Endpoint Diligence

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

With no annotations, the description carries the safety burden. It implies a non-destructive read-only check ('before you pay it', 'verifies', 'inspects') and explicitly mentions live on-chain and network activity. It could be more explicit about potential side effects like RPC calls or latency, but it conveys the operational scope better than most descriptions.

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 dense sentences pack a high amount of information without fluff. The first sentence is a long list but logically organized; the second handles return values. It could be broken into bullets for readability, but it is efficient and front-loaded.

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 compound tool with no output schema, it explains return values (score, verdict, evidence) and lists all major checks. It lacks explicit detail on what 'market baselines' or 'infra hygiene' entail and doesn't mention error handling, but the core behavior and outputs are adequately covered.

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 schema has one param (url) with zero description coverage, so the description must add meaning. It repeatedly references 'the endpoint' and specifies 'x402-metered endpoint', clarifying the expected URL type beyond the generic uri format. It doesn't explicitly define the parameter, but it is strongly implied.

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 purpose: running live diligence on an x402-metered endpoint before payment. It enumerates specific checks (402 compliance, price baselines, on-chain payTo inspection, directory presence, infra hygiene, resale detection) and describes the output, making it unmistakable and distinct from narrower sibling 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?

The phrase 'before you pay it' provides a clear usage context (pre-payment verification), and the list of checks implies when this tool is appropriate. However, it does not explicitly contrast with sibling tools like compare_price or reseller_check, nor state when not to use it.

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 mentions the 'daily radar snapshot' as a data source, implying a read-only comparison operation. However, it does not disclose the output format, potential errors, rate limits, or any behavioral traits beyond what is inferred. With no annotations provided, the description carries full burden but provides only minimal behavioral context.

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, concise sentence that starts with the action verb 'Compares' and contains no extraneous information. It is well-structured and front-loaded.

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 lack of an output schema and annotations, the description is incomplete for an agent to invoke the tool correctly. It does not specify the output format, how to handle the optional parameters, or what constitutes a valid price/category pair. The description explains the core purpose but leaves critical invocation details unspecified.

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 description adds meaning beyond the schema by explaining two modes: either an endpoint URL or a price/category pair. This clarifies how the three parameters (url, category, priceUsd) relate, even though the schema itself has no descriptions. It does not explicitly state parameter combinations or requirements, but it provides useful semantics.

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 function: 'Compares an x402 endpoint's price (or a given price/category pair) against market percentiles from our daily radar snapshot.' It specifies the verb, the resource, and the data source, making it distinct from sibling 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?

No guidance is provided on when to use this tool versus the sibling tools (check_endpoint, reseller_check). The description only implies it is for price comparison but lacks context on prerequisites, exclusions, or alternative choices.

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. It discloses that it's a 'preview' that 'reports confidence... without asserting resale as fact', and mentions matching against 'live unpaid 402 description/schema' implying network fetching behavior. However, it doesn't state whether it's read-only, potential side effects, rate limits, or what happens with incomplete input combinations.

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 dense sentence, but every clause adds substantive detail—purpose, matching sources, catalog recency, output content, and a caveat. It's front-loaded with 'Free possible-reseller preview' and contains no filler, though splitting into two sentences would improve readability.

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 has no annotations, no output schema, and 0% schema parameter coverage. The description gives an overview of matching and output topics, but omits critical invocation details such as parameter combinations, whether any source is required, expected output structure, and limitations. An agent would likely struggle to correctly call this tool without further clarification.

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 clarify parameters. It explicitly mentions 'supplied description and price' and 'endpoint's live unpaid 402 description/schema' (implying url), giving meaning beyond plain property names. But it doesn't explain how the three parameters interact (e.g., whether url alone is sufficient, or whether description and price are alternatives to url), leaving ambiguity.

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 purpose: 'Matches an endpoint's live unpaid 402 description/schema, or a supplied description and price, against a dated catalog of well-known upstream APIs' and reports confidence, signals, and markup math. This distinguishes it from siblings like check_endpoint and compare_price through the reseller-oriented matching behavior, though it doesn't 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 usage context is implied ('Free possible-reseller preview' suggests use when investigating potential reselling), but there is no explicit guidance on when to choose this tool over check_endpoint or compare_price, nor exclusions. It's not completely absent but stays at an implied level.

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