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

Annotations already declare read-only, idempotent, non-destructive behavior. The description adds valuable context beyond annotations by noting there is no live NIH endpoint and that this is a point-in-time inventory read from ODS's list page, alerting agents to potential staleness.

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?

Three compact sentences cover purpose, filtering, and an important source caveat, with the core purpose front-loaded. Every sentence earns its place and there is no 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, one-optional-parameter, read-only inventory tool, the description covers what is returned, how filtering works, and the data source limitations. It does not spell out the exact response shape, but the scope is small enough that this is a minor gap.

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 fully documents the single optional `query` parameter with a clear description and examples. The description only restates the substring-filter behavior, adding no meaningful semantic detail beyond the schema.

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 identifies the tool as an inventory of ~45 NIH ODS fact-sheet topics and explicitly connects it to the `name` parameter of `supplement_factsheet`. This distinguishes it from sibling fact-sheet tools and leaves no ambiguity about what the tool returns.

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 states the intended use — pass result values as `name` to `supplement_factsheet` — and explains the optional `query` substring filter. It does not explicitly name alternatives or say when not to use it, but the relationship to `supplement_factsheet` is clear enough.

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