ghost-x402-market-intel-vet-schema

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

With no annotations, the description carries the full burden, and it does an excellent job. It discloses the paid nature ('Paid per call via x402'), the two‑step process ('Omit it to receive the payment terms; call again with it to run the tool'), a free preflight endpoint with rate limit ('free preflight at /v1/commerce/search/preflight (3/day)'), and the return structure ('USE/WATCH/AVOID with the exact call, a fallback, valid_until and recheck_when'). This goes well beyond what a schema or annotations would typically provide.

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 description is dense but every sentence serves a purpose. It is front-loaded with the core purpose and usage, then details the evidence and return structure, then the cost/preflight. It is not overly verbose, but a few sentences pack multiple ideas. The structure is logical and scannable, earning a 4.

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?

Despite lacking an output schema, the description explains the return format, the payment flow, the need for a payment signature, and the preflight option. It covers the main triggers for re‑consultation. It does not mention error handling or limits beyond the preflight, but for a tool of this complexity it is fairly complete. A 4 reflects that it covers the essential agent needs without exhaustive edge cases.

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 86%, so the baseline is 3. The description does not add extra meaning to the parameters beyond what the schema already specifies (e.g., network, capability, min_payers). It explains the ranking logic (independent payers, calls-per-payer, etc.) but that is not parameter semantics. No additional parameter-level guidance is given, so a 3 is appropriate.

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 clearly states the tool's job: 'Decide which x402 provider to pay'. It specifies the resource (x402 providers) and the action (decide/rank/return verdict). It distinguishes itself from siblings by describing a search-and-decision function, though it does not explicitly name alternatives. It is more specific than a tautology, earning a 4.

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?

The description provides explicit conditions for when to use the tool: 'Consult when the provider is unknown, when a decision you hold has passed its valid_until, or when the price, health, verdict or funding of one materially changed.' It also advises when not to use it ('reuse a held decision until it expires or a trigger fires, rather than asking again'). However, it does not mention sibling tools as alternatives, so it lacks explicit exclusion guidance but still offers clear context.

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?

With no annotations, the description carries the burden and it does disclose the key side effect: 'Paid per call via x402.' It also describes the signed receipt output. It does not detail the two-step omit-signature/call-again flow, but that is covered in the schema, so the description adds meaningful behavioral context without contradiction.

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?

Three sentences, front-loaded with the core question, and no wasted words. It packs scope, usage, output, and cost into a compact description.

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?

Given no output schema, the description does a good job by naming the verdict enum and signed receipt. Combined with the self-documenting schema, the agent has enough to decide when to call and roughly what will come back. A full response shape would make it a 5, but it is otherwise complete.

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 adds thematic context (endpoint liveness, quote-vs-advertised price) that maps to endpoint_url and advertised_amount, but it does not add parameter-level detail beyond what the schema already provides.

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 action ('vetting' a seller before payment), names the exact context (unknown x402 seller, payment address already in hand), and lists what it checks. It also names the verdict outputs, which distinguishes it from sibling search/freshness tools.

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 clear usage context: 'Use when one named provider or payment address is already in hand and you need a verdict before you pay it.' This implies it is not for discovery, but it does not explicitly name alternatives or state when-not-to-use, so it stops short of a 5.

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?

With no annotations, the description fully carries the transparency burden: it states the output is 'not advice' but an enforceable decision, that unknown economics stay UNKNOWN and are never invented, and that derived values never override caller-stated values. It also discloses the feedback loop (only /v1/gate/outcome feeds success rates), the pricing/free conditions, and the refusal behavior when a cheaper provider succeeds less often. These are meaningful behavioral traits beyond what schema annotations could convey.

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 description is front-loaded with the tool's purpose and timing, then layers behavioral rules, economic inputs, and payment mechanics. It is a long, dense single paragraph with some stylistic repetition (e.g., 'never invented' appears in both description and schema), but nearly every sentence adds substantive guidance. The length is largely justified by the tool's complexity.

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?

