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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 covers what happens on submission: human providers quote directly, nothing is bought or paid, no quote is guaranteed, and it is free. It also notes what information is returned, which is valuable transparency.

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 three tight sentences, front-loaded with 'Read first' and a clear statement of what it does. Every sentence adds meaningful information: the action, the non-committal nature, and the return content. No 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?

For a zero-parameter describe-style tool with no output schema, this is complete. It explains the purpose, the scope, the user-facing consequences, and the information returned. Nothing critical is missing for an agent to decide whether and how to use it.

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 nothing for the description to explain. The baseline of 4 applies, and the description appropriately does not attempt to invent parameter semantics.

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 that this tool's job is to explain what submit_enquiry does, with specific details about the enquiry outcome. It explicitly references the sibling submit_enquiry tool and positions itself as the 'read first' companion, making differentiation easy.

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' is a direct usage instruction telling the agent to consult this before acting on submit_enquiry. It does not explicitly state 'do not use this to submit an enquiry', but the contrast with submit_enquiry is strong enough that the intended workflow is clear.

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 of behavioral disclosure. It explains what the tool returns and how the output should be consumed by submit_enquiry. It does not explicitly state that the operation is read-only, but a zero-parameter field metadata tool strongly implies that, and no surprising side effects are suggested.

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, no filler. The first sentence front-loads exactly what the tool returns, and the second sentence gives actionable downstream guidance. Every clause earns its place.

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 and no output schema, the description covers the returned field attributes and the intended downstream usage well. A short note about how this differs from enquiry_describe would make it fully complete, but the current definition is sufficient for correct selection and 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, so the schema imposes no burden on the agent. The description adds useful semantic context about field keys and how they should be used when submitting answers, which exceeds the baseline for a parameterless 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 clearly states that the tool exposes every field of the HVAC Maintenance Cost enquiry, including key, label, type, required flag, help text, and allowed options. It is distinguishable from submit_enquiry because it explicitly references passing answers to that tool, though it does not explicitly contrast itself with 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 downstream guidance: pass answers to submit_enquiry keyed by field key. This implies the tool is meant to be used before submitting answers, but it does not explicitly state when to prefer this over enquiry_describe or mention exclusion cases.

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: it discloses validation behavior, the returned summary/consent line/token, the requirement that the person click an email link before any provider sees the enquiry, the cap of three providers, and the person's ability to stop further sharing. This is unusually rich mutation/consent disclosure.

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 most decision-critical fact (not a purchase) and organized as Step 1 / Step 2, so it scans well. It is dense and re-embeds the full consent sentence that already appears verbatim in the schema's consent description, which is mild 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?

For a complex two-step, consent-gated tool with no annotations and no output schema, the description covers the call sequence, the return values, and the post-submission lifecycle (email link, provider visibility). An agent has everything needed to call it 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 description coverage is 100%, so the baseline is 3; the description still adds value by tying 'answers' to field keys from enquiry_fields and explaining that 'confirmation' comes from step 1 only after the summary is approved. It stops short of adding syntax or format detail beyond the schema.

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 HVAC Maintenance Cost') and immediately disqualifies adjacent mental models ('NOT a purchase, NOT a guaranteed quote'). It is clearly separable from the sibling read-only helpers enquiry_fields and 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?

Lays out the exact when-to-call sequence: Step 1 with answers + consent=true to validate, Step 2 only if the person agrees, with the same answers plus the confirmation token. Conditions and prerequisites are explicit rather than inferable.

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