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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 well: it states nothing is bought, ordered or paid, that no quote is guaranteed, and that it is free. It also discloses the return content (recipients, consent wording, confirmation method), which compensates for the absent output schema. It stops short of explicitly declaring read-only/non-destructive semantics.

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?

Three sentences, front-loaded with the 'Read first' instruction, with no filler. The wording 'States plainly what submit_enquiry does on SEO for plumbers' is slightly convoluted and the tool's own name is never used, but the size and ordering are appropriate.

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 tool with no output schema, the description covers the essentials: the nature of the operation (non-purchase, free), the guarantee disclaimer, and the kind of information returned. The main gap is that its relationship to the sibling enquiry_fields is never clarified.

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 parameters, so there is nothing for the description to disambiguate. Baseline 4 applies for a no-parameter 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 explains what the tool returns (who receives the details, consent wording, how the person confirms) and distinguishes the enquiry from a purchase, but its main clause describes what 'submit_enquiry' does rather than stating this tool's own action. An agent can infer this is a descriptive/read-only companion to submit_enquiry, but the tool's own verb is never made explicit.

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' gives an explicit sequencing hint that implies this should be consulted before submit_enquiry, which is useful. However, it names no alternatives (enquiry_fields is never mentioned) and states no conditions for when this tool is not the right one, leaving usage largely implied.

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 and no output schema, the description carries the full burden, and it does disclose the return payload (key, label, type, required, help text, options). It stops short of stating that this is a safe read-only lookup or whether the form can change, but for a zero-parameter reflection tool the essential behavioral fact – what data comes back – is covered.

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, front-loaded with what the tool returns and ending with the follow-on action. Nothing is redundant and nothing needed is missing.

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?

Because no output schema exists, the description's enumeration of returned field attributes is load-bearing and present. It could be slightly stronger on the shape of 'options' or on how it differs from enquiry_describe, but for a simple discovery tool it is close to complete.

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 the baseline is 4. The description adds no parameter information beyond the fact that outputs are keyed by 'field key', which is sufficient for a no-arg call.

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 a specific resource – the field list of the 'SEO for plumbers' enquiry – and enumerates exactly what each field contains (key, label, type, required, help text, options). An agent can tell it is a schema-discovery call. It does not, however, distinguish itself from the sibling 'enquiry_describe', so sibling differentiation is only implicit.

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 supplies a concrete workflow context: retrieve these fields, then 'pass answers to submit_enquiry keyed by field key', which tells the agent when this tool belongs in a sequence. No when-not-use condition or explicit contrast with enquiry_describe is offered.

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 provided, the description carries the full behavioral burden and does so thoroughly: it discloses the two-step validation/confirmation flow, that a confirmation token is returned in step 1 and must be passed in step 2, that the enquiry is only submitted after step 2, that an email with a required click-link is sent, and that no provider sees the enquiry until the link is clicked. It also defines the exact consent semantics. This is exceptional transparency for a mutation tool.

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 dense but well-structured, front-loading the core purpose and the two-step process in a logical order. Every sentence carries necessary information, though the consent line repetition (in the description and again in the schema) is slightly redundant. It is appropriately sized for the complexity of a two-step, consent-driven submission tool.

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 the complexity of a two-step submission with consent and email confirmation, the description is complete: it explains the full flow, the role of the confirmation token, the consent requirement, and the post-submission email step. No output schema exists, but the description mentions what step 1 returns (a summary, consent line, and confirmation token) and what happens after step 2 (email sent, provider visibility gated). An agent has everything needed to invoke this tool 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 schema already documents the parameters, setting a baseline of 3. The description adds operational context beyond the schema: answers are 'keyed by field key from enquiry_fields', the confirmation token comes specifically from step 1 after the person approved the summary, and consent=true has a precise meaning tied to the displayed line. These details help an agent use the parameters correctly across the two-step flow, though the schema already covers the basic types and requirements.

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 title and description both specify the verb and resource ('Submits an enquiry') and add critical scope: 'to SEO for plumbers', 'NOT a purchase, NOT a guaranteed quote'. This explicitly distinguishes it from the sibling enquiry_describe and enquiry_fields tools, which are clearly read-only helpers. The two-step flow is front-loaded and 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?

The description lays out an explicit when-to-use sequence: Step 1 call with answers and consent=true; Step 2 only if the person agrees, call again with the same answers, consent=true and the confirmation token. It also states the prerequisite for consent (the person has read and agreed to the specified line) and the post-submission requirement (the person must click an email link before any provider sees it). No alternative tools are needed for this specific action, and the exclusion 'NOT a purchase, NOT a guaranteed quote' further clarifies scope.

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