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

No annotations are present, so the description carries the full burden of behavioral disclosure. It goes beyond a generic 'describes' statement by disclosing that no purchase, order, or payment occurs, that no quote is guaranteed, that it is free, and by listing what the tool returns: who receives the details, the consent wording, and the confirmation method.

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 at four short sentences and front-loads the most important instruction ('Read first') before explaining scope and return contents. Each sentence earns its place: what the tool does, what it does not do, and what it returns.

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 no-input, no-output-schema meta-description tool, the description fully covers what an agent needs: the context (Forklift Training Quotes), the behavior being explained, the exclusions, and the specific contents of the return value. Nothing material is missing for 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?

The input schema has zero properties, and schema description coverage is 100%, so there are no parameters for the description to clarify. The baseline of 4 applies because the description correctly avoids inventing parameter information where none exists.

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 verb and resource: it 'states plainly what submit_enquiry does' on Forklift Training Quotes, and immediately contrasts that with what it does not do ('Nothing is bought, ordered or paid; no quote is guaranteed; it is free'). This clearly distinguishes it from the sibling action tool submit_enquiry and from enquiry_fields without needing to inspect 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?

The opening directive 'Read first' explicitly tells the agent when this tool should be used: before acting on submit_enquiry. It also clarifies the scope and exclusions of the described behavior, which helps the agent decide between this explanation tool and the actual submission tool. It does not explicitly name enquiry_fields as an alternative, so it falls just short of fully explicit when/when-not 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, the description carries the full burden. It discloses exactly what data the tool returns (key, label, type, required, help text, options) and implies a read-only metadata operation by directing actual submission to submit_enquiry. It stops short of explicitly stating 'read-only' or describing output formatting.

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 sentences with no wasted words. The primary content (field metadata) is front-loaded, and the usage direction is placed second. Every sentence serves a purpose.

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 retrieval tool, the description is nearly complete: it defines the output and the follow-up workflow. It could be slightly more complete by explicitly noting that calling this tool has no side effects or by distinguishing itself from enquiry_describe, but these are minor gaps.

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. The description adds useful semantic context by explaining that the returned field keys are the keys to use when passing answers to submit_enquiry, which clarifies the relationship between this tool and the submission 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 clearly identifies the resource ('Every field of the Forklift Training Quotes enquiry') and enumerates what is returned, but it lacks an explicit verb such as 'list' or 'get'. The title 'The questions the enquiry asks' partially compensates, and the reference to submit_enquiry helps distinguish it from that sibling.

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 explicit usage guidance: 'Pass answers to submit_enquiry keyed by field key.' This tells the agent how to use the result and names one sibling. However, it does not mention enquiry_describe or explicitly state when not to use this tool.

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 full behavioral disclosure. It clearly explains the two-step process, the validation and summary return, the consent line, the confirmation token, the email link that must be clicked before providers see it, and the exact consent text. It also discloses that it is not a purchase and not a guaranteed quote. This is comprehensive 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 detailed but well-structured, front-loading the critical caveat ('NOT a purchase, NOT a guaranteed quote') and then logically laying out steps 1 and 2. Every sentence serves a purpose, covering the process, the consent text, and the email link requirement without redundancy. It is appropriately sized for the tool's complexity.

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 the two-step interaction, consent requirement, and email verification step, the description covers all essential operational details. It explains the return of a summary, consent line, and confirmation token in step 1, and the final submission and email link in step 2. No output schema exists, but the description sufficiently explains the expected returns, making it complete for an agent to use 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%, and the description adds substantial meaning: it explains answers are keyed by field keys from enquiry_fields, consent must be true only when the person agrees to the specific consent line, and confirmation is the token from step 1 used to finalize. This goes beyond the schema's basic descriptions and clarifies the workflow-dependent 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 states the tool submits an enquiry to Forklift Training Quotes, explicitly distinguishes it from a purchase or guaranteed quote, and describes the two-step flow. It references the specific resource (human providers) and the action (submit), making the purpose unambiguous and differentiated from siblings like 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 description provides explicit usage context: step 1 for validation and obtaining a token, step 2 for final submission after consent, and notes the consent requirement. It also indirectly guides the agent to use enquiry_fields for the answers' field keys. However, it does not explicitly name the sibling tools or explain when to use enquiry_describe instead, so it stops short of a 5.

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