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

The description goes well beyond the annotations (readOnlyHint=false, idempotentHint=true) by disclosing that it records submitted details, that approval involves a human reviewer, that successful applicants receive a single-use 100% discount code, and that re-applying with the same address is safe and never overwrites decided applications. This fully aligns with the idempotentHint and adds rich behavioral context.

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 slightly verbose but every sentence provides necessary context: purpose, privacy warning, manual process, outcome, idempotency, and commercial exclusion. It is front-loaded with the main purpose and then covers critical caveats, though some sentences could be tightened.

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 the tool's complexity (5 params, manual approval, side effects), the description is complete for an agent to decide whether and how to call it. It explains the flow, safety of re-application, and expected outcomes; the existence of an output schema covers return values, so no major gaps remain.

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 schema fully documents each parameter. The description adds only that the address, institution and use case are recorded, which is behavioral rather than semantic. It does not enhance understanding of the optional source or expected_volume parameters beyond the schema, so the 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 states a specific verb and resource ('Apply for free HLA-Verify access') and narrows the audience to academic or nonprofit labs, clearly distinguishing it from commercial purchase. It also differentiates itself from siblings like beta_signup by focusing on free research access with manual review.

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?

It explicitly instructs the agent to 'Ask before calling' because the tool records personal information, sets expectations that approval is manual, non-instant, and not guaranteed, and directs commercial labs to an alternative pricing page. This gives clear 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.