When should I use a tool instead of an agent?

Use a tool for single, deterministic operations that execute quickly (under 1 second). Use an agent for multi-step workflows that require judgment, complex reasoning, or the accumulation of context over several steps.

Can I use this skill with existing MCP servers?

Yes. This skill provides wrappers and consolidation patterns that allow you to take complex third-party MCPs (like Playwright or Linear) and wrap them into more efficient, workflow-level tools for Claude.

What is the Consolidation Principle in tool design?

It is the architectural strategy of reducing the total number of tools available to an LLM while making the remaining tools more robust. Research shows that reducing tool count (e.g., from 17 to 2) can increase agent success rates from 80% to 100%.

How does reducing the number of tools improve AI performance?

Fewer tools reduce the 'decision space' for the model, leading to fewer hallucinations. It also simplifies the context window by reducing the amount of instruction text the model must process for every turn.

Claude Code Tool Design

Name: Claude Code Tool Design
Author: greyhaven-ai

bygreyhaven-ai

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API Development

Optimizes MCP tool architectures using the consolidation principle to maximize AI agent success rates and minimize cognitive load.

About

This skill empowers developers to build high-performance Model Context Protocol (MCP) servers and Claude Code integrations by applying the 'Consolidation Principle'—the practice of reducing tool sprawl to improve agent reliability. It provides proven architectural patterns for transforming fragmented, granular tools into robust, multi-purpose interfaces, which has been shown to increase AI task success rates from 70% to near 100%. Users gain access to structured parameter design standards, naming convention guides, and decision frameworks to determine when to use tools versus agents or skills, ensuring Claude always selects the most efficient path for any given task.

Key Features

Architectural reduction patterns to consolidate dozens of tools into high-success interfaces
MCP fully-qualified naming standards to prevent tool collisions
Comprehensive audit checklists for evaluating and optimizing existing tool sets
16 GitHub stars
Parameter consolidation strategies for creating flexible, multi-purpose tools
Decision frameworks for choosing between tools, agents, and skills

Use Cases

Auditing agent architectures to reduce tool-selection errors and context bloat
Designing and building custom Model Context Protocol (MCP) servers
Refactoring existing complex tool sets to improve Claude's reasoning performance

About

Key Features

Architectural reduction patterns to consolidate dozens of tools into high-success interfaces
MCP fully-qualified naming standards to prevent tool collisions
Comprehensive audit checklists for evaluating and optimizing existing tool sets
16 GitHub stars
Parameter consolidation strategies for creating flexible, multi-purpose tools
Decision frameworks for choosing between tools, agents, and skills

Use Cases

Auditing agent architectures to reduce tool-selection errors and context bloat
Designing and building custom Model Context Protocol (MCP) servers
Refactoring existing complex tool sets to improve Claude's reasoning performance