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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 disclosure burden and does useful work: it states the operation is free, that nothing is bought/ordered/paid, that no quote is guaranteed, and that the tool returns specific content (recipient details, consent wording, confirmation method). It does not explicitly state that this describe tool itself has no side effects, but describing an enquiry rather than performing one 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?

Three sentences, front-loaded with 'Read first,' and every sentence earns its place: scope, key disclaimers, and return contents. 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 informational tool with no output schema, the description is complete: it covers what the tool does, what it returns, and the key caveats an agent needs before submitting an enquiry. Nothing critical 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 already reflects that with 100% coverage, so there is no parameter meaning for the description to add. Baseline of 4 applies; the description reinforces that no input is needed by focusing entirely on what the tool returns.

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 uses a specific verb ('states plainly') and names the resource ('what submit_enquiry does on Damp Survey Prices'), so an agent can tell it is an explanatory companion to submission, not the submission itself. It clearly communicates the core meaning—an enquiry with human providers, no purchase or guaranteed quote—but does not explicitly differentiate itself from the other sibling 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 opening 'Read first' gives a clear instruction to consult this tool before acting, and the description explains the submission process so an agent knows when it is relevant. It does not explicitly state when not to use it or name alternatives, so it falls short of a 5.

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 full burden, and it does a good job by disclosing exactly what the tool exposes: key, label, type, required flag, help text, and options. It does not explicitly state that the operation is read-only, but nothing in the description implies side effects and the content is described concretely.

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 enumerates the returned field metadata, and the second connects the tool to the submission flow. Every sentence earns its place and the key scoping detail is front-loaded.

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 no-parameter, no-output-schema tool, the description is sufficient: it states the exact resource, the field metadata returned, and how to use the results. Minor gaps are the lack of an explicit no-side-effects statement and no direct comparison to sibling enquiry_describe, but the description still gives enough to select and 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?

The tool has zero parameters, so the baseline is 4 and there is no schema gap to compensate for. The description adds useful forward context by explaining that returned field keys should be used when calling 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 clearly identifies the resource ('every field of the Damp Survey Prices enquiry') and enumerates the contained elements, so an agent can tell this is the field-definition tool rather than submit_enquiry or enquiry_describe. It lacks an explicit action verb like 'lists' or 'returns', which keeps it from 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?

The instruction to pass answers to submit_enquiry keyed by field key clearly signals when this tool is useful: before submitting answers, get the field keys. It provides actionable context, though it does not explicitly name alternatives or state when not to use it.

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 fully carries the burden and exceeds expectations: it discloses that this is not a purchase or guaranteed quote, that consent must be explicitly true, that validation occurs, that a confirmation token is returned and must be used in a second call, and that an email verification step gates provider visibility. This level of behavioral detail is rare and highly valuable for a stateful, multi-step operation.

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 core purpose and scope, then proceeds logically through the two-step process. It includes the full consent text, which is lengthy but necessary for legal and operational clarity; however, this could be slightly condensed by referencing the schema's consent description instead of repeating it verbatim. The overall structure is clear and every sentence serves a purpose, but the verbatim consent repetition slightly reduces conciseness.

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 complexity of a two-step submission with consent, token, and email verification, and the lack of an output schema, the description is fully complete. It covers what the tool does, how to call it correctly in both steps, what the user must see and agree to, and what happens after submission. No critical information for an agent to invoke it correctly 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?

Schema coverage is 100%, so the input schema already documents the three parameters in detail. However, the description adds contextual meaning beyond the schema: it explains that 'answers' should be keyed by field keys from enquiry_fields (referencing a sibling tool), that 'consent' must be true and what the consent entails (with the exact consent text), and that 'confirmation' is the token from step 1. This supplements the schema's parameter descriptions, though the schema itself already covers most semantics.

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 Damp Survey Prices') and immediately clarifies scope by distinguishing it from a purchase or guaranteed quote. This precision allows an agent to differentiate it from siblings like enquiry_fields and enquiry_describe, which likely handle form definition and metadata respectively.

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, including when to call (Step 1 with answers and consent=true), what to do with the response (show summary and consent line), and the conditional second call (Step 2 only if the person agrees, with the confirmation token). It also describes the post-submission flow (email link required before providers see it), which is essential for correct invocation and user handling.

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