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

With no annotations, the description fully discloses behavioral traits: charges $0.25 one-time, is a pure pass-through, never holds keys/signs/settles, returns a settlement receipt, probe fees are non-refundable, probe_report never contains verbatim third-party responses, and no charge if the fresh run cannot be produced. This is far beyond typical side-effect disclosure and covers both payment and probe behavior comprehensively.

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 paragraph, but every sentence carries necessary operational detail for a complex two-phase payment flow. It is longer than the average tool description, but the complexity justifies the length. Slight reduction could be achieved with bullet points, but the content is efficient and free of 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?

For a complex tool with 4 parameters, a nested object, and no output schema, the description covers the full invocation lifecycle, pricing, failure semantics, probe behavior, and safety guarantees. It leaves nothing critical undefined given the tool's complexity, and no output schema is needed because the description already indicates what the report contains (assessment report and optional probe_report).

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?

Although the schema has 100% description coverage, the description enriches parameter semantics significantly. It explains the payment_signature_b64 lifecycle (omit to get challenge, include to get report) and details the probe object's pricing, behavior when probing is armed/not armed, and safety guarantee about not exposing verbatim bodies. This adds meaning beyond the schema's property 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 opens with 'Run a fresh, PAID AI assessment comparing a shortlist of already-listed x402 services for a stated need,' immediately stating the verb, resource, and scope. It clearly distinguishes itself from get_service (free read of existing assessment) and search/find 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?

Explicitly contrasts with 'reading an already-computed assessment stays free via get_service' and explains the two-step payment flow: first call without payment_signature_b64 to receive the challenge, then call again with the same parameters plus signature. It also details when the optional probe applies and when it is ignored.

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 burden. It discloses return content for both modes (status, uptime windows, response time, consecutive failures, daily snapshots) and adds the notable caveat 'No money fields.' This provides solid behavioral transparency, though it does not mention error handling or side effects.

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, with three sentences that front-load the purpose, clearly enumerate mode-specific outputs, and include a relevant caveat. Every sentence contributes information without 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?

Given the tool's moderate complexity (two optional parameters, two modes, no output schema), the description comprehensively covers what is returned in each mode. It is self-contained for an agent to understand expected results and use the 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 schema descriptions already cover both parameters fully (100% coverage). The description reinforces that 'slug' toggles modes and that 'uptime_period' applies to single-service daily snapshots, but it does not add meaning beyond what the schema already states, so a baseline score of 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 checks live health of x402 services, and distinguishes two modes: directory-wide snapshot without slug, and per-service report with slug. This specific verb+resource combination effectively differentiates from siblings like search_x402_services and get_service.

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 when to use each mode (no slug for snapshot, with slug for detailed report) but does not explicitly mention alternatives or exclusion criteria. However, the context of health checking is clear enough that an agent can decide when to invoke this vs. other 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?

With no annotations provided, the description carries the full burden of behavioral disclosure, and it excels. It details the ranking weights, the compliance cap (0.6 floor), the conservative undercount of traction, pro-quota attribution for shared payTo addresses, renorm when terms are missing, the 30-day settlement recency requirement, and that top_buyer_share_30d does not enter the score. It even discloses versioning incomparability (ranking_version 2 vs 1), which is a subtle behavioral caveat an agent must know.

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 paragraph that contains a great deal of necessary nuance, but it is not structured for scanning. It front-loads the core purpose, yet the long sentences and parentheticals (e.g., 'a fact about the payment envelope, not a judgement on the service') make it harder to parse than it could be. Every sentence does earn its place, but the wall-of-text format hurts conciseness.

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 tool's complexity (8 optional params, no output schema, no annotations), the description is exceptionally complete. It covers the core return concept (ranked recommendations), the specific output fields (top_buyer_share_30d, ranking_version), the optional facilitator context flag, and the behavior of missing/renormalized weights. An agent can fully anticipate what the tool will do and return without needing additional documentation.

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 already provides 100% parameter descriptions, well above the 80% threshold for baseline 3. The tool description adds no further detail about parameter semantics—it only restates concepts like 'filtered by category and network' that the schema already covers. Since schema does the heavy lifting, baseline 3 is appropriate; the description doesn't need to repeat parameter-level syntax.

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 specific verb+resource: 'Recommend the best x402 service(s) for a need.' It then enumerates ranking criteria (reliability, compliance, price, traction) and filters (category, network), making the tool's role unmistakable. This clearly distinguishes it from sibling tools like search_x402_services or get_service, which are about discovery and retrieval rather than ranked recommendation.

