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

With no annotations, the description carries the transparency burden and does well: it states the tool returns a plain-language explanation, explicitly denies any purchase/payment/guarantee, and enumerates the returned content (recipients, consent wording, confirmation method). It does not explicitly state that calling the tool itself has no side effects, but the describe-and-return framing makes that evident.

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 the instruction 'Read first.' Each sentence adds distinct value: what the tool explains, the non-transactional caveat, and the exact return contents. No filler or repetition within the description.

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 gives everything an agent needs: purpose, relationship to submit_enquiry, safety-relevant caveats, and a concrete list of returned details. There is no obvious missing context.

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 schema already fully covers the input surface (100% coverage). The description adds useful context about what will be returned, which is the relevant semantic information for a parameterless info 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 uses a specific verb ('States plainly') and names the exact resource it explains: what submit_enquiry does on Recruitment Agency Fees. It also clarifies the non-transactional nature ('Nothing is bought... free'), which distinguishes this informational tool from the sibling submit_enquiry and 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 'Read first' is an explicit usage directive that tells the agent to consult this before acting. It clearly positions the tool as the explanatory companion to submit_enquiry, though it does not explicitly state when not to use it or name alternatives.

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 it discloses what the tool returns: key, label, type, required flag, help text, and allowed options. It implies a read-only introspection behavior, though it does not state response shape or absence of side effects explicitly.

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 pack an exact field inventory and a forward reference to submit_enquiry with no filler. The key information is front-loaded.

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 sufficiently covers what the agent receives and how to use it. It does not explain the relationship to enquiry_describe, but that is not necessary for calling this tool 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?

The input schema has no parameters, so there are no parameter semantics to document. Baseline 4 applies because the description can add no parameter-level detail, and it instead clarifies how the returned keys connect to the submit_enquiry parameter keys.

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 identifies the resource precisely (every field of the Recruitment Agency Fees enquiry) and enumerates the meta-attributes returned. It clearly signals that this is an introspection/form-definition tool, but it does not explicitly differentiate itself from the sibling 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?

It gives actionable guidance: pass answers to submit_enquiry keyed by field key, which tells an agent to fetch fields before submitting. It does not mention when to prefer this over enquiry_describe or offer explicit 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?

No annotations are provided, so the description carries the full burden and does so richly: it discloses validation behavior, the returned summary/consent line/token, the two-phase submission, the downstream email-link click requirement before providers see anything, and the exact consent scope. It also clarifies that no purchase or guaranteed quote occurs.

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 disambiguation, then sequenced Step 1 / Step 2, which mirrors the call order. It is slightly long because the full consent text is reproduced, but that text is load-bearing and matches the schema 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?

For a two-step mutation tool with no annotations and no output schema, the description covers the whole lifecycle: what each call returns, the token handoff, the consent semantics, and the post-submission email confirmation. Nothing an agent needs to invoke 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?

With 100% schema coverage the baseline is 3, but the description adds real value: it explains that answers are keyed by field key from the sibling enquiry_fields tool, and clarifies that confirmation is the token returned in step 1 rather than a free-form value.

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') and immediately negates the most likely misinterpretation ('NOT a purchase, NOT a guaranteed quote'). Combined with the sibling names (enquiry_describe, enquiry_fields), an agent can place this tool precisely in the enquiry workflow.

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?

Explicitly defines a two-step protocol with the exact condition for step 2 ('only if the person agrees'). Names the prerequisite fields (answers keyed by enquiry_fields, consent=true) and the token needed to proceed, 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.