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

With no annotations, the description carries the transparency burden and does well: it explicitly states that nothing is bought, ordered, or paid, that quotes are not guaranteed, and that the enquiry is free. It also mentions what information the tool returns, giving a clear read-only, informational profile.

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 the imperative 'Read first,' then delivers the core facts in a direct sequence. It is slightly dense but every sentence contributes meaning, and there is no redundant 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, the description covers what the tool explains, what it returns, and the key caveats. It does not require an output schema because it describes the return content in prose, and it adequately supports an agent deciding to call it before submit_enquiry.

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 coverage is effectively complete, so there are no parameter semantics to explain. The description appropriately focuses on the tool's output and purpose rather than inventing parameter details.

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 a descriptive helper that explains what submit_enquiry does, including the key facts that no purchase or payment occurs and no quote is guaranteed. It names the related sibling submit_enquiry, which helps differentiate it from an actual submission action, though it does not explicitly contrast with 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' signals that this tool should be used before engaging with submit_enquiry, giving a clear usage context. However, it does not explicitly state when not to use it or compare it against enquiry_fields, leaving some routing inference to the agent.

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 burden of disclosing behavior. It transparently states what data the tool exposes and hints that it is an informational, read-only operation by saying answers should be passed to submit_enquiry rather than to this tool. It does not mention potential caveats such as response format, but for a zero-parameter introspection tool this is largely sufficient.

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 front-loads exactly what the tool returns, and the second sentence gives actionable guidance about how to use the returned field keys.

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 tool with no output schema and no annotations, the description covers the returned content and how to use it with a sibling tool. It could be slightly more complete by distinguishing itself from enquiry_describe, but overall it gives an agent enough to call and apply 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 no parameters, so the baseline is 4. The description adds relevant guidance that the returned field keys should be used to key answers for submit_enquiry, which enriches the meaning of the tool's output even though the input schema is empty.

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 LEV Testing Cost enquiry, along with each field's key, label, type, required status, help text, and options. It is specific about the resource and content, though it does not explicitly differentiate itself from the sibling 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 gives useful context by telling the agent to pass answers to submit_enquiry keyed by field key, implicitly indicating when this tool should be used before submission. However, it does not explicitly explain when to use this versus enquiry_describe or state any exclusions.

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, and it does so thoroughly. It discloses the two-step validation-and-submit behavior, the requirement that consent is explicit, the email-link click requirement before providers see anything, and the exact consent wording. This gives an agent an accurate model of side effects and sequencing.

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 dense but every sentence earns its place: it starts with the core distinction, then gives the two steps, then the consent requirement. The consent phrasing is repeated from the schema, but here it is essential context for the agent's conversation flow, not 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 two-step mutation tool with no output schema and no annotations, the description fully explains the return values at each step (summary, consent line, confirmation token), the expected user interaction, and the final email behavior. It even mentions the non-obvious requirement that the user must click the emailed link before submission is visible to providers. Nothing essential 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?

Although the schema already documents all three parameters, the description adds critical semantic meaning: 'confirmation' is tied to step 2, 'answers' must be keyed by field keys from enquiry_fields, and 'consent' is tied to a specific consent statement. It explains how the parameters relate across the two calls, going beyond mere field definitions.

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 clear verb and resource: 'Submits an enquiry to LEV Testing Cost,' and immediately distinguishes it from a purchase or guaranteed quote. The two-step flow is explicit, making the tool's purpose and scope unambiguous even before considering the input 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?

The description provides exact step-by-step usage: call first with answers and consent=true, review the returned summary and consent line, then call again only if the person agrees, adding the confirmation token. It also says what the tool is NOT for and references 'enquiry_fields' for the answer keys, giving clear routing guidance.

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