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 establishes clear context: use this tool when you have a need and want a ranked recommendation, with optional filters. It explains the default behavior and the 'prefer' tie-breaking emphasis. However, it never explicitly states when NOT to use this tool or names alternatives, so it falls short of full guidance; it doesn't say 'for raw search use search_x402_services' or exclude cases where the ranking logic is undesirable.

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 burden of behavioral disclosure. It clearly discloses the verification flag semantics ('on-chain' vs 'listed'), the UTC midnight reset of *_24h fields, that all volumes are in USD, and the per-facilitator scope. These are non-obvious behavioral traits that would significantly affect data interpretation. It does not mention pagination or rate limits, but for a read-only metrics tool, the key behavioral caveats are covered.

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 core purpose and proceeds logically through return values, caveats, optional features, and scope. Each sentence provides useful information, though the verification flag explanation is slightly redundant ('on-chain' repeated). It is a bit long but remains efficient and well-organized.

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 there is no output schema, the description does a good job explaining return values (USD volume, transaction counts, verification flag) and the time ranges. It also covers the important caveat about 24h fields and the optional breakdowns. It doesn't provide a full response structure but gives enough context for an agent to understand what to expect and how to interpret the data.

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 67%, below the 80% threshold, so the description should compensate for the undocumented page and per_page parameters. The description does add valuable semantics for timeframe (explaining the 24h quirk and sort order), and mentions optional timeseries and per-chain breakdowns. However, it fails to explain pagination parameters at all, leaving a gap. The added value is moderate 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 states a clear verb-resource pair: 'Get on-chain-verified settlement volume per x402 facilitator.' It explicitly distinguishes this from sibling tools by noting it is per-facilitator, not per-service, and calls it 'the core x402-list metric.' This makes it immediately clear what the tool does and how it differs from search_x402_services, get_service, etc.

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 strong usage context: it identifies the tool as the core metric for the x402 list, advises preferring 7d for a stable recent-activity read, and explains the 24h field reset behavior. It stops short of explicitly naming alternative tools for other use cases, but the per-facilitator vs per-service distinction implies when not to use it. This is clear context without explicit 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?

Even without annotations, the description discloses a key behavioral nuance: the per-endpoint `price` field is a raw on-chain atomic token amount, not US dollars, and clarifies that prices are in USD. It also implies that include_series is off by default, but omits auth or error behavior, which is acceptable for a read-only getter.

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 yet information-dense. It front-loads the core function, provides usage guidance, and finishes with a critical price-unit warning. Each sentence earns its place, though it is slightly longer than the bare minimum.

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 only two parameters and no output schema, the description gives a comprehensive account of the returned fields and clarifies the price units. It lacks error handling or pagination details, but for a single-service getter, it is sufficiently 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 schema already provides 100% coverage for both parameters, describing slug and include_series with defaults. The tool description does not add parameter-specific meaning beyond what the schema states; the price caveat relates to the response, not the parameters. Baseline 3 applies due to high 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 opens with a specific verb and resource: 'Get full detail for one x402 service by slug' and enumerates the exact data returned (live status, uptime, response time, networks, endpoint prices). This clearly distinguishes it from sibling tools like search_x402_services, which lists services.

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 explicitly says 'Use after search_x402_services to inspect a specific service,' providing a clear when-to-use directive. However, it does not mention when not to use it or offer alternatives like check_health or find_best_service, so it falls 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 carries the burden and does disclose useful behavioral traits: it returns service summaries with price (USD), uptime, status, and verification, and prices are in US dollars. It does not cover pagination or error behavior, but for a read-only search this is reasonably transparent.

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 primary action. Every sentence provides value: what it does, what can be filtered/sorted, and what it returns with a currency note. No filler or 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?

Given 9 parameters and no output schema, the description adequately summarizes the return content and supported filters/sorts. It does not explicitly describe pagination, but the schema defines page and per_page, so this is not a critical omission. Overall complete for a search tool of this complexity.

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 high at 78%, so baseline 3 applies. The description mentions filterable fields (free-text, category, network, live status, signable, sort) but does not add semantic meaning beyond what the parameter descriptions already provide, such as the meaning of 'signable' or the values for 'status'.

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 'Search and filter the x402-list directory of services that accept x402 payments,' which clearly states the verb (search/filter) and resource (directory). This distinguishes it from siblings like get_service (specific service) and find_best_service (optimized selection).

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 conveys a clear use case: searching and filtering the directory by various criteria. It does not explicitly name alternative tools or exclusionary conditions, but the context is sufficient to understand when this is appropriate compared to siblings.

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