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

With no annotations, the description carries the full disclosure burden and meets it well. It explicitly states what the tool returns (who receives the details, consent wording, and confirmation method) and what the described process is not (no purchase, order, payment, or guaranteed quote, and it is free). This gives an agent an accurate expectation for a read-only informational tool.

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, begins with a direct imperative, and every clause adds distinct value: subject, process type, key exclusions, and returned content. There is no redundancy or 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?

For a zero-parameter, no-output-schema, no-annotation informational tool, the description is complete. It covers the purpose, scope, important caveats, and what the tool returns, so an agent can invoke it correctly without further documentation.

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 100% schema coverage, so there are no parameters for the description to clarify. Per the baseline for zero-parameter tools, a 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 identifies the tool as an explainer for 'submit_enquiry on Compressed Air Servicing' and specifies that it describes an enquiry with human providers, not a purchase or guaranteed quote. It distinguishes the tool from submit_enquiry by being the descriptive precursor, but it does not explicitly differentiate itself 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?

'Read first.' is a clear, front-loaded directive telling the agent to use this tool before acting, and the description says it 'states plainly what submit_enquiry does,' making its role as a pre-submission explainer evident. It does not explicitly mention when not to use it or name enquiry_fields as an alternative, so exclusion guidance is missing.

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 clearly states what the tool exposes: every field's key, label, type, required status, help text, and allowed options. It also explains how the returned data should be used, adding practical behavioral context beyond a simple listing. It does not explicitly state read-only behavior or return format, but the low-risk, informational nature is strongly implied.

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 sentences with no wasted words. The first sentence enumerates the full content of the returned fields; the second provides the key integration hint. The structure is front-loaded with the core description and ends with actionable guidance.

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 informational tool with no output schema and no annotations, the description is largely complete. It covers what is returned and how to use it with the sibling submit_enquiry. It could additionally mention the relationship to enquiry_describe, but this is a minor gap given the tool's simplicity.

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 schema coverage is effectively 100%, so parameter documentation is not needed. The description adds value by explaining that the output fields serve as keys for submit_enquiry, which is more useful than any parameter-level detail could be.

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 Compressed Air Servicing enquiry') and specifies the content (key, label, type, required, help text, options). It lacks an explicit verb like 'retrieves' or 'lists', but the title and context make the tool's function unambiguous. It also distinguishes itself from submit_enquiry by positioning this as the source of field 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?

The description provides useful usage guidance: 'Pass answers to submit_enquiry keyed by field key.' This implies when to use this tool—before submitting—but does not explicitly explain when to prefer it over enquiry_describe or mention any exclusions. The alternative tool is referenced indirectly through submit_enquiry rather than direct comparison.

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 burden, and it delivers: it discloses the two-step validation workflow, the confirmation token requirement, the consent condition, the email link step, and that providers only see the enquiry after the person clicks. It also clarifies the consent statement wording.

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 dense but every sentence earns its place, and the critical 'not a purchase' clarification is front-loaded. The step-by-step structure makes a complex two-phase process easy to follow without excessive verbosity.

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, but the description explains expected returns: a summary, consent line, and confirmation token in step 1, and submission plus an emailed link in step 2. It also covers permissions, user consent, and the required confirmation token, leaving no critical gap for an agent to invoke the tool 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 schema already documents the parameters. The description adds meaningful workflow context: answers are keyed by field key, consent is only true when the person agrees to the exact consent line, and confirmation contains the step 1 token. This enriches the schema rather than repeating it.

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 Compressed Air Servicing') and immediately clarifies what it is not ('NOT a purchase, NOT a guaranteed quote'). This distinguishes it clearly from the sibling tools, which are descriptive rather than action-oriented.

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 explicit step-by-step usage instructions: first call with answers and consent=true to obtain a token, then call again only after the person agrees. It clearly states when not to proceed ('only if the person agrees'), but it does not explicitly mention alternatives among sibling tools.

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