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 of behavioral disclosure. It mentions the tool searches adverse event reports but does not disclose key behavioral traits such as whether this is a read-only operation, potential rate limits, authentication needs, or what the output format looks like (e.g., JSON structure, pagination). The example queries add some context but fall short of comprehensive behavioral transparency.

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 two concise example searches that directly support usage. Every sentence earns its place by providing essential information without redundancy or fluff, making it highly efficient and well-structured.

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 (searching adverse event reports with a query language), the description is moderately complete. It lacks an output schema, so the description does not explain return values, and with no annotations, it misses behavioral details. However, it covers the purpose and provides usage examples, which partially compensates for these gaps in a simple search 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 providing concrete example queries ('device.generic_name:pacemaker', 'event_type:death') that illustrate how to use the 'search' parameter in practice, going beyond the schema's generic examples. However, it does not explain the 'limit' parameter beyond what the schema already states.

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 medical device adverse event reports (MAUDE) — injuries, malfunctions, deaths.' It specifies the verb ('Search'), resource ('FDA medical device adverse event reports'), and scope ('MAUDE' with examples of event types). It distinguishes itself from sibling tools like 'fda_device_510k' or 'fda_device_recalls' by focusing on adverse event reports.

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 implied usage through example searches (e.g., 'device.generic_name:pacemaker', 'event_type:death'), which suggests when to use this tool for querying specific fields. However, it lacks explicit guidance on when to use this tool versus alternatives (e.g., other FDA tools like 'fda_device_recalls' for recalls or 'fda_count' for counts), and does not mention any prerequisites or exclusions.

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