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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. It reveals that the underlying enquiry process starts an enquiry with human providers, involves no purchase/payment, is free, and offers no guaranteed quote. It also describes what the tool returns: recipient details, consent wording, and confirmation behavior. Slight ambiguity remains because most of the description describes submit_enquiry rather than the describe tool itself.

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 'Read first' and a plain statement of purpose. Every sentence earns its place: one states what the tool does, one clarifies exclusions and cost, and one lists the return contents. No filler or redundant schema repetition exists.

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, the description is nearly complete: it explains purpose, usage timing, non-financial nature, and returned information. It could be slightly clearer about whether the return is plain text, a structured object, or a summary, but this is a minor 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 input schema has zero parameters, so there is nothing for the description to explain about arguments. The schema coverage is 100% because the schema is empty and fully described. The description appropriately focuses on the tool's return value instead.

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 function: it explains what submit_enquiry does on Private Health Costs. It uses a specific verb ('States plainly') and resource ('submit_enquiry'), and distinguishes itself by clarifying that this is informational, not a purchase or guaranteed quote. The title reinforces the purpose and differentiates it from actually submitting an enquiry.

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 imperative 'Read first' explicitly signals when to use this tool: before proceeding with submit_enquiry. It also names the relevant sibling tool and frames this as the explanatory counterpart to it. However, it does not explicitly mention when not to use it or compare itself to enquiry_fields.

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. It discloses the exact informational content of the output and implies a read-only, non-mutating lookup by describing fields rather than actions. It does not discuss error cases or pagination, but for a no-parameter metadata lookup these are minor.

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 sentences carry all necessary information with no filler. The first sentence defines the output content compactly; the second sentence connects it to the submission workflow.

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, zero-parameter metadata tool, the description is largely complete: it names the target enquiry, lists the included field attributes, and links the output to submit_enquiry. It does not mention enquiry_describe, but nothing essential about invoking this tool 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?

The tool has zero parameters and the schema contains no properties, so no parameter documentation is needed. The description adds a useful cross-reference that the returned field keys are the keys used in submit_enquiry.

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 ('every field of the Private Health Costs enquiry') and enumerates what is returned: key, label, type, required flag, help text, and allowed options. It stops short of an explicit action verb such as 'returns' or 'lists', and only lightly distinguishes itself from siblings by referencing submit_enquiry.

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 a clear, actionable usage hint: pass answers to submit_enquiry keyed by field key. This tells an agent how to consume the result, though it does not explicitly state when to prefer this tool over enquiry_describe or state 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, the description carries the full burden and does so: it discloses that step 1 only validates, that step 2 triggers an email with a click-through link, that no provider sees the enquiry until that click, that clinics may pay a fixed fee, and the exact consent text. This is unusually rich disclosure of effects and side effects 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 critical disambiguation (NOT a purchase) and structured as Step 1 / Step 2, so the process is skimmable. It loses a point because the full consent paragraph is quoted verbatim and also appears in the schema's consent description, making the middle of the entry dense and repetitive.

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?

No output schema exists, and the description compensates by naming what step 1 returns (summary, consent line, confirmation token) and what the person receives afterward (an email with a required click). The nested answers object is explained via the enquiry_fields cross-reference. Nothing essential to correct invocation 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 real meaning: it explains that answers must be keyed by field key from enquiry_fields, that consent=true is required in both steps, and that the confirmation token is the value returned by step 1. It adds sequencing semantics the schema cannot express.

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 (submits) and resource (an enquiry to Private Health Costs) and immediately negates the two plausible misreadings: not a purchase, not a guaranteed quote. It also distinguishes itself from siblings by pointing to enquiry_fields as the source of the field keys used in the answers object.

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: step 1 with answers and consent=true returns a summary and token, step 2 with the same answers plus the token only 'if the person agrees'. The gating condition for the second call is stated, not inferred.

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