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

No annotations are provided, so the description carries the full burden and does well: it discloses that nothing is bought/ordered/paid, no quote is guaranteed, the service is free, and it enumerates the returned content (recipients, consent wording, confirmation flow). This is substantive behavioral context beyond a bare read label, though it omits any note on read-only safety or freshness.

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, front-loaded with the imperative 'Read first' and the core takeaway. Slightly awkward framing ('States plainly what submit_enquiry does on Tools for PPC') adds a few words, but there is no redundancy or padding.

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 descriptive tool with no output schema, the description covers what the tool returns and the non-transactional nature of the enquiry. It is essentially complete for an agent deciding whether to read it first, though a pointer to the sibling tools would close the remaining 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 takes zero parameters and has 100% schema coverage, so there is nothing for the description to disambiguate. Baseline 4 applies since no parameter meaning is needed or missing.

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 this tool explains what submit_enquiry does — an enquiry with human providers, not a purchase or guaranteed quote — and lists the content it returns (recipients, consent wording, confirmation). It does not explicitly name its siblings enquiry_fields or submit_enquiry as alternatives, so differentiation is implied via the 'Read first' framing rather than stated.

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' gives an explicit ordering hint, suggesting it should be consumed before submit_enquiry, which is meaningful guidance. However, it names no alternatives and gives no when-not condition, so an agent must infer that enquiry_fields covers the field-level detail.

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 behavioral burden. It discloses the shape of the data returned (field key, label, type, required, help text, options), which is genuinely useful given there is no output schema. It never explicitly states the operation is read-only, nor does it cover permissions or error behavior.

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, no filler. The return payload is stated first and the follow-up action second, so the most important information is front-loaded and every clause 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 discovery tool with no annotations and no output schema, the description supplies what structured data cannot: the exact return fields and the intended follow-up call. The one omission is its relationship to enquiry_describe, which leaves a sibling-selection question unresolved.

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 there is nothing for the description to document and the baseline of 4 applies. The detail about keys being used to key answers to submit_enquiry is the only parameter-adjacent information, and it concerns a sibling's inputs rather than this tool's.

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 resource (the Tools for PPC enquiry fields) and enumerates exactly what each field carries: key, label, type, required flag, help text and allowed options. That is precise enough for an agent to know what it gets back. It stops short of differentiating itself from the sibling enquiry_describe, which an agent could easily confuse it with.

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 states the downstream workflow explicitly: 'Pass answers to submit_enquiry keyed by field key,' which tells the agent this is the discovery step before submission. There is no guidance on when to prefer it over enquiry_describe, and no exclusions are given, so it falls just short of a full when/when-not statement.

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 exist, so the description carries the full burden and it delivers: validation happening before submission, the exact return payload of step 1 (summary, consent line, confirmation token), the requirement to show the summary to the person, that submission triggers an email with a click-through link that gates provider visibility, and the precise consent wording. This is unusually complete side-effect 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?

Well front-loaded, leading with the purpose and the two 'NOT' disclaimers before the procedural detail, and every sentence carries operational content. The consent sentence is effectively stated three times (open, close, and schema), which is mild redundancy rather than padding.

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 must explain what comes back, and it does for both steps. Combined with the nested answers object and the two-step flow, it gives an agent everything needed to call correctly without guessing.

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 description coverage is 100%, so the baseline is 3, but the description adds real semantics beyond the schema: answers are keyed by field key sourced from enquiry_fields, consent is an assertion about the person's agreement, and confirmation is the token returned by step 1 rather than an arbitrary string. It does not document value types, but the schema handles that.

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 human providers), and immediately rules out the two most likely misreadings: 'NOT a purchase, NOT a guaranteed quote'. This distinguishes it from enquiry_describe and enquiry_fields, which are clearly read-only discovery 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?

Gives an explicit two-step protocol with the exact conditions: step 1 with answers+consent=true to validate, then step 2 only if the person agrees, re-calling with the same answers plus the confirmation token. It also names where field keys come from (enquiry_fields) and states the precondition for consent.

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