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

With no annotations, the description carries the full burden and does well: it clarifies the tool is informational, that nothing is bought or paid, that no quote is guaranteed, and that it is free. It also discloses return content: who receives details, consent wording, and how confirmation happens.

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 tight and front-loaded with the imperative 'Read first.' Every sentence adds distinct value: the subject scope, the non-transactional nature, and the return contents. No filler or redundant restatement.

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 describing tool with no output schema, the description fully covers what it does, what it does not do, and what it returns. An agent has enough information to invoke it correctly and interpret its 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?

The tool has zero parameters, so the baseline for this dimension is 4. There are no parameter semantics to document, and the empty schema is consistent with a purely descriptive, no-input 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 clear verb ('states plainly') and resource ('what submit_enquiry does on Gearbox Repair Quotes'), and the title reinforces the non-purchase nature. It differentiates from the sibling submit_enquiry, but does not explicitly distinguish itself from enquiry_fields.

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 'Read first' gives clear context that this tool should be consulted before submit_enquiry. It does not explicitly discuss when to prefer it over enquiry_fields or when not to use it, so it stops short of full alternative 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?

No annotations are provided, so the description carries the burden of explaining behavior. It clearly conveys that this is a read-only metadata lookup by listing the contained field attributes, and it implies no side effects. It does not discuss output shape or edge cases, but for this simple tool the 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?

Two compact sentences carry all necessary information. The first sentence front-loads the tool's content and purpose; the second provides workflow guidance. 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?

For a zero-parameter, no-output-schema metadata tool, the description is complete enough: it specifies the returned content and connects the result to the submission workflow. It would be slightly stronger if it clarified how this relates to enquiry_describe or stated the return container explicitly.

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 takes zero parameters and the empty schema fully covers that. The description adds relevant context by explaining how the returned field keys should be used with submit_enquiry, which is helpful 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 names a specific resource ('Gearbox Repair Quotes enquiry') and enumerates exactly what the tool exposes: key, label, type, required flag, help text, and options. It is clear and concrete, though it does not explicitly differentiate itself from the sibling 'enquiry_describe'.

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 second sentence gives actionable guidance: pass answers to submit_enquiry keyed by the field key. This creates a clear workflow context, but it does not mention when not to use this tool or compare it with enquiry_describe.

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, and it does so thoroughly. It explains the two-step validation/submission sequence, the confirmation token, the requirement to show the person the summary and consent line, the email with a click link, and the exact consent wording. This is exceptional 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 long but every sentence earns its place due to the consent and two-step complexity. It is clearly structured with 'Step 1' and 'Step 2', includes the exact consent text to avoid ambiguity, and front-loads the core purpose and exclusions.

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?

Despite having no annotations and no output schema, the description provides enough context for an agent to execute the tool correctly: inputs, step outputs, side effects, success criteria, and the consent requirement. Nothing critical is missing for a 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?

Although schema coverage is 100%, the description adds significant meaning beyond the schema: answers must be keyed by field key from enquiry_fields, consent must only be true after the person agrees to the specific consent line, and confirmation is the token from step 1 after approval. This directly ties each parameter to the workflow.

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 action, 'Submits an enquiry to Gearbox Repair Quotes', and immediately clarifies what the tool is not ('NOT a purchase, NOT a guaranteed quote'). This clearly differentiates it from the sibling tools enquiry_describe and enquiry_fields by its distinct verb and resource.

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 two-step workflow is explicitly described, including exactly when the second call should be made ('only if the person agrees'). It also provides exclusion criteria ('NOT a purchase, NOT a guaranteed quote'). However, it does not explicitly state when to prefer this tool over enquiry_describe or enquiry_fields, though it references enquiry_fields for field keys.

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