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

With no annotations provided, the description fully carries the behavioral disclosure burden. It explicitly states that nothing is bought, ordered, or paid for, that no quote is guaranteed, that it is free, and that the response includes recipient details, consent wording, and confirmation method. This gives an agent a clear safety and expectations profile.

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, with the key directive 'Read first' placed up front and the explanatory details following in two sentences. It earns its length by conveying behavioral boundaries and return content without unnecessary repetition.

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 appropriately notes what the tool returns: who receives the details, the consent wording, and how the person confirms. Given the tool's simple, parameterless nature, the description is sufficiently complete for an agent to understand what will happen.

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 there is no parameter burden for the description to carry. The baseline of 4 applies because there is nothing additional the description needs to document about inputs.

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 as one that explains what submit_enquiry does, using a specific verb ('States plainly') and resource ('what submit_enquiry does on Battery Storage Cost'). It is not a tautology and is distinguishable from submit_enquiry, though it does not explicitly contrast with 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 phrase 'Read first' provides a clear directive to consult this tool before proceeding, and the description explains what the user will learn (no purchase, no payment, no guaranteed quote, consent details). It does not explicitly mention when not to use it or name alternatives like enquiry_fields, but the intended context is strongly implied.

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 behavioral disclosure burden. It does disclose the response contents (key, label, type, required, help text, options), which is the core behavioral trait for a form-schema lookup tool. It does not explicitly state that the operation is a read-only lookup or describe the output container, but the read-oriented nature is strongly implied.

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 a single well-structured sentence that front-loads the resource, lists the returned field attributes, and ends with actionable cross-tool guidance. There is no filler or redundant content.

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 parameterless lookup tool, the description covers what the agent will receive and how to use that output with submit_enquiry. The only minor gaps are not explicitly describing the output format (e.g., array of objects) and not differentiating from enquiry_describe, but these are not critical for successful invocation.

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 input schema confirms this, so there is no parameter semantics to document. The baseline for a parameterless tool is 4, and the description correctly does not invent parameter guidance.

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 resource (Battery Storage Cost enquiry fields) and enumerates the exact content each field entry contains: key, label, type, required flag, help text, and allowed options. It is distinct from submit_enquiry by nature, though it does not explicitly name enquiry_describe as a sibling alternative.

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 final sentence tells the agent to pass answers to submit_enquiry keyed by field key, which establishes a clear workflow connection. However, it does not explicitly state when to prefer this tool over enquiry_describe nor list 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?

With no annotations, the description carries the full burden and does so: it discloses validation behavior, the returned summary/consent line/confirmation token, the post-submission email double opt-in before any provider sees the data, and the exact scope of third-party sharing. Side effects and the consent requirement are fully surfaced.

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 with the negation first, then the numbered steps. It is dense and the long consent quotation is repeated from the schema, but every remaining sentence conveys operative behavior rather than filler.

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 or annotations exist, so the description must cover returns and safety, and it does: it names what step 1 returns, what step 2 triggers, and the privacy consequences. An agent has everything needed to drive both calls 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?

Schema coverage is 100%, so the baseline is 3, but the description adds real meaning: answers are keyed by field key from enquiry_fields, consent must be true, and confirmation is the token only obtainable from step 1 after approval. The consent wording overlaps the schema's own consent description, costing a point.

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 opens with a specific verb+resource ('Submits an enquiry to Battery Storage Cost') and immediately negates the two most likely misreadings ('NOT a purchase, NOT a guaranteed quote'). It is clearly distinguishable from the read-only siblings enquiry_describe 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?

It prescribes exactly when to call each step: step 1 with answers and consent=true, step 2 only if the person agrees, with the same answers plus the confirmation token. This is an explicit when/when-not sequence with nothing left to inference.

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