QuietProof

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so safety is covered. The description adds value beyond them by disclosing the call is free and by enumerating the payload categories (schema, example, endpoint, price, purchase flow), which tells the agent this is a heavyweight metadata read rather than a terse lookup.

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 front-loaded sentence with the returned payload listed immediately, plus a terse 'Free.' qualifier — nothing is wasted. The comma-separated enumeration is slightly list-dumpy but every item conveys information the agent would otherwise have to discover.

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, so the description correctly compensates by naming the return payload fields. For a one-parameter lookup with full annotation coverage this is close to sufficient; it only omits what happens for an unknown id (error vs. empty) and any pagination or size caveats.

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?

With 100% schema description coverage and an inline example ('Rulepack/SKU id, for example OAS-01'), the schema carries the parameter burden. The description only reinforces that the id selects exactly one SKU ('one SKU'), adding no format, sourcing, or error semantics beyond that.

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 ('Return the full input schema, example input, output schema, result example, endpoint, price, and purchase flow for one SKU'), so an agent knows exactly what it gets back. It does not name the sibling it replaces or explain its relationship to list_rulepacks (discovery) or purchase_info (which likely also covers price/flow), leaving some ambiguity about overlap.

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?

There is no explicit when-to-use statement or exclusion; the usage is only implied by the returned contents (you need an id, so presumably call list_rulepacks first). The one-word 'Free.' signals there is no cost barrier to calling it, which is a useful nudge, but alternatives are never mentioned.

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 establish that this is a safe, read-only, non-destructive, non-open-world operation. The description adds useful context by specifying the returned information and noting that the operation is free, though it does not describe authentication needs, rate limits, or response format. With annotations covering the safety profile, this is a meaningful supplemental disclosure.

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 with no redundant or wasted phrasing. It conveys the tool's outputs and cost status efficiently.

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 health-check tool with full annotation coverage, the description provides the essential return values and cost note. No output schema exists, so explaining the returned fields is beneficial, though additional details such as expected response shape or auth requirements would improve completeness.

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 parameter semantics are not a concern and the baseline is 4. The description correctly avoids introducing parameter details that do not exist.

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 specific verb (return) and resource (service health, service version, and available audit rulepack count). This clearly distinguishes it from sibling tools such as describe_rulepack and list_rulepacks, which focus on rulepack details rather than service status.

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 diagnostic or monitoring use case by naming health/version/rulepack availability, but it does not explicitly say when to call this versus the rulepack-focused siblings. No exclusions or prerequisites are stated, so the agent must infer appropriate usage.

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 cover the safety profile (readOnlyHint=true, non-destructive, closed-world), so the description's added value is the cost note ('Free') and the fact that each entry carries pricing and input summary — a real behavioral detail agents need before planning. It stops short of saying whether the catalog is static or whether entries are complete vs. truncated.

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 short sentences, with the resource and the returned fields front-loaded before the pricing note. Every clause carries information; nothing is padding.

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 does the necessary work by naming the four fields each entry returns and confirming the call is free. Only minor gaps remain, such as ordering/size of the catalog, which are low-stakes for a no-parameter read.

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 takes zero parameters, so the schema has nothing to explain and the description has nothing to compensate for. Baseline 4 applies; no parameter semantics are needed or 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?

States a specific verb and resource ('List all QuietProof audit rulepacks/SKUs') and enumerates the fields returned (price, endpoint path, description, input summary). It never names describe_rulepack, so the list-vs-detail boundary with that sibling is left implicit rather than stated.

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?

'List all' combined with the sibling name describe_rulepack implies this is the catalog/browse entry point and the sibling is for a single pack, but the description never says so or gives an exclusion. Usage is inferable rather than instructed.

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 readOnlyHint=true, openWorldHint=false and destructiveHint=false, so the safety profile is covered. The description adds value beyond them by declaring cost ('Free.') and by enumerating the informational payload the caller receives, which effectively substitutes for the absent output schema. It does not state the response format or whether the content is static documentation, hence not a 5.

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 sentence that front-loads the verb and topic, then enumerates the covered facets, closing with the cost in one word. Every clause earns its place and nothing is repeated from the title.

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 explainer with no output schema, the description is sufficient: it tells the agent exactly which payment details it will learn and that the call is free. An agent has everything needed to decide to call it and to interpret the result.

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 takes zero parameters, so there are no semantics to document and the baseline of 4 applies. The description correctly implies no inputs are needed by framing the tool as a pure explanation request.

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 ('Explain') and resource (the x402 payment flow for a QuietProof audit on Base), and enumerates the exact facets covered: network, USDC asset, payee, challenge flow, request format. None of the siblings (describe_rulepack, health, list_rulepacks) do anything similar, so the tool is trivially distinguishable.

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 stated content (network, asset, payee, challenge flow, request format) makes clear this is the pre-purchase orientation call an agent should make before attempting an x402 payment, and 'Free.' signals no payment is required to call it. It stops short of an explicit 'call this before X' instruction or naming an alternative, so it is clear context rather than full routing guidance.

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