site

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

With no annotations, the description carries the full burden of disclosing behavior. It explicitly says nothing is bought, ordered, or paid, no quote is guaranteed, and it is free. It also discloses the return contents: who receives the details, the consent wording, and how the person confirms.

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.' Every sentence adds distinct value: what the tool explains, the key caveats, and the returned content. There is 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 descriptive tool with no output schema, the description is complete: it explains the tool's role, the workflow it describes, the limitations of the underlying process, and what information is returned. No critical usage detail 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 input schema has zero parameters and 100% coverage, so there are no parameters for the description to clarify. The baseline score of 4 applies because no parameter documentation is needed.

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 'states plainly what submit_enquiry does on Washroom Quotes' rather than performing the enquiry itself. The title further reinforces the distinction by framing the outcome as an enquiry with a human, not a purchase or guaranteed quote. This separates it from the sibling submit_enquiry 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 opening imperative 'Read first' is an explicit cue to consult this tool before taking action, and the description makes clear that it explains submit_enquiry. It does not explicitly contrast with enquiry_fields or state when not to use it, so it stops short of a full 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. It transparently discloses the content of the response (all field attributes) and the expected downstream usage. It does not mention return format or error cases, but for a zero-parameter metadata read this is acceptable.

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 wasted words. The resource and its detailed content are front-loaded, and the cross-reference to submit_enquiry is placed at the end without disrupting the core meaning.

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 zero-parameter metadata tool, the description covers the returned fields and the practical usage with submit_enquiry. It lacks an explicit statement that this is a read-only operation or a description of the response format, but neither is critical given the obvious intent and simplicity.

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 schema coverage is 100%, so the baseline of 4 applies. The description adds no parameter-specific semantics because there are none; it instead explains how the output relates to submit_enquiry, which is useful context.

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 does: it returns every field of the Washroom Quotes enquiry, listing key, label, type, required status, help text, and allowed options. It clearly distinguishes this from a general description by naming the specific field metadata, and it references the related submit_enquiry 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 implies usage when you need field-level metadata and explicitly says to pass answers to submit_enquiry keyed by field key. However, it never contrasts this with the sibling enquiry_describe, so the agent does not get explicit when-to-use versus alternative guidance.

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 behavioral burden and does so: it discloses validation on step 1, the returned summary/consent line/confirmation token, the email-confirmation requirement before any provider sees the data, the recipient cap (up to three providers), and the exact scope of consent. That is substantially more than the structured fields convey.

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-loads the critical negative scope ('NOT a purchase') and sequences the two steps cleanly. The full consent text is quoted verbatim, duplicating what the consent property description already says, which is the one redundant block.

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?

No output schema exists, and the description compensates by describing what step 1 returns and what step 2 triggers. For a nested-object, two-phase submission tool with no annotations, the workflow, consent semantics, and downstream email gate are all covered.

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 baseline is 3. The description adds real meaning on top: answers are keyed by field key sourced from the enquiry_fields tool, consent must be true and carries a defined legal meaning, and confirmation is the token returned by step 1 after approval.

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 (submits) and resource (an enquiry to Washroom Quotes), and immediately disambiguates with 'NOT a purchase, NOT a guaranteed quote.' An agent can distinguish this from the sibling enquiry_describe/enquiry_fields tools, which are referenced as inputs rather than alternatives.

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 an explicit two-step protocol: step 1 with answers + consent=true to validate, step 2 only if the person agrees, with the same answers plus the confirmation token. It also names where answers come from (enquiry_fields) and states the gate condition for the second call, leaving nothing to inference.

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