Agent Weather

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

Beyond the annotations, the description discloses the payment rails and prices, that an unpaid call returns isError with a fresh x402 PaymentRequired object and invoiceId, how to retry via _meta["x402/payment"] or payment_signature, and that unpaid calls cost nothing. The fresh-invoiceId-per-call behavior also explains concretely why the tool is not idempotent, which the annotations only assert as a flag.

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 prose is dense and mostly waste-free, with every sentence carrying information about pricing, scope, or the payment retry loop. The ordering is suboptimal, though: a full sentence on payment rails precedes the statement of what the tool actually answers, so the purpose is not 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?

There is no output schema, and the description compensates by describing the return shape (raw lowest and next-vendor prices, reasons, exclusions, status-page readings). For a nine-parameter filtered-ranking tool the remaining gap is small: it does not say how unset filters behave or how ties beyond 'next vendor' are broken.

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%, so every one of the nine parameters is already documented, including the comma-list format for vendor/capability and the units for the price ceilings. The description adds no further parameter meaning (no defaults beyond include_free, no interaction rules between filters), 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?

The description names a specific verb and resource implicitly but concretely: it answers "Which listed models.dev prices meet these filters, lowest first?" and returns raw lowest plus next-vendor prices with reasons and exclusions. That is enough to separate it from a bare list_models call, but it never names a sibling (list_models, get_price_index) as an alternative, so differentiation is by scope description rather than explicit contrast.

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?

Usage context is clear: it is a paid, per-call query over models.dev listings, and the description explains that an unpaid call is not an error condition to fix but the first step of the x402 handshake. It lacks any when-not guidance (e.g., when to use list_models or get_price_index instead), which keeps it below 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?

Beyond the annotations, the description discloses pricing across two networks, the failure mode (isError plus a x402 PaymentRequired object with a fresh invoiceId), the retry mechanism, and the fact that a new invoiceId is issued per call, which helps the agent understand the non-idempotent behavior flagged by idempotentHint=false. It also says exactly what the successful payload contains, which 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?

Three dense sentences with no filler; the payment contract, the question answered, the payload, and the error/retry path all appear in order. Minor waste comes from restating the price already present in the title, and leading with price rather than purpose makes the first sentence less agent-friendly than it could be.

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, and the description compensates by naming the returned fields and their provenance (sources and timestamps). Payment, error, and retry behavior are all covered, leaving nothing an agent needs in order to call this correctly and 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?

Schema description coverage is 100%, and both parameters are already well documented in-schema, including the vendor-slug-or-model-id duality and the Base64 PAYMENT-SIGNATURE alternative. The description repeats the payment mechanics but adds no new meaning about the provider parameter, 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?

The description states a specific resource and scope: an AI provider's status page plus a 24h internal record, returning raw indicator, incidents, and disturbed-check share. That is far more concrete than the tool name alone, but it never distinguishes itself from adjacent siblings such as get_service_status, get_pulse_providers, or get_x402_health_report, so an agent cannot tell from the text which health tool to pick.

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 invocation contract is explicit: pay per call, omit payment on the first call to receive requirements, and retry with the signed payload in _meta["x402/payment"] or payment_signature. Unpaid calls cost nothing, which clarifies a low-risk path for discovery. The gap is that no alternative sibling tool is named as the right choice when this one is not what the agent needs.

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 supplied annotations (readOnly, openWorld, non-idempotent, non-destructive), the description discloses the payment model and pricing, the exact failure mode for unpaid calls (isError plus a fresh invoiceId in a PaymentRequired object), the retry mechanism, and the shape of the returned data (resolver id, rcode, TTLs, query_ms, observed_at). This is unusually rich behavioral context for a paid, network-dependent call.

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 pricing and paid-call mechanics are front-loaded, then the purpose and return fields, then the payment retry flow — a sensible order with dense, purposeful sentences. It is slightly long, and the pricing detail duplicates information already present in the title, but nothing is genuinely wasted.

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 three-parameter, network-dependent paid tool with no output schema, the description covers everything an agent needs: what is queried, what comes back, what happens without payment, and how to complete payment. No significant gap remains.

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 schema already documents name, types, and payment_signature, including the allowed record types and the instruction to omit the signature on the first call. The description reinforces the payment loop around payment_signature but adds no syntax or format detail beyond what the schema provides, so the baseline 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 names a specific verb and resource (reads raw DNS records for a given FQDN and record types) and frames the single question it answers: 'What DNS records does this name return right now?' It also enumerates the record types and returned fields, so an agent can tell it apart from the payment/ledger siblings without opening the 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?

It gives clear usage context: it is a per-call paid DNS lookup, unpaid calls fail with an x402 PaymentRequired object, and the agent should retry with a signed payload in _meta["x402/payment"] or via the payment_signature argument. It does not explicitly name alternatives or exclusions, but the sibling set contains no overlapping DNS tool, so the only real gap is the absence of an explicit 'do not use for X' statement.

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=true, destructive=false, openWorld=true), and the description adds substantial behavior beyond them: exact per-call price and chains, the x402 payment handshake, that an unpaid call returns isError with a fresh invoiceId rather than failing silently, and that unpaid calls cost nothing. None of this contradicts the annotations, and the return-field list compensates for the absent output 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?

The pricing and pay-per-call framing is front-loaded, then the single question the tool answers, then the return fields, then the error/retry path. Nearly every sentence carries information, though the price is stated twice (title and first sentence) and 'Unpaid calls cost nothing' is partly redundant with the preceding error-handling sentence.

