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

No annotations are provided, so the description carries the full behavioral disclosure burden. The verb 'Check' clearly indicates a read-only operation, and the description discloses what will be returned: status (unpaid/paid) and on-chain payments. It does not mention error cases or side effects, but for a status-check tool this is adequate.

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, tightly worded sentence with no filler. It front-loads the action ('Check') and efficiently packs the resource, status values, and payment details into a compact structure.

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 simple 1-parameter read-only tool with no output schema, the description is sufficiently complete, covering both key return aspects: status and settling payments. It does not describe error behavior or exact response structure, but those are not necessary for this level of 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?

The schema fully describes the only parameter orderId as 'order id returned by zunivo_create_payment_link', providing clear semantic context. Since schema coverage is 100%, the baseline is 3, but the explicit tie to a sibling tool adds valuable meaning beyond the bare parameter name.

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 a specific verb ('Check') and names the resource ('payment link / order'), then clearly enumerates the returned information: status (unpaid or paid) and the on-chain payments that settled it. This distinguishes it from sibling tools like zunivo_create_payment_link and zunivo_spend_status.

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 usage: after creating a payment link, check the order status using the returned orderId. However, it does not explicitly state when to use this tool versus alternatives like zunivo_paid_fetch or zunivo_spend_status, nor does it mention any 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?

With no annotations, the description carries the full burden of behavioral disclosure. It reveals that anyone with the link can pay (a public access model) and that it returns the pay URL and order ID. This goes beyond the schema, though it does not mention side effects like persistence or authentication requirements.

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 extremely concise: two sentences, no filler. The first sentence explains what and how; the second states the return value. Every phrase earns its place, making it easy to parse.

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, the description appropriately specifies return values (pay URL and order id). It covers the core behavior, but lacks details about prerequisites (e.g., whether the recipient must be a valid .agent) or the lifecycle of the order. Still, for a simple create operation, it is reasonably 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?

Schema description coverage is 67% (to and amount have descriptions, memo does not). The description reinforces the meaning of 'to' and 'amount' in the context of the payment link, but it does not clarify 'memo' at all, leaving a gap. It adds some value but does not fully compensate for the missing memo documentation.

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

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

The description clearly states the tool's purpose: 'Create a Zunivo payment link (invoice)' with a specific verb and resource. It explains the key functionality (anyone can pay USDC to a .agent name or 0x address) and distinguishes it from sibling tools, which are about listing, resolving, fetching, and checking statuses.

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

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

The description provides clear context for when to use the tool (when you need to create a payment link for someone to pay), but it does not explicitly name alternatives or state when not to use it. The unique creation purpose among siblings makes the usage context obvious, but explicit guidance is missing.

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

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

With no annotations, the description carries the full burden. It clearly states the outcome (list of .agent names) and the inclusion criterion (published a callable service). However, it does not disclose potential behavioral aspects like ordering, pagination, or authentication requirements, which would enhance transparency.

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, front-loaded sentence with no redundant information. Every word contributes to the meaning, making it highly concise and structured.

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 simple 0-parameter enumeration tool, the description covers purpose, scope, and location. The absence of an output schema is not a significant gap because the return format (a list of names) is intuitively clear. The description is complete for correct invocation.

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

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

The tool has zero parameters, and the schema is fully covered. The description adds context about what the list contains, but since there are no parameters, the baseline of 4 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 uses a specific verb ('List') and resource ('every .agent name that has published a callable service'), clearly distinguishing this listing tool from sibling tools like zunivo_resolve_agent or zunivo_paid_fetch. The scope (public agent directory on Arc) is 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?

The description provides clear context (public agent directory) that implies when to use this tool, but it does not explicitly state exclusions or alternatives. The context is sufficient for an agent to infer the primary use case, but lacks overt when-not guidance.

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

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

With no annotations, the description carries full burden and does it well: discloses the automatic payment flow (USDC from agent wallet within budget), the 402 retry behavior, and the return payload including payment receipt. This is significant behavioral transparency.

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 purposeful sentences, front-loaded with the core action and key differentiator. Zero waste.

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

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

For a 5-parameter tool with no output schema, the description covers the essential behaviors and return values. It could benefit from mentioning error handling when budget is insufficient, but overall it provides enough context for correct invocation. Sibling tools cover agent discovery, so the integration is reasonable.

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 descriptions cover 80% of parameters, so baseline is 3. The description adds the key semantic that target can be either a full URL or an agent+path combo, which clarifies the relationship between url, agent, and path. This elevates it to 4.

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 ('Call a paid HTTP API') and the key differentiator (automatic payment on 402). Clearly distinct from sibling tools which manage agents/orders/payments.

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 clear context on when to use (calling a paid API, with auto-payment on 402) but does not explicitly compare with sibling tools or state exclusions. The target forms (full URL vs agent+path) add usage guidance.

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

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

With no annotations, the description carries the full burden. It does disclose that resolution is on-chain, the output fields, and accepted input forms. However, it omits any mention of network requirements, failure modes, or limitations of the accepted shorthand forms.

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, no filler. The purpose and key input variation are front-loaded, and every clause earns its place.

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 resolution tool with no output schema, the description is nearly complete: it states what is returned and the accepted input formats. A small gap is the lack of return structure or error behavior, but this is acceptable for such a simple 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?

The schema already documents the single `name` parameter with 100% coverage, but the description adds the accepted variants ('data.agent', '@data', 'data'), which goes beyond the schema's '.agent name to resolve'. This materially helps the agent format input correctly.

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 a specific verb ('Resolve') and identifies the exact resource ('.agent name' → 'on-chain agent card') plus the key output fields. This clearly distinguishes the tool from siblings like zunivo_list_agents or zunivo_paid_fetch.

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 implies this tool is for resolving a specific agent name, and even gives accepted input formats, but it never explicitly contrasts with alternatives or states when not to use it. The context is clear enough for a single-purpose lookup, but not fully explicit.

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

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

With no annotations provided, the description carries the full burden. It transparently states that the tool displays budget information (daily cap, spent, remaining, per-call ceiling), implicitly indicating a read-only operation. It does not mention potential side effects, rate limits, or authentication needs, but for a status-check tool the behavioral disclosure is adequate.

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, front-loaded sentence that immediately states the tool's purpose and lists the key data points. Every word contributes value; there is no filler or redundancy.

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

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

Given the tool has no input parameters and no output schema, the description sufficiently covers the return value by specifying the four main fields (daily cap, spent so far, remaining, per-call ceiling). It is contextually complete for an agent wanting to understand what this status tool provides.

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

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

The tool has zero parameters, and the description does not need to explain parameter semantics. Per the baseline for 0 params, a score of 4 is appropriate; the description focuses on what the tool returns rather than inputs.

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 a specific verb 'Show' and clearly identifies the resource: 'today's spending budget for the agent wallet'. It lists the exact information provided (daily cap, spent so far, remaining, per-call ceiling), which clearly distinguishes it from sibling tools like paid_fetch or check_order.

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 a clear use case: checking the current budget status of the agent wallet. However, it does not explicitly mention when to use this tool instead of alternatives, nor does it provide exclusions. The context is clear enough that an agent would know to use this when budgeting or pre-checking spend, but it lacks explicit guidance.

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