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

Annotations already cover read-only, idempotent, and non-destructive behavior, so the description's job is lighter. It adds useful behavioral context beyond annotations: partial uppercase matching is supported, examples are given, and return fields are enumerated. No contradiction with annotations.

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 sentences with no filler: purpose, key input behavior, optional filters, and return fields. Every sentence contributes distinct value, and the most important information is front-loaded.

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?

With a full output schema and annotations covering safety/idempotency, the description sufficiently covers purpose, input format, optional filters, and return fields. Pagination is documented in the schema, so nothing critical is missing for an agent to call this correctly.

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?

Schema coverage is 100%, so the baseline is 3. The description adds meaningful extra semantics for org_name by explaining partial uppercase matching and providing concrete examples, and it summarizes optional filter parameters, which helps the agent map inputs to intent.

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 verb 'Find', the resource 'NIH research grants', and the specific scope 'awarded to a specific university, hospital, or research institute'. It distinguishes this tool from siblings like by_pi and search by focusing on institution-based lookup, and reinforces this with the title.

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 when to use the tool: whenever you have an institution name and want grants by organization. However, it does not explicitly mention alternatives (e.g., by_pi for investigator-based lookups) or when *not* to use this tool, leaving routing to inference.

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