How does this differ from the json-outputs-implementer skill?

Strict Tool Implementer is designed for executing actions via tools in agentic workflows, whereas json-outputs-implementer is intended for data extraction, classification, and formatting API responses.

Does it support complex schema features like recursive schemas?

No, strict tool use mode currently does not support recursive schemas, string length constraints, or complex regex.

What is the main benefit of the Strict Tool Implementer skill?

It guarantees that tool parameters match your schema exactly using Anthropic's strict mode, eliminating the need for manual validation logic in your tool functions.

Which models support this skill?

This skill requires Claude Sonnet 4.5 or Claude Opus 4.1 along with the structured-outputs-2025-11-13 beta header.

Strict Tool Workflow Implementer

Name: Strict Tool Workflow Implementer
Author: cskiro

bycskiro

Desarrollo de API

Implements Anthropic's strict tool use mode to build reliable, schema-compliant agentic workflows and multi-step AI systems.

Acerca de

The Strict Tool Implementer skill enables the creation of robust AI agentic systems by leveraging Anthropic’s strict tool use mode, ensuring that tool input parameters perfectly match defined JSON schemas without the need for manual validation logic. It provides a comprehensive framework for designing production-ready tool schemas, managing complex multi-tool agent architectures, and implementing sophisticated error handling and testing patterns for mission-critical operations where type safety is paramount.

Características Principales

0 GitHub stars
Multi-step agentic workflow architecture and composition
Advanced error handling and validation patterns for tool calls
Guaranteed type-safe tool execution using Anthropic's latest models
Production-ready tool schema design with strict validation
Complete implementation examples for production-grade agentic systems

Casos de Uso

Building complex multi-step agents for automated code refactoring or DevOps tasks
Implementing mission-critical API integrations requiring guaranteed parameter structures
Creating reliable function-calling layers for enterprise AI applications

Acerca de

Características Principales

0 GitHub stars
Multi-step agentic workflow architecture and composition
Advanced error handling and validation patterns for tool calls
Guaranteed type-safe tool execution using Anthropic's latest models
Production-ready tool schema design with strict validation
Complete implementation examples for production-grade agentic systems

Casos de Uso

Building complex multi-step agents for automated code refactoring or DevOps tasks
Implementing mission-critical API integrations requiring guaranteed parameter structures
Creating reliable function-calling layers for enterprise AI applications