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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds genuinely useful context beyond that — that the result comes from a real algorithm engine rather than LLM generation — but says nothing about input constraints (e.g. equal or differing group sizes, whether volumes must be numeric strings) or what the statistical test returns.

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?

Very short and front-loaded: the resource label comes first, then the trigger, then the return. The clause '用户要算抑瘤率 TGI' partially restates the bracketed title, which is mild waste, but no sentence is otherwise superfluous.

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 only two required parameters, full schema coverage and no output schema, the description does state the return values (TGI plus a statistical test), which is the main missing piece for most tools. However, for a statistics-producing tool it omits what the statistical test actually is and what format the volumes should take, leaving real gaps for an agent composing the call.

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%, with both ctrl_volumes and treat_volumes documented in Chinese, so the schema carries the semantic load. The description adds nothing about the two parameters — no unit expectations, no note that they are arrays of string-formatted numbers, no minimum sample count — so the baseline 3 applies.

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 names a specific verb (calculate) and resource (抑瘤率 TGI), and the bracketed label plus the 'returns TGI and statistical test' clause make the output unambiguous. It is distinguishable from act_animal_tumor_volume, which computes volumes rather than the inhibition rate, though it never explicitly says so.

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?

'用户要算抑瘤率 TGI' functions as an implicit trigger condition: call this when the user wants a TGI calculation. There is no guidance on when not to use it and no sibling tool is named as an alternative, so the agent must infer routing from the tool name alone.

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