Agent Verification Utility

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

Annotations already declare readOnlyHint and idempotentHint, and the description adds topical context (free request validation, recipes, limits, paid MCP path) that clarifies what the tool exposes. It does not contradict annotations, though it does not detail additional behavior like return format or whether any computation occurs.

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 a single sentence, front-loaded with the verb 'Describe' and efficiently lists all covered topics in a comma-separated list. There is no wasted verbiage or repetition.

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 zero-parameter, read-only informational tool with no output schema, the description adequately covers the essential context: when verification is or isn't useful, validation, recipes, limits, and the premium paid path. The sibling tools provide operational context, and this description stands alone as 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?

The input schema has zero parameters, so a baseline of 4 applies. The description does not need to explain parameters since none exist, and no additional semantics are missing.

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 uses the specific verb 'describe' and clearly identifies the resource: the Agent Verification Utility. It enumerates distinct facets (usefulness, non-usefulness, validation, recipes, limits, paid MCP path), distinguishing it from operational siblings like verify_evidence and commercial ones like quote_verify_evidence.

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 implies its use for learning about deterministic verification, but it does not explicitly state when to choose it over the sibling tools (e.g., 'use verify_evidence to verify, use this tool for guidance'). No exclusions or alternative tool recommendations are given.

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 read-only, idempotent, and non-destructive behavior. The description adds specific context about what it reads (active revenue goal, funnel, margin, recommendation) and reassures about no side effects, exceeding annotation basics.

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 concise and front-loaded: the first sentence states the core purpose and key outputs, the second sentence adds a safety clarification. No redundancy.

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 zero-parameter, read-only tool with rich annotations, the description is complete—it specifies exactly what data is read and what side effects are absent, making it fully understandable in context.

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?

The tool has zero parameters, so the schema is fully covered by default. The description adds value by describing the data and output focus, which is appropriate for a no-parameter tool.

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 the tool as a read operation ('Read the active revenue goal') with specific resources and outputs, and it is distinct from the sibling tools focused on verify_evidence.

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 clear context that this is a safe, read-only operation and explicitly lists side effects it avoids ('never changes price, spends funds, or sends messages'), though it does not name alternatives or exclusions.

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?

Beyond the annotations (idempotentHint=true), the description adds that the tool 'create[s] or reuse[s] a bound quote,' reinforcing idempotency, and clarifies that it does not perform payment but only returns the request. The safety warning not to pay until policy matches is valuable additional context. No contradiction with annotations.

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 two sentences, front-loaded with the core action, and includes only high-value information. No redundant or filler content.

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?

The tool is complex with nested schema and no output schema, but the description states its main purpose and return type ('exact HTTP request'). It misses explanations of parameters and the meaning of a 'bound quote.' Given the complexity, the description is adequate but leaves some gaps.

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 0%, so the description must compensate, but it does not explain the input parameters like idempotency_key, intent, or spend_policy. It references 'binding, price, network, asset, payTo, and expiry' which are not directly mapped to schema properties and appear to relate to the quote response rather than the request inputs. The parameter names are somewhat self-explanatory, but the description adds minimal clarity.

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 uses a specific verb ('create or reuse') and resource ('bound quote') and clearly states the deliverable: 'return the exact HTTP request that will produce the x402 challenge.' It distinguishes from sibling tools like quote_verify_evidence or verify_evidence by focusing on preparing the HTTP request rather than executing it.

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 sets a clear context: 'After a successful free precheck.' It also provides a critical usage constraint: 'Do not pay until the binding, price, network, asset, payTo, and expiry match local policy.' However, it does not explicitly mention alternatives or exclusions relative to sibling tools.

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 convey idempotency and non-destructiveness, and the description adds the margin policy condition and 'free quote' outcome. However, it does not clarify whether the tool has side effects (readOnlyHint is false), what happens on policy failure, or whether it writes anything, leaving some behavioral ambiguity.

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 a single, front-loaded sentence that includes the key action and condition. Every word earns its place, with no redundant or filler content.

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 the deeply nested schema and absence of an output schema, the one-line description is insufficient. It does not explain what constitutes a 'complete verification request', what the margin policy is, what the quote contains, or how this relates to sibling tools, leaving significant gaps for an agent to use it correctly.

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 0%, and the description mentions no parameters. The schema contains complex nested objects like 'intent' with 'request', 'spend_policy', and 'precheck_receipt_digest', but the description offers no guidance on their meaning or relationships, failing to compensate for the lack of schema descriptions.

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 states a clear verb ('Validate') and resource ('complete verification request'), and specifies the outcome ('return a free quote') conditioned on margin policy. This distinguishes it from the sibling verify_evidence by focusing on the pre-purchase quote step, though it does not explicitly name alternatives.

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 implies a use case (obtaining a free quote before commitment) and a condition (margin policy passes), but it provides no explicit guidance on when to choose this tool over siblings like verify_evidence or prepare_verify_evidence_purchase. There are no stated alternatives or exclusions.

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?

The description adds behavioral context beyond annotations: it requires an explicitly authorized x402 payment, is deterministic, and needs a precheck receipt and bound payment requirement. With annotations already covering idempotency and read-only/destructive hints, this extra context is meaningful and non-contradictory.

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 primary action, and no filler. Every sentence adds critical context: what the tool does, payment authorization, and prerequisites.

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?

The description provides essential workflow context (payment, precheck receipt, bound payment) and mentions the signed evidence return, but lacks details about the complex nested parameters and the output structure. Given the rich schema and no output schema, the description is minimally adequate but leaves the agent to infer much from schema alone.

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 0%, and the description does not explain any parameters directly. It only indirectly hints at precheck_receipt_digest and spend_policy via 'free precheck receipt' and 'bound payment requirement', but the complex nested intent structure (evidence, assertions, idempotency_key) remains unexplained. The description fails to compensate for the 0% schema coverage.

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 a specific verb ('Run deterministic checks') and resource ('return Ed25519-signed evidence'), and distinguishes itself from siblings by emphasizing the paid x402 payment requirement and prerequisites. It is unambiguous about what the tool does and differs from quote/prepare/describe siblings.

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 explicitly states prerequisites ('A free precheck receipt and a matching bound payment requirement are required before signing'), making it clear when this tool should be invoked. It does not name alternatives or exclusions, but the workflow context is strong enough for an agent to understand ordering relative to prepare/quote siblings.

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