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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: it discloses validation behavior, the returned summary/consent line/token, the mandatory email-link click before any provider sees the enquiry, the disclosure that details go to up to three contractors who contact the person directly, and the ability to stop further sharing. That is rich, non-obvious behavioral context.

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 purpose and the two-step flow before the consent text. It is dense but each sentence carries operational information; the verbatim consent string is largely duplicated from the schema's consent description, which is the one piece of redundancy.

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, and the description compensates by stating what Step 1 returns and what the person receives after Step 2. Combined with the 100%-covered schema and the pointer to enquiry_fields, an agent has everything needed to invoke 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 baseline is 3, but the description adds real meaning beyond the schema: it explains that 'answers' must be keyed by field key from enquiry_fields, that consent=true is the gating condition, and that 'confirmation' is the token returned by Step 1 after human approval — clarifying the same call's dual role.

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?

Specific verb+resource ('Submits an enquiry to California HVAC Replacement Cost') plus an immediate scope boundary: 'NOT a purchase, NOT a guaranteed quote.' This distinguishes it from a purchase/quote tool and from the sibling read-only tools 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?

The description lays out the exact when: Step 1 with answers+consent=true to validate, Step 2 only if the person agrees, with the same answers plus the confirmation token. It states the precondition for the second call explicitly, 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.