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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. It comprehensively states what the tool returns (who receives details, consent wording, confirmation method) and clarifies the semantics of the underlying submit_enquiry (nothing bought/ordered/paid, free, no guaranteed quote). This gives the agent full transparency about the tool's behavior and outputs without relying on annotations.

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 efficiently structured, starting with the imperative 'Read first' to front-load the usage instruction, followed by a concise explanation of the tool's purpose and output. Every sentence adds value, and the total length is appropriate for the informational content. There is no redundancy or fluff.

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 no parameters, no output schema, and no nested objects. The description fully covers what the tool returns and its role in the workflow, making it complete for an informational tool. An agent can understand exactly what to expect without needing 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?

The input schema has no properties, and schema description coverage is 100% (trivially). Per the rubric, the baseline for parameter semantics is 3 when the schema already covers everything. The description adds no parameter-specific information because there are none to elaborate on, so a 3 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 states the tool's purpose: it describes what submit_enquiry does, not the action itself. It specifies the resource (submit_enquiry on Florida Water Damage Cost) and the key distinctions (no purchase, no guaranteed quote, free). This differentiates it from the sibling tools, especially submit_enquiry, by explicitly framing itself as the 'read first' informational counterpart.

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 opens with 'Read first,' which is an explicit instruction to use this tool before interacting with submit_enquiry. It also explains what the tool is not (not a purchase, not a guaranteed quote), guiding the agent to use it when needing to understand the submission flow rather than performing it. It implies a clear when-to-use versus the sibling tools.

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. It describes what the tool returns and implies it is a read-only operation by nature, but it does not explicitly state that it has no side effects, is non-destructive, or any other behavioral traits. For a simple getter, this is adequate but not 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 a single, front-loaded sentence that immediately identifies the subject ('Every field of the Florida Water Damage Cost enquiry') and lists the key attributes. It includes a practical usage note. Every word earns its place; no fluff.

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 tool has no parameters and no output schema, the description covers the essential information: what fields are returned and how they should be used (keyed for submit_enquiry). It does not detail the output structure (e.g., array vs object) or any error cases, but for a simple metadata retrieval tool, this is reasonably complete.

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 is empty (coverage 100%). The description adds no parameter-specific information because there are none to describe. Baseline for 0 params is 4, and the description correctly focuses on the output rather than parameters.

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 returns every field of a specific enquiry (Florida Water Damage Cost) with details like key, label, type, required, help text, and options. It identifies the resource and the action (listing fields), which distinguishes it from submit_enquiry. However, it doesn't explicitly differentiate from enquiry_describe, so a clear sibling distinction is missing.

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 clear usage context: use this tool to obtain field definitions, then pass answers to submit_enquiry keyed by field key. It implies when to use it (before submitting) but doesn't explicitly mention when not to use it or compare to enquiry_describe. It gives a useful pointer to the sibling 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 provided, the description carries full behavioral disclosure. It reveals the validation step, the returned summary/consent/token, the need for a second confirmation call, the email link the person must click, and the exact consent wording the person must have agreed to. This is substantial behavioral context beyond what the schema shows.

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 tightly organized, front-loading the core purpose and exclusions before laying out the two steps in order. Every sentence carries operational value—consent text, steps, email-link behavior—with no filler or redundancy.

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 two-step state machine is fully specified: what to send in step 1, what comes back, what to show the person, when to proceed, and what happens after submission. Even without an output schema, the agent has everything needed to invoke the tool correctly and safely.

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 schema coverage is 100%, the description adds crucial semantics: answers must be keyed by enquiry_fields, consent must match the quoted consent line, and confirmation is the token from step 1 used only in step 2. It explains the lifecycle and provenance of each parameter, which the bare schema does not convey.

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 Florida Water Damage Cost') and explicitly negates what it is not ('NOT a purchase, NOT a guaranteed quote'). This clearly distinguishes it from sibling tools like enquiry_describe and enquiry_fields by naming the submit action and referencing enquiry_fields for input 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 an explicit two-step protocol: call first with answers and consent=true to get a confirmation token, then call again with that token only if the person agrees. It also names the preceding tool required to know field keys (enquiry_fields) and states exclusion criteria (not a purchase/quote), leaving no ambiguity about when and how to invoke the tool.

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