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

Beyond the annotations, the description adds meaningful behavioral context: output is the entire matching unit, never paraphrased or summarized, by a named expert, with references and disclaimers included. It also discloses the $0.001 USDC cost and payment mechanism. The phrase 'arrive at every rung' is somewhat obscure, and it does not describe return format in detail, but the key behaviors are disclosed.

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 functional but somewhat repetitive, restating 'one answer' and 'entire, as written, never a cut' with similar phrasing. It front-loads the central concept before the alternative, but the rhetorical questions and redundant 'never paraphrased, never summarised' phrasing make it less concise than it could be.

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 with no output schema, the description explains enough: what is returned, how it is selected, who authored it, how to choose the sibling tool, and the payment context. The paymentHeader challenge behavior is covered in the schema, so that gap is filled. A minor shortfall is that 'every rung' is unexplained jargon.

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 100%, so the schema already explains both query and paymentHeader. The description adds little parameter-level meaning beyond 'one question' and 'shortest whole unit.' Since the structured field descriptions carry the heavy lifting, a baseline score 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 identifies the tool's purpose: returning the shortest whole matching unit for a single clinical question about GLP-1 topics, authored by a specific clinician. It also distinguishes itself from clinic_clinical_passage by contrasting 'shortest answer' versus 'best-matching passage.' However, it lacks a direct verb like 'returns' and leans on a rhetorical question, making the core action slightly less immediate.

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?

Usage is clearly scoped to one question with room for one answer, with an explicit instruction to use clinic_clinical_passage instead when a best-matching passage is desired. It also states the no-match behavior and that no charge occurs in that case. This gives the agent actionable when-to-use and when-not-to-use guidance.

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