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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 burden of behavioral disclosure, and it succeeds. It clarifies that nothing is bought, ordered, or paid, that no quote is guaranteed, that the service is free, and that the tool returns details about recipients, consent wording, and confirmation process. This is rich, honest 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 three sentences with no filler, opens with the most important usage instruction ('Read first'), and packs the essential caveats and return-value highlights into a compact, readable block. 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 no-parameter, no-output-schema informational tool, the description is complete: it explains what the tool does, what it does not do, and what information it returns. There is no missing behavioral or usage context an agent would need 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?

The tool has zero parameters, so the baseline is 4. No parameter documentation is needed beyond the empty schema, and the description correctly focuses on behavior rather than filling a non-existent parameter gap.

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—'States plainly what submit_enquiry does'—and names the exact resource, Machinery Transport Quotes. It clearly distinguishes itself from sibling tools: it is the explanatory read-first tool, not the action tool (submit_enquiry) or the field definitions tool (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 instruction 'Read first' explicitly tells the agent to use this tool before taking an action, giving clear usage context. It does not explicitly enumerate when not to use it or compare with enquiry_fields, but the ordering guidance is sufficient for this low-complexity informational 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 the burden of explaining behavior. It states the returned content and the exhaustive scope ('Every field'), but does not explicitly disclose that this is a read-only, side-effect-free lookup or describe the response shape. This is adequate for a simple metadata tool but leaves some traits implicit.

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 short sentences convey the purpose, content, and downstream use with no redundancy. The main information is front-loaded and every clause 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 parameterless metadata tool with no output schema and no annotations, the description is nearly sufficient: it tells the agent what fields are returned and how to use them. It lacks only an explicit statement of the response container or a direct relationship to enquiry_describe, but neither is essential for invoking the tool.

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 there is no parameter-level documentation burden. The description usefully explains how the returned field keys relate to submit_enquiry, which is the only semantic guidance an agent needs.

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 Transport Quotes enquiry' and enumerates the attributes returned (key, label, type, required, help text, options). It lacks an explicit verb such as 'list' or 'retrieve', and it does not directly contrast itself with enquiry_describe, though the field-specific scope is clear.

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 clear workflow: obtain fields from this tool, then pass answers to submit_enquiry using the field keys. It does not explicitly state when not to use this tool or how it differs from enquiry_describe, so it falls 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.

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 well: it discloses that this is not a purchase or guaranteed quote, that consent is mandatory, that a confirmation token gates submission, and that the person must click an emailed link before any provider sees the enquiry. It also explains the downstream consequence (up to three operators contact the person directly, with notification as details are shared and an opt-out). This is far more behavioral context than any annotation would provide.

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 two-step flow is front-loaded and easy to follow, with the negative framing ('NOT a purchase') placed first. It loses a point because the full consent text is reproduced verbatim even though the same string already appears in the schema's consent description, adding roughly sixty redundant words.

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?

There is no output schema, yet the description explains what each step returns (step 1: a summary, the consent line and a confirmation token; step 2: submission with an email verification link). Combined with the consent semantics and the dependency on enquiry_fields, an agent has everything needed to invoke this 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%, so the baseline is 3, but the description adds real meaning beyond the schema: it specifies that the confirmation token is only used on step 2 after approval, that answers must be keyed by field key from enquiry_fields, and it reifies what consent=true asserts. Those are ordering/semantic constraints the flat schema cannot express.

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 ('Submits an enquiry to Machinery Transport Quotes') and immediately scopes it ('NOT a purchase, NOT a guaranteed quote'), which is the key disambiguation against a purchase flow. It also names the sibling it depends on ('keyed by field key from enquiry_fields'), so an agent can distinguish this tool from the read-only siblings.

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 gives explicit call conditions per step: step 1 with answers and consent=true, step 2 only after the person approves the summary, passing the same answers plus the confirmation token. It also ties the answers argument to enquiry_fields as the key source. It does not, however, mention enquiry_describe or state when not to use this tool, so it stays short of full routing guidance.

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