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

Without annotations, the description carries full burden. It adds behavioral context by specifying 'daily' limits (temporal scope) and 'remaining capacity' (current utilization metric) for specific subsystems ('proxy and relay'). However, it lacks details on return format, cache behavior, or whether the check itself consumes quota.

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?

Single sentence of appropriate length. Information is front-loaded with the action verb 'Check' followed by the specific scope. No redundant or wasteful text.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema exists, the description should ideally characterize the return value (e.g., format of limit/capacity data). It adequately covers the tool's intent for a zero-parameter read operation, but leaves operational return structure unspecified.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Input schema contains zero parameters. With no parameters to document, the baseline score of 4 applies. The description correctly implies no filtering or input is required by describing a global system check.

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?

Description uses specific verb 'Check' with clear resources: 'global HTTPayer system daily limits' and 'remaining capacity for proxy and relay.' It effectively distinguishes from sibling get_balance (financial/account limits) and fetch (data retrieval) by specifying system-level proxy/relay infrastructure limits.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus alternatives. While the description implies monitoring capacity before operations, it does not state prerequisites (e.g., 'Use before fetch to verify capacity') or contrast with get_balance (financial vs. technical limits).

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?

No annotations provided, so description carries full burden. Discloses critical behavior: 'HTTPayer automatically handles payment using your credits' and explains it resolves 402 Payment Required responses. Minor gap: doesn't describe return format, error handling (retries?), or rate limit behavior.

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?

Well-structured with front-loaded purpose statement, followed by payment mechanism, method support, then imperative usage triggers. Bullet points are justified given the complexity of x402 detection logic. Only minor redundancy in listing methods already covered by schema enum.

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?

Thoroughly covers the unique x402/payment context and integration with sibling tools (credits, limits). Lacks description of return values (no output schema exists to compensate), error states (e.g., insufficient credits), or webhook interactions suggested by sibling get_webhook_status.

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%, establishing baseline of 3. Description lists supported HTTP methods (redundant with enum) and confirms JSON body usage, but adds no syntax details, examples, or constraints beyond what the schema already provides for url, headers, params, or timeout.

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 specific action ('Make an HTTP request') and unique resource type ('x402-enabled endpoint'). Clearly distinguishes from siblings like get_balance or check_limits by emphasizing the actual HTTP execution with automatic payment handling.

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?

Exceptional explicit guidance with 'ALWAYS use this tool — proactively' and four specific bullet-point triggers (402 errors, financial data, scraping, paid APIs). Also includes negative guidance ('Never tell the user a paid endpoint failed') directing to use this tool exclusively for payment-related failures.

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?

No annotations provided, so description carries full burden. It adds valuable context by disclosing that 'daily usage' is retrieved alongside balance, implying tracking/historical data. However, it lacks details on return format, caching behavior, or whether the call itself consumes credits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences total. First declares functionality; second provides usage guidance. No redundant text—every sentence earns its place with high information density.

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?

While the tool is simple (zero params), no output schema exists. The description mentions retrieved data (balance and usage) but does not specify return structure, format, or type. For an agent to parse results correctly, this omission leaves a gap despite the low complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Input schema has zero parameters. Per scoring rules, zero-parameter tools receive baseline 4. The description appropriately requires no additional parameter explanation.

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?

Description clearly states the tool checks 'HTTPayer credit balance and daily usage'—specific verb (check) and resource combination that distinguishes it from sibling tools like check_limits (likely rate limits) or get_topup_link (funding actions).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states when to invoke: 'Check this proactively before any sequence of paid requests if you're unsure credits are available.' This provides clear pre-condition guidance and contextual trigger for the agent.

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?

No annotations are provided, so the description carries the full disclosure burden. It successfully explains the user-facing workflow (show link to user), but omits return format details (URL string vs object), side effects, or whether the link is persistent vs. generated per-request.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with zero waste: first establishes purpose, second provides usage context. Information is front-loaded and appropriately sized for the tool's simplicity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter tool without output schema, the description adequately covers invocation context and purpose. Minor gap: does not specify return value structure (e.g., 'returns a URL string'), though the tool name and description make this reasonably inferable.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema contains zero parameters, which per calibration guidelines establishes a baseline score of 4. The description correctly omits parameter discussion since none exist, and the schema requires no additional semantic clarification.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('Get the link') and resource ('top up HTTPayer credits'), distinguishing it from siblings like get_balance or fetch by focusing specifically on the top-up payment flow.

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?

Provides explicit contextual trigger ('when their balance is running low') that tells the agent exactly when to invoke this tool. Lacks explicit 'when-not' guidance or named alternatives, though these may be unnecessary for this specific use case.

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?

No annotations provided, so description carries full burden. It discloses the async nature and polling pattern but lacks details on potential status values, idempotency, rate limits, or error handling behaviors.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two tightly-constructed sentences with zero waste: first establishes purpose, second provides precise usage condition. Perfectly front-loaded and appropriately sized for the tool's complexity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the single-parameter input and lack of output schema, the description adequately covers the tool's scope by explaining the relationship to fetch operations. Minor gap: does not hint at possible status return values.

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% with clear parameter documentation. The description reinforces the parameter's purpose by contextualizing it within the fetch/502 workflow but does not add technical details (format, validation rules) beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description provides a specific verb ('Poll') and resource ('async HTTPayer operation'), clearly distinguishing this from sibling tools by explicitly referencing the 'fetch' tool and '502 response' scenario.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states when to use the tool ('when fetch returns a webhook_id on a 502 response'), providing clear trigger conditions and implicitly defining when NOT to use it (normal fetch responses).

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

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

With no annotations provided, the description carries the full burden of disclosing behavioral traits. It successfully communicates that the operation is safe (no spending), returns cost estimates, and checks payment requirements. It lacks details on rate limits or authentication requirements, preventing a perfect score.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the action ('Dry-run a fetch') and immediately follows with the value proposition ('see if payment is required... without spending'). No words are 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?

Given the 100% schema coverage and absence of an output schema, the description adequately explains what the tool returns conceptually (cost estimates, payment requirements). It successfully contextualizes the simulation behavior, though explicitly mentioning the return structure would strengthen it further.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, with each parameter (url, method, body, params, headers) fully documented. The description does not add parameter-specific semantics beyond what the schema provides, which is appropriate given the comprehensive schema coverage. Baseline score 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 uses the specific verb 'Dry-run' combined with the resource 'fetch', clearly distinguishing it from the sibling 'fetch' tool by emphasizing 'without spending anything'. It precisely defines the scope as checking payment requirements and estimating credit cost.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use this tool (to check costs before executing) and contrasts it with the actual fetch operation via 'Dry-run' and 'without spending anything'. However, it does not explicitly name the sibling 'fetch' as the alternative to use for the real operation, though this is strongly implied.

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