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 two-parameter read tool with no output schema, the definition covers cost, payment mechanics, failure mode, retry path, and returned fields — enough for an agent to invoke it correctly. Remaining gaps are minor: no pagination or rate-limit guidance, no indication of how large the 'tracked domains' set is, and no note on whether a paid call is idempotent or repeatable across invoiceIds.

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%, so both parameters (since, payment_signature) are already fully documented, including the 7-day default. The description only echoes 'since a time' and points at payment_signature as an alternative channel for the signed payload; it adds no format or boundary detail beyond what the schema states. Baseline 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 states a specific verb and resource: 'Which tracked domains changed their public agent-access files since a time,' with 'Raw domain, path, times, hashes, HTTP status, and robots.txt group deltas' clarifying the payload. It implicitly contrasts with the single-domain sibling get_access_policy_reading by scoping to 'all tracked domains,' but never names that sibling, so the differentiation is left to inference rather than made explicit.

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?

Usage is clear: call this to find which tracked domains changed since a time, and the payment flow is spelled out step-by-step (first call without payment yields PaymentRequired + invoiceId, then retry with the signed payload via _meta or the payment_signature argument). What is missing is any exclusion or explicit routing to alternatives such as get_access_policy_reading when a single domain's current policy is wanted.

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 cover safety flags (readOnly, openWorld, non-idempotent, non-destructive); the description adds the pricing model across two rails/networks, the exact failure envelope (isError plus a PaymentRequired object with a fresh invoiceId), the retry affordance, and the cost of a failed call. These are behaviors an agent cannot derive from the annotations and are essential to invoking the tool correctly.

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 prose is dense with real operational content and has no filler sentences. However, it opens with price rather than the tool's purpose, and the pricing information duplicates the title, so the most useful sentence (what files are returned) is pushed to the middle.

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 two-parameter, no-output-schema tool with a non-trivial payment handshake, the description covers cost, failure mode, retry, and the categories of files returned. It stops short of describing the response shape (per-file sections, error payloads on crawl failure) which matters because there is no output schema to fall back on.

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%, so both parameters are already documented, including the tracked-domain constraint and an example. The description does reinforce payment_signature semantics by tying it to the x402 retry path, but adds little beyond what the schema states, 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?

The description states a concrete question the tool answers ("What public crawler/agent-access files does this domain serve?") and enumerates the artifacts returned: robots.txt groups, Content-Signal, llms.txt, well-known JSON, security.txt, TDM headers. That is a specific verb+resource definition an agent can act on. It does not explicitly contrast itself with the sibling get_access_policy_changes, so the reading-vs-history boundary is inferred 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?

It gives a clear operating procedure: call without payment to receive the x402 PaymentRequired object, then retry with the signed payload in _meta["x402/payment"] or the payment_signature argument, and notes unpaid attempts are free. What is missing is routing guidance against alternatives, e.g. when to pick get_access_policy_changes instead, or prerequisites such as the domain having to exist in the free index (that constraint lives only in the schema).

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 readOnly/openWorld/idempotent annotations, the description discloses cost (0.007 RLUSD/USDC), the unpaid-call failure mode (isError with an x402 PaymentRequired object and fresh invoiceId), the retry mechanism, and that failed unpaid calls are free. That is substantial behavioral context. The only shortfall is that it doesn't describe rate limits or expiry of the invoice.

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?

Price and payment model are front-loaded, then purpose, then mechanics, which matches the order an agent needs them. There is mild redundancy (payment terms repeated across title and body, and the question framing is wordy), but no sentence is wasted.

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 one-parameter, read-only aggregator with no output schema, the description covers cost, failure behavior, retry path, and roughly what the payload contains (readings with sources and timestamps). A fuller enumeration of the returned sections would close the remaining gap.

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% for the single optional parameter, so the baseline is 3; the description adds genuine value by explaining the alternative transport (_meta["x402/payment"]) and the two-step first-call/retry pattern. This makes the parameter's role clearer than the schema alone.

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 names a specific verb+resource and enumerates the data domains returned ('raw status-page, XRPL x402, GitHub/npm/MCP readings with sources and timestamps'), which is far more concrete than the vague title. It does not, however, differentiate itself from the many closely related siblings such as get_x402_health_report, get_pulse_providers, or get_service_status, leaving overlap unresolved.

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?

Usage guidance is strong for the payment flow (first call unpaid to obtain requirements, retry with the signed payload) but entirely absent for tool selection: nothing says when to reach for this combined record versus the narrower sibling endpoints. The agent can call it correctly but cannot confidently choose it over alternatives.

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 carries substantial behavior the annotations cannot: exact per-call pricing across two chains, that unpaid calls cost nothing, that the failure mode is isError with a fresh-invoiceId PaymentRequired object, and the retry mechanism. This is consistent with the annotations (readOnlyHint=true for a read of analytics, idempotentHint=false matching the fresh invoiceId per call), so no contradiction arises, and the disclosure is unusually complete for a paid endpoint.

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-loads cost and then the tool's purpose, and every sentence carries information (pricing, question answered, metric list, payment error path, retry). Some density and redundancy with the title's pricing string keep it from being maximally tight, but no sentence is 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?

With no output schema, the description must describe returns, and it does so at a summary level (counts, UA families, 402-to-paid tallies, docs-first vs cold-402) rather than field-by-field. Given only two optional parameters and full annotation coverage, plus thorough payment-flow documentation, this is complete enough to invoke correctly, with the only soft spot being the vague shape of the returned 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 100%, so the schema already documents both window and payment_signature, giving a baseline of 3. The description adds only a little: it clarifies that payment_signature is an alternative channel for the same signed payload and reinforces that it should be omitted on the first call, which the schema already states.

