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

Annotations already flag destructiveHint=true and openWorldHint=true, and the description adds genuinely new behavioral context: AI actions consume the account's AI limits as in the web app, an unconfirmed email only gets trial calls, suggest_pico is not persisted, and suggest_criteria is asynchronous. It stops short of stating what check or set_criteria actually does to existing criteria on overwrite, so it is strong but not complete.

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 rationale is front-loaded in one sentence and the four actions are laid out in a scannable 'action X:' pattern with no filler. It is telegraphic and dense, and the quota note trails at the end, but every clause carries information.

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 four-action, quota-limited tool with no output schema, the definition covers persistence, async behavior, cost, and where to read the async result. The remaining gap is that it never says what the check action returns or how set_criteria reports success or conflicts, so an agent must discover that at call time.

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?

With 75% schema coverage the baseline is already decent, and the description still adds meaning: it explains that criteria entries with an id edit an existing criterion while entries without an id add one, and that preset applies a pack instead of explicit criteria. It does not explain the stage, required, or exclusion_label fields, which remain schema-only.

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 the specific domain (stage 1 question and eligibility criteria) and enumerates all four actions with a concrete phrase for each: quality check, concept breakdown, AI criteria draft, and saving criteria. It also distinguishes itself from siblings by pointing to revisia_question for reading results and noting that new reviews are checked by create.

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?

Every action carries a when-to-use clause ('preparing stage 1 and the eligibility criteria', 'a review that already exists', 'runs as a job; read the result with revisia_question', 'save criteria the researcher accepts'). It explicitly routes the agent to revisia_question for the job result and to create for new reviews, which is exactly the alternative-selection guidance this dimension rewards.

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