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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 transparently states that nothing is bought, ordered, or paid, that no quote is guaranteed, and that it is free. It also discloses what the tool returns: who receives the details, consent wording, and confirmation method. This is comprehensive and beyond what annotations could have provided.

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, front-loaded with 'Read first,' and every word earns its place. It conveys the purpose, key constraints (no purchase, no guaranteed quote, free), and return content without any fluff. This is a model of concise, efficient writing.

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 description tool with no parameters, no output schema, and no annotations, the description is fully self-contained. It explains what the tool does, what it returns, and the context (Generator Servicing Cost). An agent can correctly decide when to call it and what to expect from the result. There are no missing pieces.

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 coverage is 100% (trivially). The description does not need to explain parameters, and it doesn't attempt to. Per the rubric, 0 parameters warrants a baseline of 4, which is appropriate here since the description adds no parameter-specific value but also requires none.

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 'States plainly what submit_enquiry does' and explains that it starts an enquiry with human providers who quote directly. The title reinforces this by summarizing what the user gets. It distinguishes itself from siblings by being the 'Read first' explanatory tool, not the action tool.

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 begins with 'Read first,' providing explicit guidance to use this tool before submitting an enquiry. It also clarifies the context (Generator Servicing Cost) and what the tool does not do (purchase, guaranteed quote). However, it does not explicitly mention alternatives like enquiry_fields, but the 'Read first' directive serves as a clear usage instruction.

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 transparency burden. It clearly implies a read-only lookup by describing the field catalog and its contents, and it discloses the relevant output semantics for downstream use. It does not mention pagination or authentication, but for a zero-parameter field-listing tool this is a minor gap.

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 tight sentences: the first front-loads the complete list of returned attributes, and the second provides the actionable link to submit_enquiry. Every word earns its place and there is no repetition of the title.

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, parameterless lookup tool with no output schema, the description fully conveys what is returned and how to use the result. It even adds the cross-tool relationship to submit_enquiry, making the description adequate on its own.

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 accepts zero parameters, so the baseline is 4. The description correctly adds no parameter-specific information because none exists. There is nothing missing here.

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 ('Generator Servicing Cost enquiry') and enumerates exactly what is returned: key, label, type, required, help text, and options. It does so without an explicit verb like 'list', but the meaning is unambiguous and the resource is precisely bounded. It distinguishes itself from submit_enquiry, though not from 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?

The description gives clear practical context: obtain field keys from this tool, then pass answers to submit_enquiry keyed by those field keys. This tells an agent when this tool is useful and how it connects to a sibling, though it does not explicitly discuss when not to use it or contrast it with enquiry_describe.

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 validation behavior, the exact artifacts returned in step 1 (summary, consent line, confirmation token), that submission triggers an email link the person must click before any provider sees it, and that details go to up to three providers. It also defines what consent semantically means, including how the person can stop further firms.

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?

Long but front-loaded: it leads with what the tool is not, then walks through steps in order. The verbatim consent text is duplicated from the schema's consent description, which is the one mildly wasteful element, but it is defensible since it is a user-facing statement that must be shown to the person.

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, yet the description explains what step 1 returns and what step 2 produces (submission plus a click-to-confirm email), covering the nested 'answers' object via the enquiry_fields reference. An agent has everything needed to drive the two-step flow correctly, including the human-in-the-loop checkpoints.

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 beyond the schema: 'answers' must be keyed by field key from enquiry_fields, and 'confirmation' is a token obtained from step 1 only after human approval, which the schema states but the description ties into the workflow. It stops short of documenting value types or edge cases beyond 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 and resource ('Submits an enquiry to Generator Servicing Cost') and immediately bounds it with negations ('NOT a purchase, NOT a guaranteed quote'), separating it from anything a sibling might imply. An agent can tell exactly what this tool does before opening the 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?

Gives an explicit two-step protocol: call once with answers + consent=true to validate and obtain a token, show the human the summary and consent line, then call again only if the person agrees. The conditional gate ('only if the person agrees') and the ordering are spelled out, 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.