FDEP MCP Server

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'analyze' but doesn't specify what the analysis entails (e.g., returns usage counts, locations, patterns), whether it's read-only or has side effects, or any performance considerations. This leaves significant gaps in understanding the tool's behavior.

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

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

The description is a single, clear sentence: 'Analyze how types are used throughout the codebase'. It is front-loaded with the core purpose, has zero wasted words, and is appropriately sized for the tool's complexity, making it easy for an agent to parse quickly.

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

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

Given the tool's complexity (4 parameters, no annotations, no output schema), the description is incomplete. It lacks details on what the analysis returns, how results are structured, or any behavioral traits (e.g., performance, side effects). This makes it insufficient for an agent to fully understand how to use the tool effectively in context.

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

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

The input schema has 100% description coverage, clearly documenting all four parameters. The description adds no additional parameter semantics beyond what's in the schema (e.g., it doesn't explain how 'type_name' and 'module_name' interact or what 'usage' means in context). With high schema coverage, a baseline score of 3 is appropriate as the description doesn't compensate but doesn't detract either.

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

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

The description clearly states the tool's purpose: 'Analyze how types are used throughout the codebase'. It specifies the verb ('analyze') and resource ('types'), making it understandable. However, it doesn't explicitly differentiate from sibling tools like 'analyze_type_relationships' or 'get_type_details', which could provide similar type-related insights.

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

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

The description provides no guidance on when to use this tool versus alternatives. With many sibling tools available (e.g., 'analyze_type_relationships', 'get_type_details', 'list_types'), there is no indication of when this analysis is preferred or what specific use cases it addresses, leaving the agent to guess based on the name alone.

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