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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 well: it discloses that no purchase, order, or payment occurs, that quotes are not guaranteed, that the service is free, and that it returns who receives the details, the consent wording, and confirmation behavior. This gives the agent a clear behavioral and safety 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 concise and front-loaded: it opens with the directive 'Read first,' then states the core behavior, then lists what the tool returns. Every sentence earns its place and there is no filler or repetition of the tool name.

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?

Given zero parameters, no annotations, and no output schema, the description is sufficiently complete. It explains what the tool does, what the user gets, what is not happening, and what kinds of information are returned. An agent can confidently select and invoke this tool without further clarification.

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 are no parameter semantics to explain. Per the rubric, zero parameters earns a baseline of 4. The description does not need to compensate for schema gaps.

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 a read-first explanation of what submit_enquiry does, with a specific resource ('California HVAC Replacement Cost') and concrete outcomes (human providers, direct quotes). It differentiates itself from submit_enquiry by emphasizing that nothing is bought or guaranteed, but it does not explicitly distinguish itself from the sibling 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 phrase 'Read first' gives clear directives to use this tool before engaging with submit_enquiry. It also warns what this flow is not (not a purchase, not a guaranteed quote). However, it does not explicitly discuss when to use enquiry_fields as an alternative.

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 burden of behavioral disclosure. It accurately describes the returned data and implies a read-only metadata lookup, but it does not explicitly state that the tool has no side effects, requires no authentication, or returns a flat list/object.

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 wasted words. The field content list is dense and informative, and the cross-reference to submit_enquiry is directly actionable.

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 metadata tool, the description is largely complete: it names the resource, lists the returned attributes, and explains how to use the result. It is slightly incomplete in not mentioning the sibling enquiry_describe or the expected response format, but the core calling context is covered.

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 schema coverage is 100%, so there is no parameter ambiguity. Per the baseline for zero-parameter tools, this is appropriate; the description adds the useful context that field keys are the link to submit_enquiry.

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 returns every field of the California HVAC Replacement Cost enquiry, enumerating the exact attributes (key, label, type, required, help text, allowed options). This is specific and actionable, though 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?

The description gives clear usage context by telling the agent to pass answers to submit_enquiry keyed by field key. However, it does not specify when to use this tool instead of enquiry_describe, so the selection guidance is incomplete.

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 and does so thoroughly: it discloses that this is not a purchase/quote, that step 1 only validates and returns a token, that step 2 actually submits, and that the enquiry is only visible to providers after the person clicks an emailed link. It also names the exact consent text.

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 long but earns its length: each sentence carries operational information, and the numbered step 1/step 2 structure makes the multi-step behavior easy to follow. Front-loading the 'not a purchase' caveat is effective.

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?

Given a two-step tool with no output schema, the description fully specifies inputs, expected step 1 return values (summary, consent line, token), the condition for step 2, and downstream email behavior. It even points to enquiry_fields for answer keys, making the overall context complete.

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 schema already documents all parameters (100% coverage), and the description adds crucial contextual meaning: 'answers' are keyed by fields from enquiry_fields, 'consent' has an exact quoted meaning, and 'confirmation' is the token produced by step 1. This goes beyond the schema, though a small amount is redundant with schema descriptions.

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 an enquiry') and a concrete target ('California HVAC Replacement Cost'), and explicitly disambiguates what it is not ('NOT a purchase, NOT a guaranteed quote'). The title and description together make it easy to distinguish from the sibling enquiry_* tools.

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?

Describes a precise two-step invocation protocol: step 1 with answers and consent to obtain a token, step 2 only after the person approves, with the token. It also gives the exact consent condition and notes that a follow-up click is required, leaving no ambiguity about when each call is appropriate.

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