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

Annotations only say readOnlyHint=false / destructiveHint=false / idempotentHint=false. The description adds context the annotations cannot: restricted caller set, owner scoping, and the downstream consequence (future replays learn to ignore an area only when benign verdicts recur across replays while content truly changed). That is meaningfully beyond structured metadata.

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?

Front-loaded with the core action and the not-approve/not-reject boundary; every sentence carries information. It is a dense single block without visual structure and the replay-learning sentence runs long, which slightly reduces scannability.

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?

There is no output schema, so no return-value documentation is owed. For a non-idempotent write tool the description supplies the pieces an agent needs: what it records, when to call it, category semantics, region guidance, access restriction, and account scoping.

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 80%, so the baseline is already 3. The description goes further by explaining the semantic weight of category values ("dynamic_noise" = wholly benign diff vs. any other value = a regression type) and by clarifying that regions are fractions 0-1 of the live image and take their own category when noise is mixed with real change. severity's semantics are left to the enum, a minor gap.

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 the specific act (record the AI Visual Review classification of a candidate), names the source tools it draws from (list_visual_reviews / get_visual_review), and explicitly delimits scope by saying it does NOT approve or reject. That boundary is what separates it from the approval path, so an agent can tell it apart from siblings without opening a schema.

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?

Gives an explicit trigger ("call it for every candidate you inspect"), covers the edge case (candidates left pending for a person), and states a hard access boundary (automated AI review pass only; other callers refused). When-to-use and who-may-use are both nailed down.

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