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

Annotations cover the safety profile (readOnly, idempotent, non-destructive, closed-world), and the description goes further with what annotations cannot express: the full status lifecycle (queued/running/done/failed/refused) and the actual return contract for ChatGPT and Perplexity results. The polling expectation is stated explicitly, which is exactly the behavioral context a caller needs.

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-loads the core action and the sibling linkage before the status/return detail, and every sentence carries information. The status enumeration and result-content sentence are dense but not padded, though the description runs slightly long for a one-parameter tool.

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 no output schema, the description must describe what comes back, and it does: status values plus the per-engine breakdown (who named the business, who was named instead, one fix). Combined with the polling instruction, nothing an agent needs to call and interpret this tool is missing.

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% for the single check_id parameter, so the baseline is 3. The description only restates provenance ('using the check_id it returned'), adding no format or constraint detail beyond the schema's pattern and description.

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?

Names a specific verb+resource (get the result of a check) and ties it directly to the sibling that produces the input, check_ai_recommendation. The closing sentence explicitly rules out the sibling's job ('Do not use this to start a new check'), so an agent can separate the two tools without opening either 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 explicit when-to-use (retrieving a check's result by its check_id) and when-not-to-use (starting a new check). It also specifies the poll condition and cadence: if status is queued or running, tell the user and call again after ~15 seconds.

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