US Government Open Data MCP

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

No annotations are provided, so the description carries the full burden. It describes the return content ('full nutrient breakdown') but lacks details on behavioral aspects like error handling (e.g., what happens if an invalid FDC ID is provided), rate limits, authentication needs, or response format. The description is adequate for a read-only tool but misses operational context.

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 efficiently structured in three sentences: purpose, return details, and usage guideline. Each sentence earns its place by providing essential information without redundancy. It is front-loaded with the core action and remains focused throughout.

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 simplicity (1 parameter, no output schema, no annotations), the description is largely complete. It covers purpose, parameters, and usage context. However, without annotations or output schema, it lacks details on return structure (e.g., JSON format) and error handling, which are minor gaps for a straightforward lookup tool.

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, with the parameter 'fdcId' well-documented. The description adds value by reinforcing the parameter's purpose ('FoodData Central ID') and explicitly linking it to the prerequisite tool ('get from fooddata_search results'), providing contextual meaning beyond the schema's technical definition.

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 specific action ('Get complete nutritional details'), target resource ('for a specific food by its FDC ID'), and scope ('full nutrient breakdown: calories, protein, fat, carbs, vitamins, minerals, amino acids'). It distinguishes itself from sibling tools like 'fooddata_search' by focusing on detailed retrieval rather than search functionality.

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 explicitly provides when-to-use guidance: 'Use fooddata_search first to find FDC IDs.' This clearly indicates the prerequisite step and distinguishes this tool from its sibling by specifying the workflow sequence, helping the agent understand the proper context for invocation.

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