Given 14 parameters, no annotations, and no output schema, the description covers the full workflow: when to call, what verdicts to expect, what inputs matter, how pricing/free cases work, and what to do afterwards. Combined with the rich input schema, an agent has enough context to invoke the tool correctly and interpret the high-level result categories. The per-verdict handling is left to the payment path, which the description explicitly states.

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 only 36%, so the description needs to compensate, and it does meaningfully. It names the caller's economic inputs (customer_revenue, value_of_success, max_budget, required_margin, failure_cost, switching_cost), explains revenue_models derivation rules per type, and clarifies that RETURNS_ROI's expected_return is caller-owned. It also advises preferring the LIVE 402 amount for provider_candidates. Some parameters such as task_id and currency are left entirely to the schema, so the compensation is strong but not complete.

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 precise, action-oriented role: 'Call this immediately before your agent pays an x402/API provider' and names the exact return verdicts (ALLOW / FALLBACK / DECLINE / INSUFFICIENT_EVIDENCE). It explicitly distinguishes itself from advice and from ranking, making its unique function clear. The sibling tools are unrelated (commerce search/vet/schema freshness), so there is no ambiguity in the tool's domain.

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?

The description gives an explicit temporal instruction ('immediately before your agent pays') and a follow-up protocol ('Report the result afterwards to /v1/gate/outcome'). It also explains the payment flow: omit payment_signature to receive terms, call again with it to run, paid per decision or prepaid, and free for cached decisions or INSUFFICIENT_EVIDENCE. This is enough to route an agent through the correct sequence without additional inference.

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?

With no annotations provided, the description carries the full behavioral burden, and it discloses important operational facts: it is paid per call via x402, it is a 'pre-spend' recheck, and it returns a DSSE-signed receipt. It does not detail failure modes or side effects, but the read-only 'check' framing plus billing behavior is strong.

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 description is compact and front-loaded, with the core question in the first sentence and the usage trigger and billing behavior in the following sentences. Every sentence earns its place and there is no redundant filler.

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?

It covers purpose, usage, and payment behavior well, but there is no output schema and the description never explains what the response contains, such as whether it returns a new fingerprint, a changed/unchanged indicator, or the signed receipt. That is a meaningful gap for an agent invoking a paid tool.

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%, so the schema already documents url, known_fingerprint, and payment_signature. The description adds contextual flavor about a held fingerprint and payment, but does not materially go beyond the parameter descriptions already present.

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 clearly identifies a specific resource ('published JSON Schema or OpenAPI document') and a specific operation ('changed since a fingerprint you hold'), so an agent can tell this is a freshness/recheck tool. It does not explicitly differentiate itself from the sibling tools, but their names and this tool's schema-focused wording make confusion unlikely.

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?

It gives an explicit trigger: run when a provider's published contract may have moved before paying again. It does not list exclusions or alternatives, but the stated usage context is clear enough to guide selection.

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?

With no annotations, the description carries the full behavioral burden and does it unusually well: multi-provider execution with failover, refund-as-credit when a search fails to return, a DSSE-signed receipt naming the serving provider, and the fact that no provider account or API key is needed. These are exactly the non-obvious traits an agent could not get from 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?

The core purpose is front-loaded in the first sentence, and the failover/refund/receipt points are genuinely informative, but the 'Three things most paid search tools do not do' framing and the repeated payment reassurances are marketing padding that inflate the length without adding callable detail.

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, and the description compensates by enumerating the returned fields and the normalized shape, plus the payment lifecycle. It stops short of latency, result-cap behaviour, or error modes beyond the refund promise, which keeps it from a 5.

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%, so query, country, language, results and payment_signature are already documented in the schema. The description adds no syntax, format or edge-case detail (e.g. result caps, country code expectations) beyond what the schema provides, so the baseline 3 applies.

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 ('Search the web and get the results') and enumerates the returned artifacts (organic hits with title/url/snippet, answer box, knowledge panel, related questions). It is clearly a web-search tool, but it never explicitly contrasts itself with the sibling ghost_commerce_search, leaving that distinction to inference from the name.

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: 'in ONE payment', 'no second payment', and the payment_signature semantics convey the two-step pay-then-run flow, but the description never states when to pick this tool over ghost_commerce_search or the other siblings, nor any prerequisites beyond the payment.

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