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

No annotations are provided, so the description carries the full burden, and it delivers: it explicitly states that nothing is bought, ordered, or paid, that no quote is guaranteed, and that the enquiry is free. It also discloses what the response contains: who receives the details, the consent wording, and how confirmation happens. This goes well beyond the minimum.

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 short sentences plus a clarifying title. The 'Read first' instruction is front-loaded, and every sentence contributes either scope, constraints, or output content. There is no filler or redundant detail.

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 explanatory tool with no output schema, the description is fully adequate: it names the underlying action, key constraints, and return content. An agent can decide to call it and know exactly what to expect without additional detail.

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 zero properties, so there are no parameters to document and schema coverage is trivially 100%. No parameter explanation is needed here, and the baseline of 4 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 names the tool's function with a specific verb: it states plainly what submit_enquiry does, and names the resource (Accountancy Practice Valuation). It clearly distinguishes itself from the sibling submit_enquiry tool by being the explanatory pre-read rather than the action itself. No tautology or ambiguity.

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 instruction, signaling that this tool should be consulted before using submit_enquiry. It frames the tool as the plain-language reference for what the submission tool does. It does not explicitly contrast with enquiry_fields, but the context is clear enough for an agent to know when to use it.

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. It discloses what the tool returns and implies a read-only metadata lookup whose output is used in submission. It does not discuss permissions or side effects, but for a zero-input metadata tool this is not a material omission.

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 short sentences with no filler. The first defines the output content, and the second connects the output to the submit_enquiry workflow, so every sentence 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?

For a no-argument metadata listing tool, this description is complete: it tells an agent exactly what will be returned and how to use that data in the related submission tool. There is no output schema, but the description enumerates the return contents sufficiently.

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 an empty input schema, so parameter-level explanation is not needed. The description adds relevant semantic context by explaining that the returned field keys become the keys for submit_enquiry answers.

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 states a clear purpose: it lists every field of the Accountancy Practice Valuation enquiry, including key, label, type, required status, help text, and allowed options. The explicit mention of feeding answers to submit_enquiry keyed by field key distinguishes it from the submission workflow.

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: fetch the field keys here, then pass answers to submit_enquiry using those keys. It names the downstream sibling and the intended workflow, though it does not explicitly contrast with enquiry_describe.

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 comprehensively. It discloses the two-step behavior, validation and summary generation, the confirmation token, the email link requirement, and the fact that providers only see the enquiry after the person clicks the link. It also explicitly negates purchase and quote guarantees, which is valuable safety 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?

The description is long but every sentence carries necessary operational or safety information. It front-loads the most important caveats ('NOT a purchase, NOT a guaranteed quote'), then walks through the two steps in a clear, linear, and scannable way. No filler wording is present.

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?

Despite lacking an output schema and annotations, the description fully covers what an agent needs to invoke the tool correctly: the step sequence, the required consent wording, the confirmation token flow, the return values at each stage, and the downstream email requirement. There is no missing behavioral or workflow context for safe use.

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?

Even though schema coverage is 100%, the description adds critical meaning beyond the schema: it explains the confirmation token's role across the two steps, requires the same answers to be reused, and defines consent as the person having read and agreed to the specific text. This transforms the schema fields from mere names into a usable workflow.

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 states a specific verb ('submits an enquiry') and the target resource ('Accountancy Practice Valuation'), and prominently clarifies that this is NOT a purchase or guaranteed quote. This clearly distinguishes the tool's purpose from related enquiry tools and leaves no ambiguity about what it accomplishes.

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 provides an explicit two-step invocation protocol: Step 1 with answers and consent=true to obtain a summary and confirmation token, then Step 2 only after person approval with the same answers plus the token. It defines the consent condition verbatim and explains the consequence of consent, leaving no doubt about when and how to call the tool.

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