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Divagnz

React Native Expo MCP

by Divagnz

analyze_codebase_performance

Identify performance issues in React Native codebases across list rendering, navigation, animations, memory, bundle size, and startup time.

Instructions

Analyze entire React Native codebase for performance issues

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codebase_pathNoPath to React Native project root
focus_areasNoSpecific performance areas to focus on
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are present, so the description must convey behavioral traits. It does not disclose whether the tool is read-only, requires network access, modifies files, or has side effects. The only mentioned behavior is 'analyze,' which is vague for an agent that needs to understand risks and expectations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The single-sentence description is highly concise and front-loaded with the action verb. However, its brevity sacrifices important details like usage context and output, making it efficient but not optimally informative for an agent.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (analysis of a codebase) and the lack of output schema, the description fails to explain return format, runtime expectations, prerequisites (e.g., project structure), or how results are reported. Sibling tools like optimize_performance suggest follow-up actions, but the description does not connect to them.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already describes both parameters (codebase_path and focus_areas) with full coverage. The description adds limited extra meaning beyond clarifying the scope ('entire' codebase) and focus ('performance'), which slightly enriches the context but does not substantially augment the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool analyzes the entire React Native codebase for performance issues, providing a specific verb, resource, and scope. It effectively distinguishes from siblings like analyze_codebase_comprehensive (broader) and optimize_performance (more actionable).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives such as analyze_codebase_comprehensive or optimize_performance. The description lacks context about appropriate scenarios or prerequisites, leaving the agent without helpful decision criteria.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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