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 names a specific resource and frames the exact question it answers ("How are clients finding and probing Agent Weather discovery files and paid routes?"), then enumerates the concrete outputs: raw first-party counts, UA families, 402-to-paid tallies, docs-first vs cold-402. That is well beyond restating the name. It falls short of 5 because it never names or excludes the closest siblings (get_x402_activity, payradar, get_pulse_facilitator), leaving the agent to infer the boundary from the metric list.

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?

Strong procedural guidance for the payment handshake: call unpaid to get the PaymentRequired object, then retry with the signed payload in _meta["x402/payment"] or the payment_signature argument. However, there is no guidance on when to choose this tool over sibling analytics tools, and no advice on which window to pick for which investigation.

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 cover safety (readOnly, non-destructive, open-world, non-idempotent); the description adds the paid-call cost, the exact unpaid failure contract ('isError with the x402 PaymentRequired object (fresh invoiceId)'), the retry mechanism via _meta["x402/payment"] or payment_signature, and the fact that unpaid calls cost nothing. That is substantive behavior an agent cannot get from the 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?

It is reasonably front-loaded and every sentence carries payment or output information. There is mild redundancy: cost is repeated in the title and again as the first clause of the description, and the payment details occupy more space than the core purpose sentence.

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 must describe returns, and it does so by naming the content (dates, source URLs, retrieval timestamps) and the upstream source. It stops short of describing response shape or coverage gaps (e.g. missing entries for unknown products), which would fully close the loop for a read tool.

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 the model format examples (ubuntu/24.04, python/3.12) and the payment_signature fallback already documented in the schema. The description reinforces 'release line' and the _meta payment path but adds no syntax or format detail beyond what the schema supplies, 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?

The description names a specific verb+resource question: 'What published end-of-support and end-of-life dates are listed for this release line?' and pins the data source ('primary: endoflife.date') with the returned artifact ('raw dates with source URLs and retrieval timestamps'). No sibling tool covers EOL dates, so an agent can select it without ambiguity.

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 frames the one question the tool answers, which is a clear use condition, and it explains the payment prerequisite flow (unpaid call returns PaymentRequired, then retry with signed payload). It does not name an alternative or state when *not* to use it versus siblings, 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?

Annotations only declare read-only/open-world/non-idempotent; the description adds the material facts an agent actually needs — exact price, dual payment rails, that an unpaid call errors with a structured x402 PaymentRequired object containing a fresh invoiceId, and that failed unpaid calls cost nothing. The fresh-invoiceId-per-call detail also coherently explains the idempotentHint=false annotation.

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?

Cost and payment rails are front-loaded, followed by the payload contents and the retry mechanics, so an agent reading only the first sentence already knows the price. A few clauses are dense and slightly awkward ('returns isError with the x402 PaymentRequired object'), but nothing is redundant.

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 carries the return-value burden and does so by listing the template's sections. Price, error behavior, retry path, and payload shape are all covered for a single-optional-parameter paid tool.

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?

Only one optional parameter exists and the schema already documents it at 100% coverage, so the baseline is 3. The description goes beyond the schema by stating that _meta["x402/payment"] is the preferred channel and payment_signature is the fallback for hosts that cannot set that meta key, giving the agent the ordering rationale.

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 names a specific resource — a blank two-way inter-consideration ledger template from FIM 2026 — and enumerates its contents (raw parties, per-duty owed items with open/met/unmet status fields, adjustment slots). That is far more specific than the title alone. It stops short of distinguishing itself from the sibling get_fim2026_schema, so an agent must infer which of the two FIM 2026 tools returns the template versus the 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?

The payment protocol is spelled out well: first call without payment returns a PaymentRequired object with a fresh invoiceId, then retry with the signed payload. But there is no guidance on when to choose this tool over get_fim2026_schema or the other FIM 2026 siblings — usage is only implied by the framing question it claims to answer.

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 readOnly/openWorld/idempotent annotations, the description discloses the paid-call model (0.01 RLUSD on XRPL or 0.01 USDC on Base), the exact failure behavior (isError plus an x402 PaymentRequired object with a fresh invoiceId), the retry path via _meta['x402/payment'] or payment_signature, and that unpaid calls are free. That is precisely the behavioral context annotations cannot express.

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?

Pricing is front-loaded, then purpose, then error/retry behavior, then the free-when-unpaid reassurance—a sensible order with little waste. It is dense and slightly repetitive on payment mechanics, but every sentence carries information.

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 and a single optional parameter, the description still covers what is returned (duty definitions, self-checks, indicators, with the 'not legal advice' caveat) and the exact error shape on non-payment. 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?

Schema coverage is 100% and the single parameter is already documented, so the baseline would be 3. The description adds real meaning by explaining why the parameter exists (hosts that cannot set _meta) and the expect-to-omit-on-first-call workflow, which is more than the schema conveys.

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 the specific verb and resource: it returns the FIM 2026 guidance schema, namely 'raw duty definitions, self-checks, and measurable indicators.' It even frames the single question the tool answers, which is unusually concrete. It does not differentiate against the sibling get_fim2026_ledger_template, so it stops short of a 5.

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?

Usage is implied by the question the tool 'solves,' and the payment-retry flow is spelled out, but there is no explicit when-to-use/when-not guidance and no mention of the closely related get_fim2026_ledger_template sibling. An agent must infer the boundary from the name alone.

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, open-world and non-idempotent, but the description goes well beyond them: exact price (0.02 RLUSD on XRPL mainnet, 0.02 USDC on Base), the failure mode (isError + PaymentRequired with fresh invoiceId), and the explicit reassurance that unpaid calls cost nothing. The fresh-invoice-per-call statement also usefully explains why idempotentHint is false. Only minor gap is that it doesn't say whether an unpaid call consumes any quota or how long an invoice stays valid.

