site

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

With no annotations provided, the description carries the burden of behavioral disclosure. It makes clear this is a read-only explanatory tool that 'states' and 'returns' information, and it enumerates what the user is not committing to ('Nothing is bought, ordered or paid; no quote is guaranteed; it is free'). It could be more explicit that calling this tool itself has no side effects, but the language strongly supports that.

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 and front-loaded with 'Read first', then delivers the core purpose and return content in two more sentences. It is slightly repetitive with the title, especially around the 'not a purchase' framing, but it does not waste words on irrelevant detail.

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 informational tool, the description is complete. It tells the agent what the tool does, what it clarifies for the user, and what specific information it returns: who receives details, the consent wording, and how confirmation happens. No critical context is missing for correct selection and 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 parameters and 100% schema description coverage, so there is nothing for the description to add at the parameter level. Per the calibration baseline for zero-parameter tools, a score of 4 is appropriate; the description does not need to compensate.

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 one that 'states plainly what submit_enquiry does', with a specific verb and resource, and further clarifies that it is informational, not a purchase or quote action. It does not explicitly contrast with the sibling tool enquiry_fields, so it misses the top tier on sibling differentiation, but its purpose 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 opening 'Read first' is a direct usage cue telling the agent to consult this tool before acting on submit_enquiry. It does not explicitly enumerate alternatives or state when not to use the tool, but the instruction and the contrast with submit_enquiry imply the correct workflow.

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 behavioral disclosure burden. It explicitly describes the output content: field key, label, type, required, help text, and options. This is sufficient for a read-only metadata retrieval tool with no side effects. It does not mention pagination or ordering, but those are not necessary for this simple, parameterless 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 with no filler. The first sentence front-loads exactly what fields are returned, and the second adds actionable guidance for using the result. Every clause contributes meaningful information.

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 tool with no output schema, the description fully covers what the tool returns and how to consume it. It describes the domain ('Industrial Roofing Cost enquiry'), enumerates the metadata included, and connects the output to the submit_enquiry workflow. No critical information 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 coverage is 100%, so there is no parameter documentation burden. The description correctly focuses on the output structure and how to use it with submit_enquiry. This matches the baseline for a parameterless 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 Industrial Roofing Cost enquiry') and specifies what information is provided: key, label, type, required status, help text, and allowed options. It does not use an explicit verb like 'retrieve' or 'list', but the meaning is unambiguous. It also distinguishes itself from submit_enquiry by explaining that fields are used to key answers in that tool.

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 practical usage guidance: 'Pass answers to submit_enquiry keyed by field key.' This tells an agent that this tool is used to understand the enquiry fields before submitting answers via submit_enquiry. It does not explicitly state when not to use it or mention enquiry_describe, but the intended workflow is clear.

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 of behavioral disclosure. It discloses validation on the first call, the returned summary/consent line/token, the requirement to show them to the person, the second-call submission, and the email-link requirement before any provider sees the enquiry. This is unusually thorough.

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. It front-loads the critical distinction (not a purchase/quote), then structures the two steps clearly and ends with the exact consent line. The length is justified by the procedural 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?

The tool has a multi-step interaction, consent obligations, a token handoff, and an email-verification consequence. The description covers all of these despite having no output schema to lean on. The only minor omission is error/validation-failure behavior, but the core calling contract is fully specified.

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?

Although the schema already covers 100% of parameters, the description adds valuable meaning: answers are keyed by field key from enquiry_fields, consent is tied to the exact quoted agreement text, and confirmation is the token produced in step 1. This clarifies the relationship between parameters and the two-step workflow.

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 action — submitting an enquiry to Industrial Roofing Cost — and immediately disambiguates what it is not: not a purchase and not a guaranteed quote. This clearly distinguishes the tool from siblings like enquiry_describe and enquiry_fields, which are about describing or listing fields rather than submitting.

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 explicitly provides a two-step invocation protocol: first call with answers and consent=true to get a summary and token, then call again with the token only if the person approves. It also states the consent condition exactly, leaving no ambiguity about when the tool should be called.

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