Why are tool descriptions considered prompt engineering?

Agents use descriptions to reason about intent and infer parameters; clear, specific descriptions steer the model's behavior and significantly reduce tool misuse failures.

What is the correct way to name MCP tools?

Always use fully qualified names in the format 'ServerName:tool_name' to prevent 'tool not found' errors, especially when working with multiple MCP servers.

How does Architectural Reduction improve agent performance?

It replaces complex specialized tools with general-purpose primitives like file system access, allowing the model's internal reasoning to handle task complexity more flexibly.

Can Claude help optimize its own tools?

Yes, by using the Tool-Testing Agent pattern, Claude can analyze its own failure logs and suggest improvements to tool descriptions and schemas to prevent future errors.

What is the Consolidation Principle in tool design?

It is the practice of creating single, comprehensive tools for workflows rather than multiple narrow ones, which reduces model ambiguity and minimizes token consumption.

Tool Design for Agents

Name: Tool Design for Agents
Author: boisenoise

byboisenoise

API Development

Provides architectural principles and best practices for designing high-performance tools and MCP interfaces for AI agents.

About

This skill equips developers with the framework needed to create effective agent-tool interfaces, focusing on the Consolidation Principle and Architectural Reduction. It provides guidance on writing tool descriptions that function as prompt engineering, handling error recovery, optimizing response formats for token efficiency, and implementing Model Context Protocol (MCP) naming conventions. By emphasizing tools as contracts between deterministic systems and non-deterministic models, it helps eliminate common failure modes in agentic workflows and improves model reasoning accuracy.

Key Features

Tool Description Engineering: Crafting descriptions that act as steering prompts for models.
Response Optimization: Balancing output verbosity and token efficiency for better performance.
0 GitHub stars
MCP Tool Integration: Implementing fully qualified naming standards for Model Context Protocol.
Consolidation Principle: Reducing ambiguity by grouping related tasks into comprehensive tools.
Architectural Reduction: Leveraging system primitives over specialized tools to enhance flexibility.

Use Cases

Debugging and refining existing tools that agents are misusing or failing to call.
Designing custom tools for a new Claude Code agent implementation.
Standardizing tool conventions across a multi-server MCP architecture.

About

Key Features

Tool Description Engineering: Crafting descriptions that act as steering prompts for models.
Response Optimization: Balancing output verbosity and token efficiency for better performance.
0 GitHub stars
MCP Tool Integration: Implementing fully qualified naming standards for Model Context Protocol.
Consolidation Principle: Reducing ambiguity by grouping related tasks into comprehensive tools.
Architectural Reduction: Leveraging system primitives over specialized tools to enhance flexibility.

Use Cases

Debugging and refining existing tools that agents are misusing or failing to call.
Designing custom tools for a new Claude Code agent implementation.
Standardizing tool conventions across a multi-server MCP architecture.