens.

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.

Descriptions guide selection, but implementations enforce correctness, authorization and safety. Both require testing; the model may also inspect exposed code/results.

Detailed Guide

Read the detailed guide before executing this skill. It retains the complete procedure and reference material. Treat its safety, prerequisites, and validation requirements as mandatory. For focused work, load the relevant sections; for end-to-end work, read the guide completely.