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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 explicitly states that nothing is bought, ordered, or paid, that no quote is guaranteed, that the service is free, and that the tool returns who receives the details, the consent wording, and how confirmation works. This is substantial and accurate transparency.

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 with no wasted words. 'Read first' front-loads the key usage instruction, and each subsequent sentence adds essential behavioral or output information.

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 is complete: it states the purpose, clarifies what is not happening, and enumerates what the tool returns. No important details appear to be 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, so the baseline is 4. The description adds useful context about the tool's purpose and outputs, which is appropriate even though there are no parameter semantics to clarify.

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 explains what submit_enquiry does on Legionella Assessment Cost, including that it initiates an enquiry with human providers rather than a purchase. It is clear about the resource it describes, but it does not explicitly differentiate itself from the sibling 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 phrase 'Read first' strongly signals that this tool should be used before submit_enquiry, and the description clarifies what the user can expect. However, it does not explicitly state when to use this tool versus enquiry_fields or other alternatives, leaving some 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 full burden. It discloses the return content in detail: field keys, labels, types, required flags, help text, and allowed options. There are no hidden side effects or destructive behaviors indicated, and the description's enumeration effectively sets expectations for what the tool returns.

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 the tool's core purpose and enumerates the returned attributes; the second sentence immediately gives actionable usage context. Every word 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 zero-parameter, read-only metadata tool with no output schema, the description provides sufficient context: what data is returned and how it connects to submit_enquiry. A slight gap is that it does not clarify how enquiry_describe differs, which could help an agent choose between the siblings, but this is minor given the clarity of the description.

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 useful semantic context by explaining that field keys are the values to use when constructing answers for submit_enquiry. There are no parameters needing further elaboration.

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 what the tool provides: every field of the Legionella Assessment Cost enquiry, including key, label, type, required status, help text, and allowed options. The resource is specific and the content is enumerated concretely. It does not explicitly use a verb like 'retrieve' or 'list', but the meaning is unambiguous and distinguishable from 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?

The description gives practical routing guidance by stating that answers should be passed to submit_enquiry keyed by field key. This implies when to use the tool: before submitting an enquiry. However, it does not explicitly contrast with enquiry_describe or state when not to use this 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 full burden and does so: validation happens server-side, step 1 returns a summary/consent line/token, submission is gated on a support-confirmed token, and the person must click an emailed link before any provider sees the data. It also spells out exactly what consent authorizes (up to three assessors, stopping further disclosure), which is unusually rich causal context.

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 core action and the negative qualifiers, then the two steps in order, so structure is strong. It loses a point only because the full consent sentence is reproduced verbatim in both the description and the consent parameter schema, a redundancy that inflates length.

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, yet the description explains what step 1 returns (summary, consent line, confirmation token) and what the end state is (email link, provider visibility gated on click). For a nested-object, two-phase submission tool with no annotations, nothing an agent needs to call it 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 the baseline is 3, but the description adds real meaning: answers are keyed by field key sourced from the sibling enquiry_fields tool, consent must be paired with consent=true, and confirmation is the token returned in step 1 only after the person approves the summary. That clarifies the lifecycle and cross-tool dependency beyond the schema text.

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+resource (submit an enquiry) plus scope qualifiers that distinguish it from siblings: it is not a purchase and not a guaranteed quote at Legionella Assessment Cost. An agent can tell it apart from enquiry_describe and enquiry_fields, which only supply field metadata.

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 the condition for each call: step 1 with answers + consent=true, step 2 only if the person agrees, re-sending answers, consent and the step-1 token. It also sets exclusions up front ('NOT a purchase, NOT a guaranteed quote'), leaving no inference about when to invoke it.

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