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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=true, so the safety profile is covered. The description adds meaningful non-obvious behavior beyond that: the call is asynchronous, returns a job_id immediately on worker-backed deployments, and requires polling — context the agent could not infer from annotations alone.

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?

Two sentences, zero waste. The core action is front-loaded and the async/polling behavior follows immediately, making the most operationally important detail easy to scan.

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 read-only, six-parameter tool with no output schema and fully documented parameters, the description covers what an agent needs to invoke and follow up. It does not describe the shape of the review output beyond 'suggest improvements', a minor gap given there is no output schema.

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 all six parameters documented in the input schema including defaults and enum values for focus_areas. The description contributes no additional parameter meaning, 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?

States a specific verb and resource ('Start an AI-powered code review') plus the outcome ('suggest improvements'), and explicitly distinguishes itself from the polling sibling check_ai_review_status. An agent can identify the tool's role without opening the 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 clear sequencing guidance: worker-backed deployments return a job_id and the agent should poll check_ai_review_status until completion. It names the alternative tool and the condition that selects it, though it does not state when this is preferable to other review-related siblings like repo_quality or analyze_coverage.

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