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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 burden. It discloses what the tool returns: who receives the details, the consent wording, and how the person confirms. It also clarifies the non-binding, free nature of the enquiry. It does not mention side effects or permissions, but for a zero-parameter describe tool this is not a significant omission.

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 imperative 'Read first' and then efficiently summarizes the tool's purpose and output. The title is a bit redundant with the description, but every sentence in the description adds value by specifying what is and is not delivered. It is slightly verbose but not bloated.

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, the description is complete: it states when to use it, what it explains, and what it returns. An agent can decide to invoke it and know what to expect without missing critical information.

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 accepts zero parameters, so the baseline of 4 applies. The description does not need to explain parameter meanings and instead uses its space to clarify the tool's purpose and output, which 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 names the specific verb 'States' and the resource, submit_enquiry on Colorado Roof Replacement Cost, and clearly distinguishes this tool from the actual submission tool by explaining it is a plain-language explainer of what submit_enquiry does. It also differentiates the outcome from a purchase or guaranteed quote, so an agent knows exactly what this describe tool provides.

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' gives explicit sequencing guidance to use this tool before submit_enquiry. It does not explicitly mention when to use enquiry_fields or contrast alternatives, but the context of siblings and the phrase 'Read first' make the usage scenario clear; a small gap remains since no explicit exclusion or alternative is given.

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 must carry the behavioral burden; it does by framing the tool as a metadata lookup and by assigning the actual submission action to submit_enquiry. It enumerates the returned contents, but it does not explicitly state side-effect-free behavior or error/auth conditions, which would be the main remaining gap.

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 filler; the first sentence front-loads the complete list of returned attributes and the second provides necessary integration guidance. Every word 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 simple metadata-returning tool with no parameters and no output schema, the description enumerates the full content of the response and its relationship to submit_enquiry. It does not describe the exact response envelope, but the listed attributes are enough for an agent to consume 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?

The tool takes no parameters and the schema coverage is 100%, so there is no parameter ambiguity. The baseline for a zero-parameter tool is 4, and the description adds useful semantic context by mentioning that field keys are the contract for submit_enquiry.

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 exactly what the tool exposes: each enquiry field's key, label, type, required status, help text, and allowed options. It is distinguishable from the siblings by naming the field-metadata scope, though it lacks an explicit verb such as 'returns' and does not contrast itself with enquiry_describe.

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 clear downstream context by telling the agent to pass answers to submit_enquiry keyed by field key, which links this tool's output to the correct consumer. It does not state explicit when-not-to-use conditions or describe enquiry_describe's role, so it stops short of a full alternative-selection guide.

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, and it does so thoroughly. It explains the two-step validation and submission flow, the confirmation token, the consent line, the email link requirement, and exactly what consent means by quoting the consent text.

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 'NOT a purchase' clarification, then structures the two-step process explicitly. The consent quote is included because it is essential to evaluating whether consent=true is appropriate.

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?

Despite having no output schema and no annotations, the description fully covers the tool's behavior, expected inputs, step sequencing, return values for step 1, the email follow-up, and the consent requirement. An agent has enough information to invoke the tool correctly and interpret the two-step process without additional context.

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 meaningful context: answers are 'keyed by field key from enquiry_fields', consent is tied to the exact quoted consent text, and confirmation is clearly identified as 'the confirmation token from step 1, after the person has approved the summary'. This maps each parameter to its role in the flow.

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's function: it submits an enquiry to human providers at Colorado Roof Replacement Cost, and immediately clarifies what it is NOT ('NOT a purchase, NOT a guaranteed quote'). This verb-resource pairing and explicit scope distinguishes it from sibling tools like enquiry_describe and 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 step-by-step usage instructions: Step 1 requires answers and consent=true and returns a token; Step 2 should only be called 'only if the person agrees' with the confirmation token. It also gives a precise condition for proceeding, making it clear when the tool should and should not be invoked.

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