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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 disclosure burden and meets it: it explicitly states that an enquiry 'starts' with human providers, that 'Nothing is bought, ordered or paid,' that no quote is guaranteed, and that it is free. It also discloses precisely what the description returns, including consent wording and confirmation details.

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 the most important cue ('Read first') and each subsequent clause carries distinct information: what the underlying tool does, what it does not do, cost, and return content. It is compact and free of filler.

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?

Even without an output schema, the description tells an agent what to expect back: recipient details, consent wording, and confirmation mechanism. It is adequate for a parameterless explanatory tool, though it stops short of specifying the exact textual format of the returned message.

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 input schema is empty (zero parameters), so the description needs to add no parameter-level meaning; the 0-param baseline of 4 applies. The description focuses correctly on behavior and returned content rather than inventing parameters.

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 opens with 'Read first' and states its exact function: it 'states plainly what submit_enquiry does on Machinery Repair Quotes.' It then enumerates the key facts returned (no purchase, no guaranteed quote, free, who receives details, consent wording, confirmation), which clearly distinguishes it from the action-oriented sibling submit_enquiry and 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?

It signals when to call it via the imperative 'Read first,' indicating this should precede submit_enquiry, and it frames the tool as an explanatory overview rather than the actual submission flow. It does not explicitly mention enquiry_fields or give a when-not-to-use rule, so it falls short of the strongest routing 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 provided, the description carries the full transparency burden. It openly discloses what the tool returns—field metadata including requiredness and allowed options—and explains how the output should be consumed. It does not explicitly state that the tool is read-only or describe side effects, but this is clearly an introspection tool and the content disclosure is strong.

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 two compact sentences with no filler. It front-loads the resource, gives a structured list of returned attributes, and ends with a concrete usage instruction. Every sentence 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 zero-parameter, no-output-schema introspection tool, the description is complete: it states what the tool returns, the attributes included, and how to use those attributes when calling submit_enquiry. Nothing essential to invoking 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?

The tool has zero parameters and the schema description coverage is 100%, so there is nothing missing at the parameter level. The description adds useful downstream context by noting that field keys should be used when passing answers to submit_enquiry, which aids correct sequencing even though it is not strictly parameter semantics.

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 resource as 'Every field of the Machinery Repair Quotes enquiry' and enumerates the exact contents: key, label, type, required status, help text, and allowed options. It does not use an explicit verb like 'get' or 'list', and it does not explicitly distinguish itself from the sibling enquiry_describe, but the field-focused scope is 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 provides indirect usage guidance by telling the agent to pass answers to submit_enquiry keyed by field key, implying this tool should be used to discover valid field keys before submission. However, it does not explicitly state when to use this tool versus enquiry_describe, and there are no clear exclusions or alternative-selection conditions.

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 excels: it exposes the two-step nature, that validation happens before submission, that nothing is sent without the email-link click, and that an email is triggered. It also states the exact consent condition and wording, which is material behavioral context.

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 longer than average but fully warranted by the two-step workflow; it is front-loaded with the critical 'not a purchase/quote' warning, uses numbered stages, and every clause adds operational detail. No filler or tautology.

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 complex mutation tool with no output schema and no annotations, the description covers prerequisites (field keys), exact request patterns for both steps, the intermediate return value, the final outcome, and consent requirements. An agent has everything needed 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?

Schema coverage is already 100%, and the description adds real value on top: it explains that answers must be keyed by enquiry_fields keys, that consent is only valid when the person agreed to the quoted text, and that confirmation is the token returned from Step 1 after approval. This clarifies the optional parameter's role and the workflow dependencies.

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 Machinery Repair Quotes'), explicitly distinguishes it from a purchase or a guaranteed quote, and describes the two-step submission process. The title reinforces the action, so an agent can tell it apart from enquiry_describe and 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?

Provides explicit step-by-step invocation conditions: Step 1 validation with consent=true, then Step 2 only after the person approves, using the confirmation token. It also directs the agent to enquiry_fields for the answer keys and states the tool is not a purchase, so there is no ambiguity about when it applies.

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