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

No annotations are provided, so the description must carry the full burden. It correctly indicates a read operation (returns data) but does not disclose any behavioral traits such as rate limits, authorization needs, or pagination behavior, which is a notable 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?

The description is exceptionally concise with two sentences. The first sentence front-loads the core purpose and value proposition ('highest-intent buying signal'), and the second lists filters efficiently. No wasted words.

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 13 parameters and no output schema, the description leaves gaps: it doesn't explain the return structure, pagination, or how results are ordered. For a tool that returns many records, this is a significant omission.

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 description coverage is 77%, already providing decent parameter documentation. The description adds context about filtering by 'institution, PI, sponsor, topic, state, IC, phase' but does not significantly enhance clarity beyond the schema. Baseline 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 returns 'the newest NIH grants and newly-registered clinical trials in a territory', specifying both verb and resource. It explicitly distinguishes itself as a 'GTM-trigger tool' for life-sciences sales, differentiating from sibling tools like delta_digest or search_records.

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 strong context on when to use (high-intent buying signal for sales) but does not explicitly state when not to use or compare to alternatives. It implies usage for initial outreach but lacks direct exclusion criteria.

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