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GSU-FrankJ
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tool-design

Design agent tool APIs with clear descriptions and error messages.

Updated Mar 26, 2025
Search Tags:#prompt engineering#api design#ai development#tooling#mcp#agent tools
One-click install
npx skills add https://github.com/GSU-FrankJ/tournament_experiment --skill tool-design-gsu-frankj
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: tool-design
Source: https://github.com/GSU-FrankJ/tournament_experiment/tree/main/.cursor/skills/tool-design
Command: npx skills add https://github.com/GSU-FrankJ/tournament_experiment --skill tool-design-gsu-frankj

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill addresses the challenges of designing robust and intuitive tools for AI agents, ensuring seamless interaction and preventing common failure modes.

Core Features & Use Cases

  • Tool API Design: Create clear, unambiguous interfaces for agent tools.
  • Consolidation Principle: Apply principles to reduce tool complexity and ambiguity.
  • Architectural Reduction: Explore minimalist tool architectures for enhanced agent performance.
  • Use Case: When developing a new AI assistant, use this Skill to define the set of tools it can use, ensuring the tools are easy for the AI to understand and use effectively, leading to better task completion.

Quick Start

Use the tool-design skill to create a new tool description for a weather API.

Frequently Asked Questions about tool-design

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I design effective agent tools that prevent common failure modes?▼

Design effective agent tools by applying principles of clarity, consolidation, and architectural reduction to create unambiguous tool APIs that prevent common failure modes. This approach ensures seamless AI interaction and robust task completion.

What is description engineering for AI development tooling?▼

Description engineering for AI development tooling is the practice of writing clear tool descriptions and optimizing response formats so agents can accurately interpret and use the tools provided to them.

How to optimize error messages for agent recovery during task execution?▼

Optimize error messages for agent recovery by designing responses that clearly communicate the failure context, enabling the AI agent to understand the issue and adjust its parameters for successful task completion.

Does this approach support MCP tool naming conventions for API design?▼

Yes, this approach explicitly supports adherence to MCP tool naming conventions during API design, ensuring your agent tools maintain standardized interfaces for seamless integration.

What is the consolidation principle in architectural reduction for agent tools?▼

The consolidation principle in architectural reduction focuses on minimizing tool complexity and ambiguity by merging overlapping functionalities into clear, minimalist tool architectures for enhanced agent performance.

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