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 search functionality and provides example queries, which adds useful context. However, it lacks details on behavioral traits such as rate limits, authentication needs, error handling, or the structure of returned results (since no output schema exists). The description does not contradict any annotations, as none are given.

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 front-loaded with the core purpose in the first sentence, followed by specific search methods and clear examples. Every sentence earns its place by providing essential information without redundancy, making it efficient and well-structured for quick comprehension.

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 (search with two parameters) and the absence of both annotations and an output schema, the description does a good job of covering the basics: purpose, usage examples, and parameter context. However, it lacks details on result formatting, pagination, or error scenarios, which would be needed for full completeness in this 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, so the baseline is 3. The description adds value by explaining the types of searches possible (e.g., by name, CAS code) and providing concrete examples that illustrate how to use the 'search' parameter effectively. This enhances understanding beyond the schema's technical description of the query format.

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: 'Search FDA substance data — molecular-level ingredient information.' It specifies the exact resource (FDA substance data) and verb (search), and distinguishes itself from sibling tools by focusing on molecular-level ingredient information, which is unique among the listed FDA-related tools like fda_approved_drugs or fda_unii.

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 clear context for usage by listing searchable fields (name, CAS code, UNII, molecular formula) and includes example queries. However, it does not explicitly state when to use this tool versus alternatives (e.g., fda_unii for UNII-specific searches) or mention any prerequisites or exclusions, which prevents a perfect score.

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