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

Annotations already cover the read-only/idempotent/open-world profile, and the description layers on non-obvious operational facts: 0.005 USD USDC via x402 on Base or Solana, unpaid calls return payment options rather than failing, unreachable sites are not charged, and results come with an EAS attestation on Base. This is exactly the cost/auth/billing context an agent needs before invoking a paid call.

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?

A single dense paragraph that front-loads what the report contains, then usage, then price and failure behavior. Every clause carries information, though the source list (RSL, AIPREF, TDMRep, C2PA) is long enough to make the sentence borderline overloaded.

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?

An output schema exists so return structure need not be described. Combined with the annotation profile and full schema coverage, the description covers everything an agent must know before calling: what it returns conceptually, what it costs, what happens without payment, and caching behavior.

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%, so the baseline is 3, but the description adds real semantics for two parameters: what happens without payment (explains `pay`) and that the default result is cached (implies the `fresh` behavior). Domain format itself is left to the schema, which already documents it well.

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 ('Full AI-consent report for a domain') and enumerates exactly what is aggregated: robots.txt per AI bot, RSL, AIPREF, TDMRep, noai meta, llms.txt, C2PA, score and stance. It does not explicitly differentiate itself from the near-sounding siblings ai_consent_score or can_ai_use, which is the only missing piece.

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 a clear trigger ('Use it before crawling, training on or ingesting a site') and explains the no-payment path (returns x402 payment options) and the not-charged case. It stops short of naming which sibling to use for a cheap score or a quick yes/no check.

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