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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 full burden of behavioral disclosure, and it excels: it explicitly states no purchase occurs, no payment is made, no quote is guaranteed, the service is free, and it describes what information is returned (recipients, consent wording, confirmation method).

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 critical 'Read first' instruction. Every sentence adds distinct value: what the tool does, what it does not do, and what it returns. 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-parameter, no-output-schema informational tool, the description is fully complete. It explains the tool's purpose, disambiguates it from submission, clarifies non-purchase expectations, and summarizes the return content. An agent has everything needed to use 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?

The tool has zero parameters, so the schema is empty and there is nothing for the description to explain. This matches the baseline of 4 for zero-parameter tools; no additional parameter semantics are 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 purpose: it describes what submit_enquiry does, distinguishing it as an informational pre-read rather than a purchase or submission. The title reinforces the distinction from actual enquiry submission. This clearly differentiates it from sibling tools like 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 opening 'Read first' explicitly signals when to use this tool: before submitting an enquiry. It doesn't explicitly name alternatives or exclusions, but the context strongly implies this is the orientation/reference tool for understanding the submission flow.

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 behavioral disclosure burden. It clearly states what the tool returns (all fields and their attributes) and adds the useful context that these keys are used to pass answers to submit_enquiry. It does not explicitly state side effects or response shape, but for a read-only metadata enumeration 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. It front-loads the core resource and purpose, uses a compact colon list for the returned attributes, and closes with a practical pointer to submit_enquiry. Every sentence earns its place.

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, parameterless metadata tool, the description provides the essential return contents and a clear connection to the submission flow. However, it does not specify the response shape (array vs object) or explicitly address the relationship to enquiry_describe, which leaves a small but non-critical gap.

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. The description adds no parameter details because none are needed; the schema properties object is empty and the description does not introduce any hidden inputs.

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 ('Hernia Surgery Cost enquiry') and enumerates the returned field metadata attributes (key, label, type, required, help text, options). It differentiates itself from submit_enquiry by explaining that answers are keyed by field key, but it does not explicitly distinguish 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 implies when to use the tool: to discover the fields and keys needed before calling submit_enquiry. It does not provide explicit when-not guidance or contrast with enquiry_describe, so the usage context is present but incomplete.

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 at all, the description carries the full burden and does so: it discloses that step 1 only validates and returns a summary/consent line/token, that nothing reaches any provider until the person clicks the emailed link and selects recipients, and that chosen providers pay a fixed fee. These are genuine behavioral facts an agent could not infer from the schema alone.

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 core statement and negations are front-loaded, and the Step 1 / Step 2 structure makes the two-call sequence easy to follow. The full consent sentence is quoted in the description despite already living verbatim in the schema's `consent` property, which is a meaningful block of duplicated text.

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?

The tool is a stateful two-call mutation with a nested answers object and no output schema, so the description must explain results itself — and it does: step 1 returns a summary, consent line and token; step 2 triggers an email link that gates provider visibility. Nothing an agent needs in order to invoke either call 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 baseline is 3; the description goes beyond by explaining how the same `answers` and `consent` params are used differently across the two calls and where `confirmation` comes from. It also points at enquiry_fields for the field keys, which the schema does not say. Minor deduction because the per-parameter meaning is mostly restated rather than extended.

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 opens with a specific verb and resource ("Submits an enquiry to Hernia Surgery Cost") and immediately negates the two most likely misreadings ("NOT a purchase, NOT a guaranteed quote"), so an agent can't confuse it with a checkout or quoting tool. The two-step framing also distinguishes it from enquiry_describe/enquiry_fields, which are clearly discovery tools.

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?

It gives explicit when-to-call rules for both invocations: step 1 with answers plus consent=true, then step 2 "only if the person agrees" with the returned token. The gating condition and the human-in-the-loop requirement are stated as instructions, not left to inference.

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