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

With no annotations provided, the description carries full behavioral disclosure. It explains exactly what happens ('starts an enquiry with human providers who quote directly'), what does not happen ('nothing is bought, ordered or paid'), the cost ('it is free'), and what the tool returns: recipients, consent wording, and confirmation process.

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.' The main sentence is dense but organized with semicolons, and there is little waste. Minor redundancy with the title's 'not a purchase, not a guaranteed quote' prevents a perfect score.

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, documentation-style tool with no output schema, the description is complete: it explains what the tool does, what submit_enquiry does, what is NOT involved, and exactly what information is returned (recipients, consent wording, confirmation method). An agent has enough context to call and interpret the result.

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 empty schema properties, so the schema provides no parameter semantics. The description appropriately focuses on the tool's output contents rather than parameters, which matches the baseline for a zero-parameter tool.

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 specific verb-resource relationship: it 'states plainly what submit_enquiry does' rather than performing the enquiry. It clearly identifies the tool as a descriptive/educational tool and distinguishes it from the action-oriented sibling submit_enquiry by emphasizing 'nothing is bought, ordered or paid; no quote is guaranteed.'

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 instruction 'Read first' gives explicit sequencing context: use this before acting on submit_enquiry. It also sets expectations about what the tool is not (a purchase or guaranteed quote), but it does not explicitly name alternatives like enquiry_fields or state when to prefer them.

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?

No annotations are provided, so the description carries the full behavioral disclosure burden. It clearly states what the tool returns and enumerates the output contents, which is strong for an introspection endpoint. It does not explicitly say 'read-only' or 'no side effects', but the wording 'Every field of the enquiry' conveys a non-mutating lookup clearly.

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 exact output content, and the second sentence gives a critical usage pointer to submit_enquiry. 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 simple no-parameter introspection tool, the description is complete. It names the specific enquiry, lists the return fields, and explains how to use the result with submit_enquiry. Since there is no output schema, the description successfully carries the burden of explaining what the agent will receive.

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 takes zero parameters, so parameter semantics are a non-issue. The description still adds value by explaining how the output's field keys should be used as parameter keys in submit_enquiry. With no parameters and an empty schema, the baseline of 4 is appropriate and the description provides no unnecessary parameter syntax.

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 defines the tool as returning every field of the Access Control Cost enquiry, enumerating the exact attributes: key, label, type, required, help text, and allowed options. This is specific and distinguishes it from sibling tools like enquiry_describe by focusing on the field-level schema rather than the enquiry as a whole.

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 clear context by explaining that answers should be passed to submit_enquiry keyed by field key, which tells an agent why this tool matters and how its output connects to a sibling tool. It does not explicitly contrast with enquiry_describe, but the usage context is unambiguous enough for an agent to select this tool when it needs field definitions.

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 most of it well: it discloses validation behavior, the returned summary/consent line/token, the double-confirmation requirement, and the post-submission email-link gate before any provider sees the data. It does not mention failure modes (e.g. what happens on an invalid answers payload or a bad token), which keeps it short of a 5.

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 critical scoping ('NOT a purchase') is front-loaded and the two steps are ordered and labelled, which is the right structure for a stateful call. It loses a point because the full consent sentence is quoted verbatim in both the description and the schema's consent property, a duplication that adds length without new 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 two-phase mutation with no output schema and no annotations, the description covers everything an agent needs: what each call does, what is returned at each stage, the token handoff, the consent contract, and the downstream email-verification step. 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?

Schema coverage is 100% so the baseline is 3, but the description adds real value beyond the schema: it ties the answers object to keys sourced from enquiry_fields, and it explains that confirmation is only populated in step 2 (it does not appear in the required list). That sequencing semantics is not derivable from 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?

The description names a specific verb (submits) and resource (an enquiry to Access Control Cost) and immediately disambiguates the two most likely misreadings: NOT a purchase, NOT a guaranteed quote. It is clearly distinct from the read-only siblings enquiry_describe and enquiry_fields, so an agent can select it without opening a 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?

It spells out the exact two-step calling protocol: step 1 with answers + consent=true to validate, step 2 with the same answers, consent=true and the confirmation token, and only if the person agrees. Both the when and the gating condition are explicit, leaving nothing to inference.

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