Lumière PayCheck

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint=false and destructiveHint=false, so the safety profile is covered; the description reinforces it with 'Read-only, free, no parameters' and adds the useful scope boundary that it reveals nothing about any individual endpoint. The 'free'/'no parameters' notes are mild restatements rather than new behavioral depth, so this sits just below the top.

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 tight sentences, front-loaded with the purpose and the return content before the routing guidance. The trailing 'Read-only, free, no parameters' clause duplicates annotation data and could be trimmed, keeping it short of a 5.

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?

An output schema exists, so return values need not be specified, yet the description still names the key fields. With annotations carrying safety and the description carrying scope, routing, and usage context, an agent has everything needed to select and call this tool 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?

The tool takes zero parameters, so the baseline is 4. The description confirms 'no parameters', which correctly sets the agent's expectation that it can be called bare, though there is no parameter semantics left to explain.

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 (get an overview of the whole monitored x402 catalog) and enumerates exactly what it returns: endpoint count, verdict distribution across named buckets, and last-computed times. It explicitly distinguishes its scope from per-endpoint tools, so an agent can tell it apart from all five 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?

Gives an explicit use case (context or reporting) and an equally explicit when-not with named alternatives: 'It says nothing about any single endpoint: use check_endpoint for one endpoint, top_endpoints for a ranked list, or check_payment before paying.' Nothing is left to 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?

Annotations already declare readOnly/idempotent/non-destructive, and the description adds substantial context on top: it is free, reflects monitoring on a 30-minute cadence plus real test payments, fresh endpoints can return 'insufficient_data', and out-of-catalog endpoints return monitored: false rather than an error. These are behavioral traits an agent cannot infer from annotations or schema.

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 return payload, then routing guidance, then operational caveats. Despite being several sentences, each one carries distinct decision-relevant information with no restatement of the name or schema.

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?

An output schema exists, so return values need no further explanation; the description nonetheless defines the verdict enum values (proceed, caution, avoid, free, insufficient_data), which is exactly the interpretive context a caller needs. Edge cases for unknown and brand-new endpoints are both 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?

Schema description coverage is 100% and the single url parameter is fully documented in the schema (full URL including path, as the agent will call it), so the description correctly does not re-explain it. The description adds no format or normalization detail beyond the schema, 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 ('Get the trust verdict for one x402 endpoint') and enumerates the concrete outputs: score, grade, verdict, uptime, delivery-test status, payout-wallet incidents. It is immediately distinguishable from check_payment, top_endpoints, and get_full_report without opening any 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?

Gives explicit routing: use this when judging trustworthiness before a price quote exists; use check_payment when you already hold the 402 quote (amount and payTo) and are about to pay; use top_endpoints to discover rather than check a known endpoint. The when/when-not conditions and the alternatives are all named.

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 cover read-only/idempotent safety, and the description adds value beyond them: what specifically triggers denial (trust verdict, cap, monitored price, payTo mismatch), that it neither makes nor blocks the payment, and that it is free. It even flags the paid /v1/authorize API for teams needing spend limits and receipts.

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 decision and return shape, then routing and edge-case handling in compact sentences. The closing sentence promoting the paid /v1/authorize API is the only part that reads as upsell rather than operating guidance.

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?

An output schema exists so return values need not be detailed, yet the description still names the allow-flag contract and what to do with denials. For a read-only decision tool with 100% schema coverage, nothing an agent needs to call 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 100% and all seven parameters carry descriptions including defaults and atomic-unit examples, so the schema does the heavy lifting. The description reinforces which parameters come from the 402 quote but adds no format or default detail beyond the schema, matching 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?

States a specific verb ('Decide whether a specific x402 payment should go through') plus the concrete return contract ('allow true/false with reasons'). It explicitly separates itself from the sibling check_endpoint, so an agent can route without opening either 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?

Gives explicit when-to-use ('right before paying, with the amount, payTo, and network from the quote'), an alternative ('check_endpoint if you only want an endpoint's grade without a quote'), and a behavioral rule for the negative case ('If allow is false, report the reasons to the user rather than paying').