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-loads the most decision-relevant fact (deprecation and replacement), then price, then purpose, then the failure/retry mechanic. Dense but every sentence carries actionable information; the payment channel details are repeated in the title, which is mild 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?

No output schema exists, and the description compensates by listing the returned readings and their provenance fields. For a two-parameter read-only paid endpoint, the description covers cost, authorization path, error behavior, and replacement routing — 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 description coverage is 100%, so the two parameters are already documented; baseline would be 3. The description adds value by explaining the payment_signature argument's role in the retry loop and by naming the _meta["x402/payment"] channel, which does not appear in the schema at all.

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 the specific resource (x402 payment readings for one XRPL payee) and enumerates the returned fields (24h payments, payers, account fields, endpoint 402 readings with sources/timestamps). It also explicitly declares itself a deprecated alias and names the replacement, get_merchant_readings, so an agent can distinguish it from its sibling 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 an explicit when-not-to-use ('Deprecated: use get_merchant_readings') plus the full paid-call flow: first call without payment returns isError plus a PaymentRequired object with a fresh invoiceId, then retry with the signed payload. Both the alternative tool and the alternative payment channel (_meta["x402/payment"] vs payment_signature) are named with the condition that selects each.

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 readOnly/openWorld annotations, the description discloses cost and payment rails, that an unpaid call returns isError with a PaymentRequired object containing a fresh invoiceId, the retry path via _meta['x402/payment'] or payment_signature, and that unpaid calls are free. That is exactly the operationally critical behavior an agent needs.

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?

Price and payment rails are front-loaded, then the question it answers, then the return contents, then the error path — a logical order. Some price/rail detail duplicates the title verbatim, which costs a little space.

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 takes on the burden of describing returns and does so (payments, payers, account fields, 402 readings with sources and timestamps). It omits things like result size or time-window configurability, but is otherwise sufficient to call 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 coverage is already 100%, so both parameters are documented structurally; the description nevertheless adds the sequencing rule that payment_signature should be omitted on the first call to receive requirements, which the schema alone does not convey.

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 pair (paid readings for an XRPL payee) and enumerates the returned data: raw 24h payments, payers, account fields, and endpoint 402 readings. It is clearly narrower than siblings like get_x402_activity or get_merchant_profile, though it never names an alternative to make that contrast explicit.

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 a concrete usage frame — 'solves one question: What x402 payment readings does this XRPL payee show?' — plus the full paid-call protocol including what happens unpaid and how to retry. It stops short of saying when a caller should prefer a sibling tool over this one.

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 say read-only, open-world, non-idempotent; the description adds materially more: the exact per-call price and rails, that unpaid calls return isError with a PaymentRequired object containing a fresh invoiceId, the two retry channels (_meta["x402/payment"] or payment_signature), and that failed unpaid attempts cost nothing. That is precisely the failure-mode and cost context an agent cannot get from the 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 content is useful but the ordering is off: the first sentence leads with pricing already stated in the title, pushing the actual purpose to sentence two. The payment instructions are dense and run together, though almost every clause carries real information.

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 takes on return-value burden and does list the reading types and their provenance ('with sources'). Payment preconditions and failure handling are fully covered; what is missing is any sense of response shape or size for a read-only open-world tool.

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 both enums (name, sort) are fully documented in the schema, so the baseline is 3. The description adds a little by naming the _meta payment transport that the payment_signature schema entry references, but it contributes no extra meaning about the category values themselves.

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 resource and scope: price and listing readings for a models.dev category, with the returned fields enumerated (raw counts, 24h price changes, new/removed listings, vendor disturbances with sources). It stops short of distinguishing this from siblings that also return pricing data, such as get_price_index, get_model_report, or list_models.

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 'solves one question' framing implies when to reach for it, and the payment/retry path is spelled out. However, there is no guidance on when to use this versus get_price_index, get_current_conditions, or list_models, which is the main selection risk given the crowded sibling set.

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 and destructiveHint=false, so the description's real value-add is the failure/payment path, which it discloses precisely: unpaid calls return isError with a fresh invoiceId and cost nothing. It does not address caching, rate limits, or why idempotentHint=false on what appears to be a stable read, which keeps it 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?

The pricing terms are front-loaded and partially duplicated (title lists three price variants, the description restates two), consuming space ahead of the actual purpose. The core 'solves one question' framing and the payment retry instructions are useful, but the opening is boilerplate-heavy rather than function-first.

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 should sketch the return values, and it does so briefly (raw canonical id, cutoff, limits, change events with timestamps). Combined with complete schema coverage and a thorough payment/error explanation, an agent has enough to call it correctly, though the shape of the returned object remains under-described.

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%, so model, provider, and payment_signature are already documented with examples and constraints. The description adds only the output-side field list, not additional meaning about parameter values or the provider/model pairing beyond what the schema states.

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 — reading models.dev identity and change records for a given model — and enumerates the returned fields (canonical id, cutoff, limits, change events with timestamps). It does not distinguish itself from near siblings such as get_model_report or get_model_category, so an agent still has to infer which of the model-oriented tools to call.

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?

Strong guidance is given for the payment path: omit payment on the first call, receive the x402 PaymentRequired object, retry with the signed payload in _meta["x402/payment"] or payment_signature. However, there is no guidance on when to choose this tool over siblings like get_model_report or list_models, which is the other half of usage selection.

