Agent skill · software engineering · sickn33
agent-tool-builder
Tools are how AI agents interact with the world. A well-designed
Why this skill is useful
Adds comprehensive guidelines for tool schema design, error handling, and validation that enhance LLM interaction capabilities.
What it needs
About 2k tokens when loaded. Last updated 2026-08-07. 44,571 stars on the source repository.
What this skill does
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 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 implementations. The LLM never sees your code - it only sees the schema and description. 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. Python Example """ import anthropic from anthropic import betatool client = anthropic.Anthropic() @betatool def getweather(location: str, unit: str = "fahrenheit") -> str: '''Get the current weather in a given location. Args: location: The city and state, e.g. San Francisco, CA unit: Temperature unit, either 'celsius' or 'fahrenheit' ''' # Implementation return json.dumps({"temperature": "72°F", "conditions": "Sunny"}) @betatool def searchweb(query: str) -> str: '''Search the web for information. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills sickn33/agent-tool-builder--38bb70