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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 does so richly: it discloses the two-step handshake, that step 1 validates and returns a summary/consent line/token, that step 2 actually submits, that an email confirmation gates provider visibility, and the exact scope of consent (up to three specialists, opt-out). This is well beyond a bare mutating call.

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?

Purpose and the critical 'not a purchase' disclaimer are front-loaded, and the step sequence reads cleanly. It is dense and the consent wording is duplicated from the schema, but each block earns its place given the two-step novelty of the tool.

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?

No output schema exists, yet the description explains what step 1 returns (summary, consent line, confirmation token) and what step 2 triggers (email with a click-through link). For a nested-object, two-phase tool this is complete enough to call 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 description coverage is 100%, so the baseline is 3, but the description adds flow-level meaning the schema cannot: answers must be keyed by field key from enquiry_fields, consent must be true, and confirmation is the token returned by step 1 and only passed after approval. It explains the roles rather than just restating types.

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') and immediately bounds scope with what it is NOT ('NOT a purchase, NOT a guaranteed quote'). It also situates itself against the sibling enquiry_fields by naming it as the source of the answer keys.

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?

Gives explicit when-to-call sequencing: step 1 with answers+consent=true, then step 2 only 'if the person agrees' with the returned token. It also states the human-gated condition (email link click before any provider sees it), leaving no ambiguity about prerequisites.

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