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 (readOnly, openWorld, non-idempotent, non-destructive), the description discloses the paid-per-call model, exact cost in two rails, the error shape returned without payment (x402 PaymentRequired with a fresh invoiceId), and the retry mechanism. That is precisely the behavioral context an agent needs before invoking a billable tool, and it is consistent with idempotentHint=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?

Dense and front-loaded, with the pricing constraint before the payload description and the error/retry path last. Some redundancy with the title's price string, which repeats the same 0.01 RLUSD/USDC figures.

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 outline the returned content (raw prices, limits, modalities, events, status with sources and timestamps) and fully covers the failure mode. A short note on charge behavior on retries or response envelope shape would close the remaining gap.

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%, so both id and payment_signature are already documented in the schema, including the _meta fallback. The description only restates the payment-signature mechanism without adding new syntax or constraints, 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 frames a single concrete question — what price, limit, vendor-status readings models.dev lists for a model — and names the returned fields (prices, limits, modalities, events, status with sources and timestamps). It clearly separates this from list_models (which supplies the id) but does not distinguish itself from near-neighbors like get_model_identity or get_end_of_support.

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 call protocol is spelled out: first call without payment returns a PaymentRequired error, then retry with the signed payload in _meta["x402/payment"] or the payment_signature argument, and unpaid calls cost nothing. What is missing is guidance on when to choose this over sibling pricing/identity 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 declare readOnly, idempotent, non-destructive, open-world behavior, so the safety profile is covered. The description adds real context beyond that: it is free, timezone-anchored, a fixed one-day lag, source-declared (not authoritative live measurements), and takes no inputs. Return shape details remain thin.

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 short sentences, front-loaded with the free-tier signal, then purpose, then scope caveats. Every sentence carries distinct information 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?

No output schema exists, so the description must convey what comes back, and it does so at a summary level (listing, price and status changes). It stops short of describing response structure or how changes are itemized, but for a zero-input read tool it is nearly 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?

Zero parameters, so the baseline is 4. The explicit 'No inputs' confirms the agent need not supply anything, which is the only parameter-related fact worth stating here.

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?

Names a specific verb+resource: the day-old change summary of the AI model directory, with the exact window (previous calendar day, America/Chicago). It distinguishes itself from generic siblings like get_sample_yesterday by scoping to the model directory, though it does not name a specific alternative tool.

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?

'Not live data' implicitly steers the agent away from this tool when current data is needed, and the free-tier note hints at cost tradeoffs. However, no sibling is named as the live/current alternative, so the agent must infer which of list_models, get_current_conditions, or get_sample_yesterday to use instead.

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 goes well beyond the annotations: it discloses the exact price and rails, that an unpaid call returns isError with a PaymentRequired object carrying a fresh invoiceId (consistent with idempotentHint=false), and that unpaid calls cost nothing. Retry mechanics via _meta["x402/payment"] or payment_signature are spelled out. What is missing is latency, caching, or rate-limit behavior, and the annotations already cover the safety profile, so 3 is fair.

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 content is front-loaded with the price and rails, then the question it answers, then the payment/error flow, so a reader can stop early. Most sentences earn their place. Some redundancy appears between the title and first sentence on pricing and chains.

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 still enumerates the returned fields (per-endpoint prices, rails, category lows, change deltas, sources, times). The single optional parameter is covered, and the error and payment states are explained. Nothing an agent needs in order 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 only one optional parameter and the schema already documents it at full coverage, so the description can only add marginal value. It does clarify that payment_signature is the fallback for hosts that cannot set _meta["x402/payment"] and that it should be omitted on the first call, which duplicates rather than extends the schema text. 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?

The description states a specific verb and resource with scope: it returns live XRPL x402 resource prices, spelling out the payload (per-endpoint prices, rails, category lows, change deltas with sources and times). It frames the tool around a single question, which makes it easy to distinguish from read-only sibling feeds. It does not name any sibling (payradar, get_x402_activity, get_discovery_feed) explicitly, so it stops short of a 5.

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?

'Solves one question: What prices are live XRPL x402 resources advertising right now?' gives clear context for when to reach for this tool. The payment flow is also a usage procedure: call without payment to get requirements, then retry once a signature is available. No exclusions or explicit alternative tools are given, which keeps it at 4 rather than 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?

Beyond the annotations it discloses pricing per rail, the exact failure mode for unpaid calls (isError with a fresh invoiceId), that unpaid calls are free, and the two retry channels. The fresh-invoice-per-call behavior is consistent with idempotentHint=false, so nothing conflicts with the structured hints.

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 cost and purpose, which is correct, but the pricing is largely duplicated from the title and "Unpaid calls cost nothing" restates the preceding sentence about the isError/PaymentRequired response. The dense clause stacking costs some readability for a one-parameter read tool.

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 carries the return-value burden and does name the returned signals, though not their structure. Payment/auth, error path, and cost are all covered, which is what an agent needs to invoke it correctly; only the shape of the success payload remains vague.

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 the single parameter is already documented, so the baseline is 3. The description adds the surrounding protocol semantics — that you omit the argument on the first call and supply the signed payload only on retry — which tells an agent how to sequence the parameter rather than what it is.

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 names a concrete question the tool answers — whether the XRPL x402 facilitator is reachable and whether known endpoints return 402 — plus the returned evidence (reachability, on-ledger success samples, valid-402 probe rates). That is clearly distinguishable from siblings such as get_x402_health_report or get_pulse_providers, though it never explicitly contrasts itself with them.

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 gives a clear selection trigger ("solves one question") and an explicit operational procedure: call without payment to get the PaymentRequired object, then retry with a signed payload in _meta["x402/payment"] or the payment_signature argument. It does not name an alternative tool for adjacent needs, so the routing guidance is strong but not exhaustive.

