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

No annotations are provided, so the description carries the burden of behavioral disclosure. It explains that this tool returns information about the enquiry flow, and clarifies that the enquiry itself involves no payment or guaranteed quote. However, it stops short of explicitly stating that this tool itself is side-effect-free and only returns an explanation.

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 front-loaded with 'Read first' and is reasonably concise. However, it repeats what the title already conveys ('not a purchase, not a guaranteed quote' appears in both), adding some redundancy without earning all of its wording.

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 descriptive tool with no output schema, the description serves as both the tool's contract and its output summary. It lists what the returned text will cover: who receives the details, the consent wording, and how confirmation happens. This is sufficient for an agent to know what to expect.

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 input schema is empty, with full schema coverage. With no parameters to document, the description has no additional parameter semantics to provide, and a 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 clearly states the tool's function: it explains what submit_enquiry does on Gearbox Reconditioning Cost. It is specific about the verb ('States plainly') and the resource (submit_enquiry). It does not explicitly name or contrast with sibling tools, but the purpose is unmistakable.

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 phrase 'Read first' is an explicit usage instruction, telling the agent to invoke this tool before submit_enquiry. It gives clear context for when to use it, though it does not mention alternatives or exclusions explicitly.

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. It states what is returned (field metadata) but does not explicitly say whether the operation is read-only, has side effects, or requires any permissions. Since this is a no-parameter query tool, one could assume it is safe, but the description does not confirm that. It also lacks details about the output format or potential variations (e.g., whether the list is static or dynamic). For a tool with zero annotation coverage, this is a significant gap.

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, well-structured sentence. It front-loads the core purpose ('Every field of the Gearbox Reconditioning Cost enquiry') and then lists the specific attributes, followed by a practical usage hint. There is no wasted wording, and the sentence is concise yet informative.

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 there is no output schema, the description explains what the tool returns (field metadata) and how to use it (pass answers keyed by field key). It covers the essential information an agent needs to call this tool and interpret its results. It does not mention edge cases like empty list behavior or errors, but for a simple field enumeration tool, it is reasonably complete. The absence of output schema is compensated by the explicit list of returned attributes.

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 schema already covers everything (100% coverage trivially). The baseline for 0 params is 4. The description adds value by explaining that the returned field keys are used as keys for submit_enquiry, which provides contextual meaning beyond the schema. 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 states a specific resource (the fields of the Gearbox Reconditioning Cost enquiry) and enumerates the attributes it exposes (key, label, type, required, help text, allowed options). This is clear and action-oriented, though it does not explicitly differentiate from the sibling enquiry_describe, which might describe the enquiry itself rather than its fields. The verb 'Every field' and the list of metadata make the purpose unambiguous.

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 gives a practical usage instruction: 'Pass answers to submit_enquiry keyed by field key,' which tells the agent how to use the returned keys. It implies the tool should be called before submitting an enquiry, but it does not explicitly contrast with enquiry_describe or state when not to use it. The guidance is helpful but not comprehensive regarding alternatives.

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 exist, so the description carries the full burden. It discloses the validation/summary/token behavior of step 1, the email-link-required-before-provider-sees-it behavior of step 2, and the exact consent text. This is far more transparent than a generic 'submits an enquiry' statement.

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?

Every sentence is functional, and the most important caveats are front-loaded ('NOT a purchase, NOT a guaranteed quote'). The length is justified by the two-step interaction complexity, and the step-by-step structure makes it easy to follow.

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 multi-step mutation tool with no output schema, the description is self-sufficient: it states step 1's return values, the required user action, the email behavior, and the consent wording. Nothing needed to call the tool correctly 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?

Schema coverage is 100%, so the baseline is 3. The description adds meaningful process semantics beyond the schema: the same answers and consent=true are used in both steps, and the confirmation token comes from step 1. It also directs the agent to enquiry_fields for the answer keys.

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 and resource ('Submits an enquiry to Gearbox Reconditioning Cost'), explicitly negates purchase/quote, and distinguishes itself from siblings by being the submission step. The reference to enquiry_fields signals the broader flow without ambiguity.

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 a detailed two-step protocol with explicit conditions: call with answers and consent=true, show the summary and consent line, then call again only after agreement with the confirmation token. It also gives a when-not-to-use caveat ('NOT a purchase'), but it does not explicitly name sibling tools as alternatives.

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