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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, and it delivers: it discloses that no purchase, order, payment, or guaranteed quote occurs, that the service is free, and that the tool returns who receives the details, the consent wording, and the confirmation method. This goes well beyond a minimal statement of purpose.

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, front-loaded with the urgent 'Read first', and every clause adds meaningful information about behavior, outcomes, and return contents. There is no filler or repetition.

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 informational tool with no output schema, the description is complete: it explains why to use it (read first), what it covers (submit_enquiry behavior, costs, guarantees, consent, confirmation), and what it returns. An agent has enough context to invoke it correctly and understand the result.

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?

There are zero parameters and the schema is empty, so the baseline of 4 applies. The description does not need to explain parameter meaning, and it does not waste space doing so.

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 that this tool explains what submit_enquiry does on Fire Compliance Cost, using a specific verb ('states') and resource ('what submit_enquiry does'), and it lists what it returns. It effectively distinguishes itself from submit_enquiry by being the read-first description layer. It does not explicitly contrast itself with the other sibling enquiry_fields, so it is not quite a 5.

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 an explicit directive that tells the agent to use this tool before calling submit_enquiry, and the description explains the task context: starting an enquiry with human providers. It does not name exclusion conditions or the alternative enquiry_fields, but the intended sequencing 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?

No annotations are provided, so the description carries the burden of explaining behavior. It makes clear this is a metadata/read-style operation that exposes field definitions rather than mutating anything, and it specifies what information will be returned. It does not discuss error or edge-case behavior, but for a simple field-listing tool this is adequate.

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 scope and contents are stated up front, and the final sentence provides practical guidance on how the returned field keys should be used.

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 metadata tool with no output schema, the description is largely complete: it names the fields returned and links to the related submission workflow. The relationship to enquiry_describe is left implicit, but that does not prevent an agent from using this 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 has zero parameters and 100% schema coverage, so there are no parameter semantics for the description to clarify. The mention of using field keys with submit_enquiry adds useful contextual meaning beyond the empty schema.

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 returning every field of the Fire Compliance Cost enquiry, and lists the exact attributes included: key, label, type, required, help text, and allowed options. The title reinforces the meaning, and the closing sentence distinguishes it from submit_enquiry by explaining that answers must be keyed by field key.

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 concrete usage context: fetch the fields first, then pass answers to submit_enquiry keyed by field key. It does not explicitly compare with enquiry_describe or state when not to use this tool, 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?

No annotations are provided, so the description carries the full behavioral burden and does so well: it discloses that step 1 validates and returns a summary plus a confirmation token, that step 2 actually submits, that the person must click an emailed link before any provider sees the data, and the exact scope of data sharing (up to three companies). This is unusually rich disclosure for a mutation 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?

Front-loaded with the core purpose and non-purchase caveat, then walks the two steps in order. Slightly long because the full consent text is reproduced even though the schema already carries it verbatim for the consent parameter, which is redundant but not harmful.

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, so the description must explain returns - and it does, naming the summary, the consent line, and the confirmation token from step 1. For a two-step, consent-gated submission tool with a nested answers object, the description covers everything needed 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?

Schema coverage is 100%, so the baseline is 3, but the description adds real meaning: it explains that answers are keyed by field key from enquiry_fields, that consent=true is a precondition, and critically that the confirmation token comes from step 1 and is only supplied once the person has approved the summary.

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?

States a specific verb (submit) and resource (enquiry) and immediately clarifies what it is NOT ('NOT a purchase, NOT a guaranteed quote'). This distinguishes it from siblings enquiry_describe and enquiry_fields, which respectively describe and enumerate fields, rather than submit data.

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?

Gives explicit when-to-use sequencing: Step 1 call with answers + consent=true, Step 2 only if the person agrees after seeing the summary, call again with the confirmation token. It also names the sibling enquiry_fields as the source of the field keys, so the agent knows how to obtain valid input.

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