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 (readOnly, idempotent, non-destructive, closed-world), and the description adds genuinely new behavior: the returned report is itself a payable x402 endpoint, that payment happens through the agent's own x402 client, and that unmonitored endpoints return 404 and are never charged. The billing and error behavior are exactly the kind of context annotations cannot 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?

It is front-loaded with the purpose, then the return values, then the exclusivity condition and the 404 caveat — good ordering with little redundancy. It runs slightly long for one parameter, but every sentence carries information the agent needs.

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?

An output schema exists, yet the description still summarizes the return shape (report URL, price, network) and covers the purchase path and unmonitored-endpoint failure mode. For a single-parameter read tool, nothing an agent needs 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?

There is a single parameter and the schema already documents it at 100% coverage ('Full URL of the x402 endpoint you want the paid report for, including path'). The description only reinforces the 'one endpoint' scope without adding format or syntax detail, so the baseline of 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?

The description gives a specific verb and resource ('Get instructions for buying the detailed paid report on one x402 endpoint') and enumerates exactly what the report contains (score breakdown, price quote, wallet/price history, test-payment results). It also explicitly states what the tool is not ('it doesn't buy the report itself'), which separates it cleanly from any purchasing sibling.

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 names the alternative (the free check_endpoint result) and the precise condition for escalation ('only when the free result isn't enough and the user wants the full history'). It also clarifies the reporting vs. buying boundary, so the agent knows this call alone won't complete a purchase.

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 only declare the safety/idempotency profile; the description goes further, disclosing the one-vote-per-buyer-and-payment rule, the 24-hour window, that repeats are ignored, and the downstream consequence that multiple independent buyer reports trigger a paid re-test that alone can change a grade. This is real behavioral context beyond the structured fields and is consistent with idempotentHint=true and readOnlyHint=false.

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 core action and tightly packed, with every clause carrying routing or behavioral information. It is dense enough that some nuance (single-use vs. per-payment vote) takes a second read, but there is little waste.

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?

An output schema exists, so return values need not be described. The description covers invocation timing, preconditions, exclusion conditions, deduplication semantics, and downstream effects, leaving no material gap for correct invocation.

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, but the description adds meaning by specifying where the required receipt comes from (the allow decision / paid /v1/authorize API), which clarifies provenance beyond the schema's terse 'returned with the allow decision'. It does not elaborate on problems/httpStatus/tx, but those are well documented in the schema.

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+resource (report whether a paid x402 call delivered) and names the exact receipt source (Lumière PayCheck allow decision via /v1/authorize). It explicitly separates itself from siblings with 'Not for checking endpoints (use check_endpoint or check_payment).'

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 when-to-use ('Use it once, right after paying, only when you have such a receipt') and when-not ('skip it if you paid without one, or if the user asked you not to report'), plus the alternative tools for the endpoint-checking case. Nothing is left to 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?

Annotations already declare readOnlyHint, idempotentHint and non-destructive behavior, so the safety profile is covered. The description still adds useful operational context: it is free, read-only, filtered to incident-free endpoints, and rankings refresh as monitoring runs every 30 minutes. It does not describe ordering/pagination behavior beyond 'best first', so it stops short of 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?

Three sentences, each earning its place: the first defines the resource and output, the second gives the use case, the third handles routing, cost and freshness. The scoping and routing information is front-loaded with no 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?

An output schema exists, so return values need no explanation. The description covers selection criteria, ordering, freshness cadence, cost, safety profile and sibling routing — everything an agent needs to call this 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 100% with a single optional 'limit' parameter (1-50, default 10), so the schema already documents the parameter fully. The description adds nothing about how limit interacts with ranking or whether truncation occurs, so 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 ('List the x402 endpoints that are currently safest to pay') with the exact filter criteria (verdict proceed or caution, no payout-wallet incidents) and returns score, grade, verdict and test-payment status. It clearly distinguishes itself from check_endpoint and check_payment by naming both 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?

Explicitly says when to use this tool ('discover reliable endpoints or pick between providers') and routes to alternatives for the two adjacent cases: check_endpoint for evaluating one endpoint and check_payment for approving a payment. No inference is required.

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