Answer Checkup

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

Annotations only declare readOnly/mutation flags, so the description must carry the money semantics — and it does: exact prices, settlement only on delivery, idempotent retry with no double charge, and the payment-cap caveat. This is precisely the context an agent needs before triggering an irreversible spend.

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?

Price and payment model are front-loaded, then the call sequence, then edge cases — a sensible ordering. It is dense but nearly every sentence carries operational instructions; the website-comparison sentence is the one low-value line.

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 paid, open-world tool with no output schema, the description covers price, tier selection, the handshake, return shape (JSON report plus private link), retry safety, and client configuration. Nothing needed 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 86%, so the baseline is 3; the description still adds real value by explaining that `payment` is the base64 PAYMENT-SIGNATURE obtained from the first, payment-free call, and that `prompts` are answered before generated questions fill to 25. Only `category` remains undocumented in either place.

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 resource (the paid AI visibility report) with concrete tiers and prices, and identifies it as the paid counterpart to the website reports. An agent can tell immediately this is the x402-gated purchase path, distinct from scan_site and get_scan_details.

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 two-step invocation protocol: call once without `payment` to obtain x402 requirements, then call again with identical arguments plus the base64 signature. It also prescribes behavior for the failure case (retry with the same payment) and for a client payment cap (raise to 49 USDC for Full).

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

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

Adds substantial context beyond the annotations: exact price (2.99 USDC, scheme exact), settlement only on completion, and a no-double-charge guarantee with an explicit retry path. The annotations already flag a write/paid operation (readOnlyHint=false, destructiveHint=true), and the description explains the monetary consequence rather than contradicting it.

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 price and mechanism, then the behavior, then the retry rule — a logical order with no filler. The clause 'the same $2.99 scan details as on the website' is mildly redundant with the opening price statement.

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 covers return values (every check, score breakdown, prioritized fixes as JSON), the two-phase payment protocol, settlement conditions, and retry semantics for a two-parameter open-world tool. An agent has everything needed to invoke it correctly in both phases.

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; the description goes beyond the schema by explaining that `payment` is intentionally omitted on the first call and reused verbatim on retries. That adds real semantic meaning to the otherwise opaque base64 PAYMENT-SIGNATURE parameter.

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: runs an AI readiness scan for one website and returns checks, score breakdown, and prioritized fixes as JSON, plus the paid/x402 framing. It is clear what the tool does, but it never names when to prefer it over sibling scan_site or get_report, leaving the boundaries to inference.

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 explicit call sequencing — first call without `payment` to obtain x402 requirements, then call again with `payment` — plus a retry rule with identical arguments on failure or timeout. What's missing is guidance on when to use this paid tool versus the free-sounding scan_site or the get_report sibling.

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

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

Annotations already declare openWorldHint=true and destructiveHint=false, so the safety profile is partly covered. The description adds real value beyond them by disclosing the exact checks performed, the return format (score + grade), and the monetization/upsell path (a link to unlock prioritized fixes for $2.99), which the annotations do not reveal.

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?

Two sentences, front-loaded with the 'Free' framing and then the check list plus return summary. The long parenthetical crawler list is dense but each item is informative; nothing is redundant or padding, though the enumeration could be slightly tighter.

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 single-parameter tool with no output schema, the description adequately covers what is inspected and what comes back (score, grade, unlock link). Minor gaps remain around error behavior and whether the page is fetched live, but nothing critical for correct invocation 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 description coverage is 100% with a single well-documented url parameter (including a format example), so the schema carries the semantics. The description adds no parameter-level detail beyond what is already structured, which matches the baseline 3.

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 names a specific verb (checks) and precisely enumerates the resource set: robots.txt AI-crawler rules, llms.txt, schema.org JSON-LD, title/meta description, raw-HTML content, and sitemap. It also states the output shape (0-100 score and grade), so an agent knows exactly what the tool does 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?

Usage is only implied: the leading 'Free.' signals this is a no-cost entry check, and the mention of a $2.99 unlock hints that deeper analysis lives elsewhere. There are no sibling tools to route against, but the description never states when to prefer this scan versus other approaches or what conditions make it inappropriate.

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