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

With no annotations, the description carries full disclosure burden and does so well: 'Nothing is bought, ordered or paid; no quote is guaranteed; it is free' reveals the non-binding, no-cost nature of the enquiry. It also discloses what the tool returns (recipients, consent wording, confirmation process), going beyond the bare minimum.

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 'Read first' directive is effectively front-loaded, and the three sentences each add information: what the tool explains, the non-purchase semantics, and the return contents. The opening 'States plainly what submit_enquiry does' is slightly redundant with the tool name, but the overall structure is tight.

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 meta/describe tool with no annotations and no output schema, the description covers what an agent needs: the tool's explanatory purpose, the outcome semantics (free, non-binding, human providers), and a summary of returned content. It could name the sibling enquiry_fields, but nothing critical 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?

The schema has zero properties, making parameter documentation unnecessary; the baseline of 4 applies. The description introduces no parameter confusion because there are none to document.

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 purpose: it 'states plainly what submit_enquiry does' on Freight Insurance Cost, framing itself as the explainer/pre-read for the submission sibling. It clearly differentiates itself from submit_enquiry by emphasizing this is about understanding an enquiry, not executing one.

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?

'Read first' is an implied usage directive that tells the agent to consult this before acting on submit_enquiry. However, it never explicitly names when to use this vs. the alternatives, and enquiry_fields is entirely unaddressed.

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 burden of behavioral disclosure. The description does not state whether this is a read-only operation, whether it has side effects, whether it requires authentication, or what errors might occur. It only describes the output content. For a tool with no annotations, this is a significant gap; the agent is left to assume the operation is safe and non-mutating without explicit assurance.

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, compact sentence that front-loads the core purpose ('Every field of the Freight Insurance Cost enquiry') and immediately follows with the relevant details (what each field contains and how to use the output). There is no filler or redundant wording, and it is appropriately structured for quick parsing by an agent.

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?

The tool is simple (no parameters, no output schema, no annotations), so the description does not need to explain return values or complex behavior. It clearly states what is returned (fields with attributes) and how to use that information (keyed answers for submit_enquiry). The only minor omission is an explicit statement that the tool is read-only, but given the simplicity, the description is largely complete for an agent to invoke it correctly.

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

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

The tool has 0 parameters and the schema coverage is 100% (vacuously). According to the rubric, a tool with 0 parameters gets a baseline of 4. The description does not need to add parameter semantics because there are none, and it does not introduce any confusing parameter-related information. The score reflects that the description is adequate for a parameterless tool.

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 ('returns'), a specific resource ('every field of the Freight Insurance Cost enquiry'), and enumerates the content (key, label, type, required, help text, options). It clearly distinguishes itself from siblings by referencing submit_enquiry and implying it is the field-definition provider. An agent can immediately understand what this tool does and how it differs from the other tools.

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

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

The description includes an explicit usage instruction: 'Pass answers to submit_enquiry keyed by field key.' This tells the agent that the output of this tool is meant to feed into submit_enquiry, providing clear context for when to use it. However, it does not explicitly state when not to use it or name alternatives like enquiry_describe, so it is not a full 5.

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

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

With no annotations, the description carries the full burden and does so thoroughly: it discloses validation behavior, the exact return payload of step 1 (summary, consent line, token), that the person must show and approve the summary, and that submission triggers an email link the person must click before any provider sees the data. It also spells out the downstream effect (contact details sent to up to three firms, notified per firm, can opt out).

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

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

Front-loaded with the two-step flow and the not-a-purchase caveat, and each sentence maps to an actionable decision. The repeated consent string is long but is quoted material the agent must display verbatim, so it 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 three-parameter nested-object tool with no output schema and no annotations, the description supplies everything needed: the staged protocol, the returned token, the required user-facing disclosure, and the post-submission email verification gate.

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

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

Schema coverage is 100%, so the baseline is 3, but the description goes beyond it: it explains that `answers` is keyed by field key sourced from enquiry_fields, that `consent` must be paired with the actual consent text, and that `confirmation` is the token from step 1 held until the person approves the summary. This adds real invocation meaning 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?

The name, title and first sentence state a specific verb (submit) and resource (enquiry) to human providers, and explicitly negate the two most likely misreadings: 'NOT a purchase, NOT a guaranteed quote'. It also distinguishes itself from the sibling read-only tools (enquiry_describe, enquiry_fields) by framing this as the terminal action.

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 prescribes exactly when to call step 1 (with answers + consent=true) and the strict precondition for step 2 (only if the person agrees, with the returned token). It also states the when-not (not a purchase, not a quote) and the consent condition that gates the call.

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