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

No annotations are present, so the description carries the burden of explaining behavior. It clearly indicates this tool 'states' and 'returns' information, implying a read-only, side-effect-free operation, and it adds useful context about what submit_enquiry does (free, no purchase, no guaranteed quote). It stops short of an explicit 'this tool does not actually submit', but the framing is strong and unambiguous.

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 tight sentences with no filler, and the most important directive ('Read first') is front-loaded. Every sentence earns its place by either explaining the tool's function, clarifying what it is not, or listing what it returns.

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?

This is a zero-parameter, no-output-schema informational tool, and the description names the concrete outputs you can expect: who receives the details, the consent wording, and how the person confirms. That is sufficient for an agent to decide whether to call this before submit_enquiry and to know what it will get back.

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 properties, and the description correctly adds no parameter documentation because none exists. With 0 parameters, the baseline of 4 applies and the description fully satisfies this dimension.

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 uses a specific verb ('states plainly') and names the exact resource it describes ('submit_enquiry'), so an agent knows this is a reference/explanation tool rather than the submission tool itself. The title also frames it as a non-action output ('not a purchase, not a guaranteed quote'), clearly distinguishing it from its siblings.

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?

'Read first' is an explicit usage directive telling the agent to invoke this before acting, and the description frames itself as a pre-submission reference for submit_enquiry. It does not explicitly discuss when to use enquiry_fields instead, but the core choice between describing and submitting is clear.

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 of behavioral disclosure. It transparently states what the tool returns: all fields with their metadata and allowed options. It does not explicitly describe side effects, but a field-listing tool is clearly non-mutating and the description communicates its scope accurately.

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 and every word earns its place. The first sentence compactly enumerates the field attributes, and the second sentence links the output to the related submit_enquiry tool with direct usage guidance.

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 low-complexity, zero-parameter tool with no output schema, the description is reasonably complete: it specifies the exact content scope and how to use the result. It could be slightly stronger by clarifying how this tool relates to enquiry_describe, but the provided context is sufficient for correct invocation.

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 is empty with 0 parameters, so there are no parameter semantics to explain. The baseline for zero-parameter tools is 4, and the description appropriately adds no unnecessary parameter information.

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 provides every field of the Private Surgery Costs enquiry along with key attributes such as label, type, required flag, help text, and allowed options. It distinguishes itself from submit_enquiry by mentioning that answers are passed to submit_enquiry keyed by field key, though it does not explicitly contrast 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 gives actionable usage guidance by telling the agent that answers should be passed to submit_enquiry keyed by field key, implying this tool is the source for valid keys. It does not explicitly state when to use this tool versus enquiry_describe, but the guidance is clear enough for the primary intended workflow.

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 does so: it discloses that this is not a purchase or guaranteed quote, that step 1 performs validation and returns a summary/consent line/token, that step 2 actually submits, that an email confirmation link is mandatory before any provider sees the data, and the exact consent scope (up to three hospitals/clinics chosen by the service). This is unusually complete behavioral disclosure for a mutation tool.

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-loaded with the most important framing (not a purchase), then the two steps in order. It is dense rather than wasteful, but the full verbatim consent paragraph is substantially duplicated in the schema's consent description, which costs it a point.

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, so the description compensates by explaining what each step returns (summary, consent line, confirmation token) and what happens after submission (email link, provider visibility). Combined with a nested answers object and a required consent flag, an agent has everything needed to call both stages 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?

Schema coverage is 100%, so the baseline is 3, but the description adds genuine meaning: it explains that answers are keyed by field key sourced from enquiry_fields, that consent must accompany both calls, and that the confirmation token comes from step 1 and is only used on the second call. The token's lifecycle is clearer in the description than in 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?

States a specific verb and resource ('Submits an enquiry to Private Surgery Costs') and immediately bounds it with 'NOT a purchase, NOT a guaranteed quote'. It also names the related sibling concept (answers keyed by field key from enquiry_fields), so an agent can place it relative to enquiry_fields and 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?

Gives an explicit two-step protocol with conditions: step 1 validates and returns a token, step 2 is called 'only if the person agrees' with the same answers plus the token. It also specifies the consent gate (consent=true) and that the person must click an emailed link. There is no ambiguity about when to call which stage.

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