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

Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds context about optional restrictions and a caveat on interpretation, but does not disclose return format, pagination, or data update characteristics, leaving a moderate transparency gap.

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?

Two concise sentences, front-loaded with the main action and followed by use cases and a caveat. Every sentence earns its place with no redundant information.

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 list-style tool with no output schema, the description covers purpose, optional filters, use cases, and a caution. It does not describe output structure or data freshness, but the schema provides field-level details for most parameters, making it reasonably complete.

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 67%, and the description compensates by enumerating filter dimensions: topic, organization, state, institute, activity code, and SBIR/STTR. This gives meaning to parameters that lack schema descriptions (ic, state, organization) and reinforces the semantics of others.

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?

States 'Find recently issued NIH awards' with a specific verb and resource, and lists distinct filters like new competing applications and SBIR/STTR. This differentiates it from sibling grant tools such as nih_funding_expirations or nih_grant_award_history.

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?

Second sentence provides clear use cases ('financing and emerging-program monitoring') and a caution about commercial validation. It lacks explicit naming of alternative tools, but the context is sufficiently clear for an agent to decide when to use this tool.

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