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

No annotations are provided, so the description carries the behavioral disclosure burden. It does explain that the described process has no purchase, no payment, and no obligation, and it says the tool returns details about recipients, consent wording, and confirmation. However, it does not explicitly state that calling this tool itself is side-effect-free or read-only, though the name and purpose imply it.

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,' then delivers the core purpose, the key behavioral facts, and the return contents in three tight sentences. Every sentence earns its place with no wasted words.

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-argument informational tool with no output schema, the description is complete: it tells the agent what the tool does, why it matters, what the underlying process entails, and exactly what will be returned. Nothing an agent needs to decide whether to call it 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?

There are 0 parameters, so the baseline is 4 and the description does not need to document any arguments. It adds no parameter info because none 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 states a specific verb and resource: it 'States plainly what submit_enquiry does on Office Relocation Quotes'. It clearly positions itself as the read-first explanatory tool, and the title reinforces what the user gets (an enquiry with a human, not a purchase or guaranteed quote). This makes it easy to distinguish from sibling tools submit_enquiry 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 opens with 'Read first,' giving an explicit timing signal that this tool should be used before submit_enquiry. It does not name alternatives or state when not to use it, but the context is clear enough for an agent to sequence it correctly.

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. It discloses the exact content of the tool's output: key, label, type, required status, help text, and available options. It implicitly indicates a read-only metadata operation, though it does not explicitly state side-effect-free behavior.

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 first sentence enumerates the fields of the returned metadata, and the second provides a direct usage instruction tying the output to submit_enquiry.

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, low-complexity metadata tool, the description is complete: it specifies what the tool returns, lists the returned attributes, and explains the downstream use case with submit_enquiry. No additional context is needed for an agent to call or interpret 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 and the schema description coverage is effectively complete, so there is no parameter documentation burden. The description still adds value by explaining the role of field keys when constructing submit_enquiry calls.

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 provides every field of the Office Relocation Quotes enquiry, and enumerates the attributes included: key, label, type, required flag, help text, and allowed options. It is distinguished from submit_enquiry by explicitly pointing to that sibling as the place to pass the answers, though it does not differentiate from 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?

The second sentence gives practical guidance: use the field keys from this tool to key answers to submit_enquiry. However, it does not explicitly state when to use this tool versus enquiry_describe, or any conditions that would make one preferable over the other.

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 so well: it discloses the two-phase confirmation flow, that step 1 only validates and returns a summary/consent line/token, that nothing is submitted until step 2, and that the person must click an email link before any provider sees the enquiry. It also spells out the exact consent semantics and the cap of three firms — real behavioral context beyond the schema.

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 two-step skeleton and uses Step 1/Step 2 markers, so the critical flow is scannable. The verbatim consent paragraph is long and partially duplicates the schema's consent property description, which is the main source of redundancy, but it is substantively important text rather than 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?

There is no output schema, yet the description specifies what each call returns (a summary, the consent line, a confirmation token), what the person must do (approve the summary, then click an emailed link), and the limits on data sharing. For a nested-object input with a required two-call protocol, nothing an agent needs 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 baseline is 3, but the description adds genuine meaning: it ties 'answers' to field keys from enquiry_fields, mandates consent=true, and — crucially — explains that 'confirmation' is the token from step 1 used only on the second call after approval. That sequencing is not derivable from the schema alone.

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 Office Relocation Quotes') and immediately negates the two most likely misreadings ('NOT a purchase, NOT a guaranteed quote'). It also distinguishes itself from siblings by pointing at enquiry_fields for the answer keys, so an agent can tell it apart from enquiry_describe and enquiry_fields without opening a schema.

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?

Usage is spelled out as an explicit two-step protocol: Step 1 with answers + consent=true to validate and obtain a token, Step 2 'only if the person agrees' with the same answers plus the confirmation token. It names the alternative source of field keys (enquiry_fields) and states the consent precondition, 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.