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, destructiveHint=false, openWorldHint=true, so the safety profile is covered, but the description adds substantial context they cannot: a concrete price per call, the two payment rails (xrpl:0 and eip155:8453), the exact failure shape (isError with an x402 PaymentRequired object carrying a fresh invoiceId), and that unpaid calls cost nothing. That is real behavioral disclosure beyond structured fields. It does not say whether the underlying data is cached, throttled, or how stale asOf can be, which keeps it from 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?

The core question and the payment mechanics are front-loaded and every clause carries information; the title repeats the pricing, causing some redundancy. It is a dense block rather than a structured list, but 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 usefully names the returned fields (per-provider indicators, reason, asOf, observed_uptime_7d, attribution) and fully specifies the payment handshake and error path. What is missing is which providers are covered and how this differs from the adjacent decision/status tools, which matters given a crowded sibling set.

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 the single parameter is already documented, so the baseline is 3. The description still earns credit by explaining the alternative transport (_meta["x402/payment"]) and the sequencing rule that the parameter should be omitted on the first call — meaning the schema alone would not tell an agent when to supply it.

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 concrete verb+resource: it returns "raw per-provider indicators, reason, asOf, and observed_uptime_7d samples" from public AI-provider status pages, framed as answering one question. That is far more specific than the name alone. It stops short of distinguishing itself from close siblings such as decide_provider_health, get_service_status, or get_pulse_storm, so an agent still has to guess which of those to pick.

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?

Usage guidance is strong on the payment path — omit payment on the first call, receive the PaymentRequired object with a fresh invoiceId, then retry with the signed payload — but there is no guidance on when to use this tool versus the sibling health/decision tools in the same family. The when-to-pay flow is explicit; the when-to-call context is only implied by the framing question.

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 say read-only/non-destructive/open-world, while the description adds the genuinely important behaviors: the tool is metered per call, failure without payment returns isError with a fresh x402 PaymentRequired invoiceId, and the exact retry channel (_meta["x402/payment"] or payment_signature). It also states unpaid calls are free, which matters for an agent deciding whether to probe.

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-loads the price and the single question it answers, then the return shape, then the error/retry path – a sensible order. It is dense and repeats the price information already present in the title, which is mild redundancy but not 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?

No output schema exists, and the description compensates by naming the returned fields and the failure object shape, plus payment requirements and retry mechanics. For a single-optional-parameter read tool, an agent has enough to call it and recover from the unpaid path; only a concrete example of the PaymentRequired payload 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?

With one optional parameter and 100% schema coverage the baseline is 3, but the description adds real sequencing meaning the schema does not: omit it on the first call, then supply the signed payload on retry, and it exists specifically for hosts that cannot set _meta. That is meaningful usage semantics beyond the schema text.

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 concrete scope: 'What is the worst current level across status pages, facilitator reachability, and recent changes?' plus the return fields (storm/level/reason, observed_* samples). This separates it from get_pulse_facilitator and get_pulse_providers, though it never names those siblings explicitly to say which one to prefer.

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 gives clear procedural guidance for the paid flow (omit payment on first call to receive requirements, retry with the signed payload; unpaid calls cost nothing) but no guidance on when to choose this aggregate storm signal over get_pulse_facilitator, get_pulse_providers, or get_service_status. Usage is implied by the 'one question' framing rather than stated as selection criteria.

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 open-world, so the safety profile is covered. The description adds genuinely new behavioral facts: it is free, the data is one day stale, the timezone is America/Chicago, and there are no inputs — exactly the context an agent needs to avoid mistaking it for live data.

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 short sentences with the most decision-relevant fact ('Free') front-loaded, followed by what it returns and the key caveat. Nothing is padded or repeated.

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 no-argument sample tool with no output schema, the definition covers cost, freshness, timezone, and data nature. The only remaining gap is that it doesn't characterize the report's contents or size, which matters slightly since the stated goal is format inspection.

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?

Zero parameters, so the baseline is 4. The description also confirms 'No inputs', which matches the empty schema and prevents an agent from hunting for arguments.

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 ('Returns a day-old sample of the conditions report') plus the exact time basis (previous calendar day, America/Chicago). It implicitly separates itself from get_current_conditions by declaring 'Not live data', though it does not name that sibling directly.

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 a clear when-to-use rationale ('so you can inspect the report format before paying') and an implicit exclusion ('Not live data' → use the live tool for actual conditions). It stops short of explicitly naming the alternative tool an agent should pick instead.

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 read-only, idempotent, non-destructive, open-world, so the bar is lower. The description still adds real value beyond them: the call is free, the payload is sourced from /.well-known/x402, and it carries no report data — all facts unavailable from 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?

Three short sentences, front-loaded with the free-cost signal and ending with the no-inputs constraint. Every sentence adds a distinct fact with no 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?

No output schema exists, yet the description enumerates the returned contents (reachability, API version, paid routes with prices and accepted assets) and the source endpoint. For a zero-parameter status tool, nothing an agent needs to decide to call it 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?

Zero parameters, and the description confirms "No inputs," matching the empty schema. Baseline applies; nothing further is needed.

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?

Names a specific verb and resource: returns reachability of the Agent Weather API and its XRPL payment facilitator, the API version, and the paid route/price/asset list. It also explicitly rules out report data, which separates it from siblings like get_model_report and get_current_conditions.

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?

"Free" and "Returns no report data" give clear context for when this tool is appropriate (status/price discovery, no cost) rather than a data fetch. It stops short of naming an alternative tool to use once prices are known, so no explicit routing.

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?

