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

Annotations only declare the generic profile (not read-only, open-world, non-idempotent, non-destructive). The description adds the traits that actually matter for a decision: it consumes one of the plan's monthly runs (a quota cost), it takes about five minutes (latency/asynchrony), and it fans out to five external providers. That is meaningful context beyond the structured fields.

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?

Four short sentences, front-loaded with what the tool does, then cost, then the prerequisite workflow, then where results appear. No filler and no repetition of the title.

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, but the description closes that gap by naming get_ai_visibility as the retrieval path and giving the ~5 minute window. Combined with the quota warning and the prerequisite chain, an agent has everything needed to call this correctly and set user expectations.

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?

The tool takes zero parameters, so there is nothing for the description to disambiguate and the baseline is 4. The description correctly implies the question set comes from tracked questions rather than from arguments, which is the only semantic point available.

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 ('run an AI visibility audit') and immediately specifies the mechanism: querying ChatGPT, Perplexity, Gemini, Claude and Grok with every tracked question and recording mentions. It also distinguishes itself from the sibling that returns data ('get_ai_visibility has the results'), so an agent can separate the trigger from the read.

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 prerequisite sequence: call get_tracked_questions first, show the user the questions, and offer to update them via set_tracked_questions. It also names the follow-up tool (get_ai_visibility) and the timing condition for using it, leaving nothing to inference.

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