Skill UI

Covers designing agent tools from schema creation through validation and error handling, emphasizing descriptions that keep LLMs accurate and reusable via MCP standards.

This skill specializes in designing, optimizing, and evaluating prompts for Large Language Models (LLMs). It allows users to generate optimized prompt templates, structured output schemas (e.g., JSON mode, function calling), and comprehensive test suites. Use this skill when building new LLM applications, implementing complex reasoning patterns like Chain-of-Thought, defining system guardrails, or building robust evaluation frameworks to measure and improve model performance.

A PreToolUse hook that forces Claude to investigate before editing files. It denies the first edit, demands concrete facts like importers and data schemas, then allows retry—raising design depth by an average of 2.25 points in A/B tests.

This skill focuses on designing tools for AI agents to interact with the real world effectively. It covers schema design, JSON Schema best practices, error handling, and validation. It also addresses description writing for LLMs and the emerging MCP standard. Proper tool design prevents hallucinations and ensures safety. Includes Python SDK examples for function calling.

Design or review an AI agent tool registry or MCP router: document parameter schemas, caller authorization, runtime limits, effect-aware retry contracts and verification evidence before connecting tools to an agent runtime.