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

With no annotations provided, the description carries the full burden of behavioral disclosure, and it does so thoroughly. It states that nothing is bought, ordered, or paid, that no quote is guaranteed, that the service is free, and that the tool returns who receives the details, the consent wording, and how confirmation happens. This gives an agent a clear picture of side effects and outcomes.

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

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

The description is compact, front-loaded with the actionable 'Read first' directive, and each sentence adds distinct information: what the tool explains, what it does not do, and what it returns. The phrasing is direct and avoids unnecessary elaboration.

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, no-output-schema, no-annotation tool, the description is complete. It explains the tool's purpose, the domain context, the non-financial nature, the free aspect, and the specific return content. An agent has enough information to decide when to call this tool and what to expect from it.

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, so the baseline is 4 and the description does not need to explain parameter behavior. The description instead focuses on what the tool communicates, which is appropriate for a parameterless informational tool. No parameter semantics are missing.

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

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

The description states a clear, specific purpose: it is a read-first tool that explains what submit_enquiry does, framed as starting an enquiry with human providers. It distinguishes the tool from the actual action tool by emphasizing that nothing is purchased, ordered, or guaranteed. The title reinforces this with the 'not a purchase, not a guaranteed quote' 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?

The opening phrase 'Read first' gives explicit guidance to consult this tool before proceeding, which is strong usage direction. It clarifies that this tool explains submit_enquiry, but it does not explicitly mention when to choose this over enquiry_fields or when it can be skipped. The guidance is clear 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly states the returned field attributes: key, label, type, required status, help text, and allowed options. This makes the tool's output behavior predictable without needing to infer much, though it does not explicitly state that it is a read-only operation.

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, information-dense sentence that front-loads the core purpose and then lists the specific output components. The additional instruction about submit_enquiry is relevant and earns its place without adding verbosity.

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 metadata tool with no output schema, the description is complete: it enumerates the shape of the returned data and explains how to use those data with submit_enquiry. Nothing critical is missing for an agent to call and process the result 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 zero parameters, which sets the baseline at 4. The description appropriately avoids discussing parameters, and the empty input schema confirms no arguments are required. No additional parameter semantics are 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?

The description clearly identifies the tool's subject—every field of the Classic Car Restoration Cost enquiry—and lists what information each field includes. It does not use a strong imperative verb like 'lists' or 'returns,' and it does not explicitly differentiate from enquiry_describe, but the content makes the purpose evident.

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 actionable guidance by stating that answers should be passed to submit_enquiry keyed by field key. This implies the tool is used to discover valid keys before submission, though it does not explicitly say when to choose this tool over enquiry_describe or give 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 and does: it discloses the two-step protocol, that step 1 validates and returns a summary/consent line/token, that nothing reaches providers until the person clicks an emailed link, and exactly what consent authorises (contact details to up to three named specialists). This is unusually rich behavioral disclosure for a mutation tool.

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 negative framing and a clean Step 1/Step 2 structure, so the critical path is easy to scan. The final consent paragraph is long and largely duplicates the consent field description in the schema, which is mild redundancy rather than 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?

There is no output schema, so the description must explain returns — and it does, describing step 1's summary, consent line and token, and step 2's outcome (submission plus an email link gating provider visibility). Combined with the parameter guidance, an agent has everything needed to run both calls 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 100%, so the baseline is 3, but the description adds real semantics: answers must be keyed by the field key from enquiry_fields, and the confirmation token is specifically 'from step 1, after the person has approved the summary'. It clarifies when consent must be true rather than just what it means, going beyond the schema's own 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?

States a specific verb (submits) and resource (an enquiry to Classic Car Restoration Cost) and immediately disambiguates with 'NOT a purchase, NOT a guaranteed quote'. It also ties itself to the sibling enquiry_fields by naming it as the source of the field keys, so an agent can place it in the flow without opening other schemas.

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 prescribes the when: Step 1 with answers + consent=true, and Step 2 'only if the person agrees' with the same answers plus the confirmation token. It names the trigger condition for the second call and rules out purchase/quote interpretations, leaving nothing to inference.

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