Goes well beyond the annotations by disclosing the per-call price and payment networks, the failure mode (isError with a fresh PaymentRequired object containing invoiceId), and the two ways to retry with a signed payload. This is exactly the kind of operational context annotations cannot express, and nothing contradicts readOnlyHint=true or idempotentHint=false (each paid retry is a new charge).

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?

Cost and scope are front-loaded and the error/retry mechanics are compact. There is minor redundancy with the title's pricing line and the closing 'Unpaid calls cost nothing' restates what the 402 flow already implies.

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 one-optional-parameter, no-output-schema, paid read tool, the description covers cost, networks, return contents, failure behavior, and recovery. An agent has everything needed to call it correctly on the first attempt.

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 the single optional payment_signature is already documented in the schema. The description still adds value by explaining the order of operations (omit it first to get requirements, supply it after the 402) and by naming the _meta["x402/payment"] alternative path.

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 resource and scope: 'What x402 payment volume and merchant activity did our XRPL scan record?' and enumerates the outputs (raw payments/volume series, unique payers/merchants, sample txs). It does not name or contrast with plausible siblings such as get_x402_health_report or get_merchant_readings, so the agent must infer which x402-related tool to pick.

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?

Frames the tool as answering exactly one question and states the payment prerequisite up front, including that unpaid calls cost nothing, which tells the agent it is safe to probe once. It gives no explicit exclusions or alternatives among the many sibling data 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 mark it read-only, non-destructive and open-world, but the description adds the parts annotations cannot express: per-call pricing on specific networks, the exact failure mode (isError plus a fresh invoiceId), the retry mechanism, and the fact that unpaid calls cost nothing. The only mild tension is that idempotentHint=false is not explained, but the fresh-invoice-per-call behavior is implied.

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?

Pricing is front-loaded and the core question comes early, so an agent can decide quickly. The pricing wording is somewhat run-on and partially redundant with the already verbose title, which repeats the same three prices.

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 one-parameter read tool with no output schema, the description covers cost, invocation flow, failure behavior, retry path, and the shape of the returned data. Nothing an agent needs to call it successfully 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?

With one optional parameter at 100% schema coverage, the schema already documents payment_signature fully. The description still adds value by framing the first call as unpaid (receive requirements) and by naming the _meta["x402/payment"] header alternative for the same parameter.

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 question the tool answers ("Which known XRPL x402 endpoints answer a valid 402") and enumerates the returned content: per-endpoint liveness, price/asset/payTo deltas, and facilitator readings with sources. It is far more specific than a restated title, but it never names a sibling (e.g. get_x402_activity or get_pulse_facilitator) to disambiguate within a crowded family.

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 gives clear operational context: the call is paid on two rails, an unpaid call returns isError with a PaymentRequired object, and the retry path is either _meta["x402/payment"] or the payment_signature argument. What is missing is explicit when-to-use guidance relative to sibling x402 tools, so there is context but no 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?

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, open-world), but the description adds genuinely non-obvious behavior: the index is a day old, only models first seen at least 24 h ago appear (flagged in `snapshot`), and the result set is explicitly not a ranking. Data-freshness and inclusion-lag semantics are exactly the traits an agent cannot infer from structured fields and could otherwise be misled by.

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?

Information is front-loaded (cost, then scope, then exclusions, then usage) and nearly every clause carries weight. The one redundancy is mentioning the paid get_model_report tool twice — once to list what it holds and again to say to pass ids to it — which could be merged into a single sentence.

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 five-parameter, zero-required, read-only listing tool with no output schema, the description covers scope, staleness, and follow-up adequately. The only soft spot is the reference to a `snapshot` flag, which points at a response field that is never otherwise described, leaving the return shape partly implicit.

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 all five parameters documented, including the category enum, so the schema already carries the parameter burden. The description restates the filter dimensions (vendor, category, text query) and pagination (limit/offset) without adding syntax, defaults, or interaction rules beyond what the schema says. Baseline 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 states a specific resource (the AI model directory index) and enumerates exactly which fields come back: model id, name, vendor and categories only. It also distinguishes itself from siblings by name (get_model_report, get_model_category) and explicitly says it is 'not a ranking', so an agent can tell which listing tool to pick without opening a 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?

It gives an explicit free-vs-paid split: this tool covers the shallow index, while live prices, context length, vendor status, 24h/7d changes, job cost and events live in get_model_report and get_model_category. It closes the loop with a concrete next step ('Use the ids with the paid get_model_report tool'), which is exactly the when-to-use guidance an agent needs from a cheap discovery call.

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?

Well beyond the annotations, the description discloses price (0.003 per call), the two payment rails, that unpaid calls cost nothing, that an unpaid call returns isError with a fresh invoiceId, and how to retry via _meta["x402/payment"] or payment_signature. One gap: the title advertises '0.003 RLUSD on Base' as a third rail that the description never mentions, and it does not reconcile paid spending with the readOnlyHint=true annotation. Overall still strong disclosure for a paid, open-world probe.

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?

All content is relevant, but the description opens with pricing rather than the tool's purpose, so the key 'what does this do' statement is buried in the second sentence. Sentences are long and densely packed with multiple clauses, and pricing detail duplicates 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?

With no output schema, the description carries the return-value burden and does so by enumerating the 402 fields (network, asset, payTo ledger fields, TLS, latency, uptime) and the error shape. What a successful paid response contains is only implied by that field list, and the missing Base RLUSD rail from the title leaves a small hole for a tool whose whole job is payment readiness.

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 schema already documents url, max_usd and payment_signature, making 3 the baseline. The description reinforces the two-step payment_signature flow and the _meta alternative, which the schema only partially conveys, but it says nothing about max_usd or its 0.10 default and price-ceiling behavior.

