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

Annotations only declare the safety profile (readOnlyHint=false, idempotentHint=true, destructiveHint=false); the description goes well beyond them by disclosing async timing (1-2 minutes), the retry semantics that make it idempotent ('picks up the same run, never a second one'), and the return value (brand_id). This is exactly the behavioral context annotations cannot carry.

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 purpose and outcome, and the polling/retry rule is stated where it matters. It runs long and repeats the schema's link-type list, but each sentence carries usable instruction rather than filler.

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 long-running, open-world tool with no output schema, the description supplies the missing pieces: return value (brand_id), the async wait/poll loop, and the correct next tool. An agent has everything needed to invoke and follow through.

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% and both parameters are already documented, including the accepted link types and the conditional need for description. The description largely restates the schema's link examples, so it does not add meaning beyond structured data; baseline 3 applies.

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 measuring/scanning a brand) and immediately specifies the scope: whether ChatGPT, Perplexity, Claude or Google AI mention it and who they recommend instead. An agent can distinguish this from list_brands or get_visibility 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?

Explicitly names the follow-up tool ('then use get_scan_status'), describes the polling condition ('if it is still running, call again with the same link'), and states when the optional description param is needed ('Only needed when add_brand says it couldn't read the website').

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