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

Very rich beyond annotations: it states it returns no answers, that platforms citing no sources count as not measured, that fewer than 3 measured platforms makes the run unsound, and that this call charges nothing while payment happens via MPP/HTTP 402 with a Stripe token. The charge-only-if-controls-pass rule and the read-only, no-charge framing are consistent with readOnlyHint and destructiveHint=false.

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?

The question hook is front-loaded and each sentence carries operational weight: what is measured, what is not returned, soundness rule, payment flow, billing condition. It is dense but slightly long, and some phrasing is promotional rather than purely informational.

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 still explains the return payload (measurement plus payment_url, price, instructions) and the downstream payment step. It also flags the failure mode (unsound run under 3 measured platforms) and the billing guarantee, so an agent knows exactly what happens after invoking.

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 subdomain rule. The description reinforces that the question must be a real buyer question asked live with web search on, but adds no format, length, or validation semantics beyond the schema.

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?

The description opens with a concrete question that defines the measurement: whether a domain is cited by ChatGPT, Claude, Gemini and Perplexity for a buyer question. It then enumerates exactly what the result contains (per-platform citation, position, platform count, top competing domains), which distinguishes it from siblings like run_peer_benchmark or search_cultmath.

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?

Usage context is clear: ask a buyer-style question about a domain's AI citation footprint, and expect a quote-stage tool that must be followed by a POST to payment_url. It does not explicitly name alternatives or say when a sibling tool is a better fit, so it stops short of the 5 bar.

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