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 and resource: a pre-flight scan that checks whether an x402 endpoint is answering and captures its unpaid 402 response, including network, asset, payTo, TLS, latency and uptime. It is clear what the tool does, but it never distinguishes itself from close siblings such as payradar, paycheck_demo, get_x402_health_report or get_service_status, which an agent must disambiguate on its own.

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?

Usage context is explicit: run it before paying to answer 'is this endpoint answering right now, and what does its unpaid 402 show'. The description also gives the concrete call sequence (first call unpaid to receive the PaymentRequired object, then retry with the signed payload), which is exactly the guidance an agent needs. It lacks explicit when-not guidance or a named alternative when a cheaper/other diagnostic sibling is more appropriate.

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 read-only, idempotent, non-destructive and open-world behavior, and the description adds genuinely new context: the response is cached up to 10 minutes and is composed of raw checks first, then reasons, then a signal summary. It also notes there are no inputs, so callers know no authorization or parameters are negotiated. Minor gap: it does not say what happens when the demo target is unreachable.

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 key qualifier ('Free.') and then the response shape. Every sentence carries information; the only cost is mild jargon ('x402 shape', 'payTo') that is not unpacked.

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 useful work by outlining the return structure (raw checks, reasons, summary) and the caching window. For a zero-argument demo endpoint that is close to complete; only the differentiation from sibling radar/paycheck tools 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 are zero parameters, so the baseline is 4. The description confirms 'No inputs,' matching the empty schema, and adds nothing that could mislead about arguments.

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 concrete resource and content: a full Pay Radar example report for Agent Weather's own /v1/pulse/facilitator, listing raw checks (reachable, latency, tls, x402 shape, asset, payTo) plus reasons and a summary. However, it never distinguishes this tool from the many similar siblings (payradar, payradar_demo, paycheck, get_pulse_facilitator), and the name paycheck_demo versus the described 'Pay Radar' subject adds confusion rather than resolving 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?

'Free.' and 'No inputs.' imply it is a no-cost, call-anytime preview, which hints at using it instead of a paid sibling. No explicit when-to-use, when-not-to-use, or named alternative is given, so the agent must infer the routing from the word 'Free' and the tool name alone.

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?

Goes well past the annotations by disclosing the price and two accepted rails (0.003 RLUSD on XRPL mainnet, 0.003 USDC on Base), the fact that an unpaid call deliberately returns isError with a fresh invoiceId, and the exact retry mechanism for supplying a signed payload. It also enumerates the observable surface returned (raw 402 shape, network, asset, payTo ledger fields, TLS, latency, uptime history). Nothing here contradicts readOnlyHint or the other annotations — erroring out on a missing payment is a payment protocol state, not a state mutation.

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 price and purpose, then the question it answers, then the payment mechanics — a logical decision order with almost no filler. The paragraph is dense and slightly run-on, and the per-call price is stated both in the title and in the first sentence, giving mild 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 3-parameter tool with no output schema, the description covers what an agent needs: cost, trigger condition, the two-step unpaid-then-paid handshake, and an inventory of returned fields. The only gap is that max_usd's role as a spend guard is left entirely to the schema, and the shape of the paying response is only sketched rather than described.

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%, so the baseline is 3 and the schema already defines url, max_usd, and payment_signature with format and default. The description adds real value for payment_signature by explaining the _meta fallback vs. the explicit argument and the omit-on-first-call convention, but it says nothing about max_usd's price-ceiling behavior beyond what the schema states.

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 — a pre-flight scan of an x402 endpoint — and crystallizes it into one question: "Is this x402 endpoint answering right now, and what does its unpaid 402 show?" The title also discloses it is an alias of paycheck, which prevents duplicate-invocation confusion. It stops short of 5 because it never distinguishes itself from siblings like get_x402_health_report, get_x402_activity, or payradar_demo, which an agent could plausibly pick instead.

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?

"Before paying" is an explicit trigger condition, and the payment protocol is spelled out: first call returns isError with the PaymentRequired object, then retry with the signed payload via _meta["x402/payment"] or payment_signature. It also reassures that "Unpaid calls cost nothing," removing hesitation about probing. What is missing is any exclusion or named alternative (e.g., when to prefer the demo variant or the health-report sibling).

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 open-world, so the safety profile is covered. The description adds two things the annotations cannot: results are cached up to 10 minutes (so data may be stale) and the response is structured as raw checks followed by reasons and a signal summary. That is genuine added context for an agent reasoning about freshness.

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 short sentences: cost/availability first, then what the response contains, then the caching caveat and the no-input constraint. Every clause carries information and the most decision-relevant facts are 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?

With no output schema, the description usefully enumerates the returned check fields and the reasons/summary layer, and it discloses caching and the absence of inputs. What remains unstated is auth or rate-limit requirements and an explicit routing hint versus payradar, which keeps it short of 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?

There are zero parameters, so the baseline is 4, and the description correctly confirms 'No inputs' so the agent knows no configuration or endpoint argument is accepted. Nothing further is needed for an empty object 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?

The description names a concrete deliverable: a full Pay Radar example run against Agent Weather's own /v1/pulse/facilitator endpoint, enumerating the checks it performs (reachable, latency, tls, x402 shape, asset, payTo). The word 'example' plus the fixed endpoint distinguish it from the sibling payradar tool, though the description never names that sibling outright.

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?

'Free' and 'No inputs' imply this is a zero-config trial call, which is useful selection context, but there is no explicit statement of when to pick this over payradar or paycheck_demo. The agent must infer that this is for evaluating the response shape rather than checking its own endpoint.

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