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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 behavioral burden and does so well. It discloses that this initiates an enquiry, not a purchase, that no quote is guaranteed, that it is free, and what the tool returns in terms of recipient information, consent wording, and confirmation steps.

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 and front-loaded with 'Read first.' Every sentence adds meaningful context: what the tool does, what it does not do, and what it returns. There is no filler or repetition of schema 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?

For a parameterless description tool with no output schema, the description covers everything an agent needs: when to use it, what behavior it explains, key exclusions, and the content of the returned explanation. Nothing essential 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?

The tool has zero parameters, so the schema already has complete coverage by default. There is no parameter-level meaning for the description to add, making the baseline score of 4 appropriate.

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 descriptive explainer: it 'states plainly what submit_enquiry does' rather than performing the submission. It also distinguishes itself from submit_enquiry by emphasizing that nothing is bought, ordered, or paid, and that no quote is guaranteed.

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?

'Read first' is an explicit usage cue signaling that this tool is meant to be consulted before using submit_enquiry. It does not explicitly contrast with enquiry_fields, but the framing strongly implies a pre-submission orientation and the description makes the tool's role 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 behavioral burden and it does disclose what the returned data contains, including optional values and allowed options. It doesn't explicitly state that the call has no side effects, but the read-only nature is strongly implied by the content and the submit_enquiry distinction.

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 with no filler. The first sentence front-loads exactly what the tool returns, and the second adds the key relationship with submit_enquiry that an agent needs to act on the result.

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 fully compensates by specifying the returned metadata and how to use it. Nothing else is needed to invoke the tool correctly or to understand its role in the enquiry flow.

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 input schema has no parameters and the schema coverage is 100%, so there is nothing for the description to add about parameter semantics. The baseline of 4 for a zero-parameter tool applies.

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 returning the full field schema of the Pest Control Prices enquiry and enumerates the attributes it exposes (key, label, type, required, help text, allowed options). It also names submit_enquiry as the destination for answers, which distinguishes this introspection tool from that sibling.

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 second sentence gives concrete usage guidance: fetch field definitions, then pass answers to submit_enquiry keyed by field key. It does not explicitly enumerate when not to use it, but the reference to submit_enquiry supplies enough context for an agent to choose between the two tools.

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 delivers: it discloses that step 1 only validates and returns a summary/token, that step 2 actually submits, that consent is legally meaningful, and that an email double-opt-in link must be clicked before providers see anything. These are exactly the behavioral facts an agent cannot infer from schema or 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?

Front-loaded with the core distinction and then cleanly organized into Step 1/Step 2. It is long and the consent statement is reproduced nearly verbatim from the schema, which is mild redundancy, but the length is largely justified by the two-step flow.

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?

Even without an output schema, the description specifies what each step returns (summary, consent line, confirmation token; then submission plus an emailed confirmation link). For a two-phase, nested-parameter, side-effecting tool, nothing an agent needs to call it 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 the baseline is 3, but the description adds genuine meaning: 'answers' must be keyed by field keys from enquiry_fields, 'consent' is the person's agreement to a specific disclosed statement, and 'confirmation' is the token returned by step 1 and used only in step 2.

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) and resource (an enquiry to Pest Control Prices), and immediately disambiguates with 'NOT a purchase, NOT a guaranteed quote.' This clearly distinguishes it from the sibling read/describe tools, whose names suggest no side effects.

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 an explicit two-step protocol: step 1 with answers+consent to obtain a summary and token, step 2 only after the person agrees. The condition gating step 2 ('only if the person agrees') and the pre-submission consent requirement remove all guesswork.

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