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

Since no annotations are provided, the description carries the full burden. It explains what the tool returns (who receives details, consent wording, confirmation method) and frames itself as descriptive of submit_enquiry, but it never explicitly states that calling this tool does not itself start an enquiry or have side effects. Given the title's wording, that omission is a meaningful gap.

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 three sentences, front-loaded with the 'Read first' instruction, and wastes little space. It could be slightly tighter since the title already carries some of the same meaning, but overall it is concise and well organized.

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 covers the essential context: what process it explains, what the user can expect, and what information it returns. It is not exhaustively detailed about output formatting, but the low complexity makes the current detail adequate.

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 has no properties, so the baseline is 4. No parameter-level explanation is needed, and the description correctly avoids inventing parameter guidance.

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's job: it states what submit_enquiry does, framing it as an informational description rather than the submission itself. It names the resource (Industrial Cleaning Quotes enquiry process) and the sibling it explains, but it does not explicitly contrast itself with enquiry_fields, so it falls just short of 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 opening phrase 'Read first' is a clear directive to use this tool before acting on submit_enquiry, which gives an agent a concrete usage cue. It does not explicitly describe when not to use it or compare alternatives, but 'Read first' provides sufficient context for a 0-parameter informational tool.

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 burden, and it does disclose the informational nature of the call and what it returns: every field with its key, label, type, required status, help text, and options. It implies a safe read-only listing and gives no indication of side effects. It does not discuss errors or access restrictions, but for a parameterless metadata tool this is not a significant omission.

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 concise sentences with no waste: the first front-loads the tool's content, and the second gives a practical cross-reference to submit_enquiry. Every sentence adds value and the structure is easy to scan.

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 introspection tool, the description fully enumerates the expected return content and explains how to use the returned keys. Nothing essential is missing for an agent to call the tool and act on its 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?

The tool accepts zero parameters, so the baseline is 4. The description correctly adds no parameter semantics because there are no parameters to document, and the schema already covers everything 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 that the tool exposes every field of the Industrial Cleaning Quotes enquiry and enumerates the field metadata: key, label, type, required flag, help text, and allowed options. This clearly differentiates it from submit_enquiry, though it does not explicitly contrast it with 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 description provides a clear usage context: to learn the fields/keys of the enquiry, and it explicitly instructs the agent to pass answers to submit_enquiry keyed by field key. It does not state when-not-to-use cases or explicitly mention enquiry_describe as an alternative, so exclusions are only implied.

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 bears the full burden of behavioral disclosure. It excels by revealing that this is not a purchase or guaranteed quote, defining consent with the exact text, and disclosing that the enquiry reaches providers only after the person clicks the email link. It also describes step-1 validation and the token hand-off, which are non-obvious behaviors.

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 long but every sentence earns its place. It front-loads the core purpose and then structures the two steps clearly. The quoted consent text removes any ambiguity, and the flow is easy to follow despite the complexity.

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 two-step, human-in-the-loop submission with no output schema, the description is complete. It covers inputs, expected returns (summary, consent line, confirmation token), the user-consent gate, and the email-click requirement. An agent has 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?

Although schema coverage is 100%, the description adds crucial semantics: answers must be keyed by field keys from enquiry_fields, consent means the person has agreed to the exact quoted line, and confirmation is the token produced in step 1. This goes well beyond the schema's structural descriptions.

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 the specific action: submits an enquiry to Industrial Cleaning Quotes. It explicitly distinguishes this from a purchase and a guaranteed quote, and the title reinforces the two-step nature. This clearly separates it from the sibling tools, which are about describing enquiries and fetching field definitions.

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 explicit step-by-step usage: call with answers and consent=true, then conditionally call again with the confirmation token. It also references enquiry_fields for answer keys, which orients the agent to the correct companion tool. It does not explicitly name alternatives, but the workflow context is unambiguous.

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