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

With no annotations provided, the description carries full burden. It transparently states that 'nothing is bought, ordered or paid; no quote is guaranteed; it is free,' and enumerates the return content (who receives details, consent wording, confirmation method). This discloses the tool's non-destructive, informational nature without relying on annotations.

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.' It conveys the core purpose, key exclusions, and return content without excessive verbosity. The title is a bit unconventional but doesn't detract from the description's clarity.

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, no-output-schema tool, the description fully covers what the tool does, what it returns, and how it should be used. Nothing essential is missing for an agent to correctly invoke 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 the schema covers everything (100% coverage). The description doesn't need to add parameter details; per calibration, a zero-parameter tool gets a baseline of 4, and the description adds no confusion.

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 uses a specific verb ('states plainly') and a specific resource ('submit_enquiry on Grease Trap Cleaning Cost'), clearly distinguishing itself from sibling tools: it describes what submit_enquiry does, not the action itself. This makes the purpose unambiguous.

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 opens with 'Read first,' giving an explicit instruction to use this tool before submit_enquiry. While it doesn't name alternative tools like enquiry_fields or specify when not to use it, the directive is clear and actionable for the agent.

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 must carry the burden of behavioral disclosure. It states the content of the response but does not explicitly say whether the operation is read-only or has side effects. Since it only returns field definitions, it is likely safe, but the lack of an explicit read-only statement or mention of any prerequisites leaves some ambiguity.

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 filler. The first sentence immediately states the tool's purpose and enumerates the attributes, and the second provides a crucial usage pointer. It is front-loaded and every word 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 there is no output schema and no annotations, the description provides all essential information: what the tool returns (field attributes), and how to use the result (pass to submit_enquiry). An agent can call this tool without additional context, and the description fully compensates for the missing structured metadata.

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?

There are zero parameters, so the schema is trivially 100% covered. Per the baseline for 0 params, a score of 4 is appropriate. The description does not need to explain inputs, and it adds no parameter-related semantics; it only clarifies the output structure, which is out of scope for this dimension.

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 Grease Trap Cleaning Cost enquiry, listing the attributes (key, label, type, required, help text, allowed options). It distinguishes itself from siblings by focusing on field-level details rather than the enquiry as a whole, so an agent can tell it apart 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?

It gives a concrete usage hint: 'Pass answers to submit_enquiry keyed by field key', which tells the agent that the output should be used to construct a submission. It does not explicitly mention when not to use this tool or contrast with enquiry_describe, but the context is clear enough for an agent to infer the appropriate scenario.

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 exist, so the description carries the full burden, and it does most of it: validation behaviour, what step 1 returns, the double-opt-in email link the recipient must click before any provider sees data, and the exact scope of consent (up to three contractors, direct contact, right to stop). It stops short of covering failure/retry semantics, whether step 1 is idempotent, or what happens if the token expires.

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 negative scoping statement, then the two steps in order, which is the right structure for a procedural tool. The full consent paragraph is reproduced verbatim from the schema's consent parameter description, which is duplication that costs space without adding information.

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?

With no output schema and no annotations, the description supplies what an agent needs: what step 1 returns, that the enquiry is not submitted until step 2, and the downstream email verification step before providers see the data. Nothing required to call this correctly is missing.

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 operational meaning the schema cannot: 'answers' are keyed by field key from enquiry_fields, consent must be true only after the person has agreed, and 'confirmation' is the token obtained from step 1 and only passed on the second call. That sequencing is genuinely 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) and immediately scopes it with 'NOT a purchase, NOT a guaranteed quote', which prevents the most likely misclassification. It is clearly distinguishable from the sibling read tools enquiry_fields and enquiry_describe, which supply the inputs this tool consumes.

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: step 1 call with answers + consent=true, show the person the summary and consent line; step 2 only if the person agrees, call again with the confirmation token. The gating condition (human approval) and the alternative action (do not submit) are both stated.

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