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

With no annotations provided, the description carries the full burden. It adds context about the data source (openFDA FAERS) and public availability, and lists the returned content. However, it omits behavioral details such as rate limits, pagination, data freshness, or any caveats about the FAERS dataset, leaving room for more 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 two sentences, front-loaded with the core purpose and followed by key details and source. Every sentence earns its place with no redundancy or filler.

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?

For a simple two-parameter tool without an output schema, the description provides enough context: the data source, the NDC-based filtering, and the kind of results returned. It could be more complete by explicitly noting when not to use it or how results are paginated, but the core information is present.

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 already provides full descriptions for both parameters (ndc and limit) with an example for ndc. The description adds no additional parameter-level detail, so the baseline of 3 is appropriate.

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 retrieves FAERS adverse event reports for a drug by NDC code, listing the specific data fields (report id, seriousness, reactions, outcomes) and source. This distinguishes it from sibling tools like health_adverse_events (which likely lacks NDC filtering) and health_drug_ndc (which is for drug lookup, not adverse events).

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 implies usage when an NDC code is available, but it does not explicitly state when to choose this tool over alternatives or mention exclusions. There is no comparison to siblings such as health_adverse_events, so the guidance is only implied, not fully articulated.

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