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

Goes well beyond the annotations by disclosing that this is an asynchronous run that takes about a minute and returns a run_id for polling, plus concrete rate limits (two a day per address) and tiered allowances. The annotations only flag non-read-only, non-idempotent, open-world; the description supplies the operational context an agent actually 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 scope before the operational details, and each sentence carries weight (scope, async flow, quotas). It is dense and somewhat run-on with nested parentheticals, but nothing is wasteful.

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 an output schema present, return values need not be described; the description instead covers the async lifecycle, the follow-up call, and quota behavior, which is exactly what remains ambiguous. Nothing an agent needs to invoke it correctly 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 coverage is 100% and the single url parameter is already documented with examples ('example.com or https://example.com'), so the description adds little param detail. Baseline 3 applies when the schema does the heavy lifting.

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 and resource ('AI visibility audit') and enumerates exactly what it covers: identity files, crawler policy, schema graph, page health, and answer-engine naming. It is clearly distinguishable from siblings like atlas_search or check_identity.

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 routes the agent to the follow-up tool ('call get_analysis with that id') after the run completes, and specifies the conditions under which different account tiers apply. When-to-use and the alternative are both stated.

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