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

Annotations establish that this is a write (readOnlyHint=false) but not destructive or open-world. The description adds genuinely new behavioral context: the feedback goes to the OpenCancer team, no reply is sent back through it, and it is explicitly not an urgent-care channel. That is exactly the kind of downstream consequence annotations cannot express.

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?

Three tight sentences with the primary action front-loaded before the trigger conditions and the behavioral caveats. Dense but not padded, though the third sentence stacks several caveats together and could be split for easier scanning.

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 an output schema present the description need not describe return values, and annotations cover the safety profile. What remains — when to use it, which kind to pick, what happens to the feedback, and the no-reply expectation — is fully covered for a 4-parameter reporting tool.

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 a baseline of 3 applies, but the description adds real semantics by explaining the interplay between fields: answer_id identifies the answer, message carries the user's own words, and the 'missing_answer' kind pairs with answer_id or tool and no message. It stops short of explaining the remaining enum values (bug, idea, praise) beyond their self-evident labels.

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 specific verbs and resources: flagging an OpenCancer answer for expert review, and sending feedback to the team. It is clearly distinguishable from every sibling (ask_opencancer, find_clinical_trials, get_trial_details, open_case), all of which are retrieval tools rather than reporting channels.

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?

Enumerates concrete trigger conditions: the answer was wrong, unsafe, or incomplete; the user wants to tell OpenCancer something; or a tool returned no usable answer. It even prescribes the right kind value ('missing_answer') and the parameter combination for that case, leaving nothing to inference.

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