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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 reasonably well: it discloses that nothing is bought, ordered or paid, that no quote is guaranteed, that it is free, and what content it returns (recipient, consent wording, confirmation). For a zero-parameter informational tool this is a solid disclosure of the operation's consequences.

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 tight sentences with the directive 'Read first' front-loaded, and the key reassurance (free, nothing bought) stated plainly. Minor redundancy exists between the title's parenthetical and the body's restatement of 'not a purchase, not a guaranteed quote', but the text is otherwise lean.

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-param, no-output-schema informational tool, the description is adequate: it explains the enquiry outcome and even summarizes return content (recipient, consent wording, confirmation). The only real gap is not clarifying its relationship to the enquiry_fields sibling.

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 of 4 applies; there is no parameter meaning to add or omit. The description correctly focuses on what the call returns rather than inventing inputs.

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 purpose: it explains what submit_enquiry does on Restaurant SEO agency, clarifying that an enquiry is not a purchase or guaranteed quote. It distinguishes this informational tool from the submit action, though it never contrasts itself with the enquiry_fields sibling, so the boundary between the two 'read' tools is left somewhat 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?

'Read first' gives an explicit ordering cue that this should be consulted before submit_enquiry, which is useful. However, it offers no explicit when-not guidance and never names enquiry_fields as the alternative for inspecting field-level details, so the choice between the two read tools must be inferred.

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 it does disclose the return shape (key, label, type, required flag, help text, allowed options) in the absence of an output schema. It says nothing about auth or whether the tool has side effects, but for a static form-field listing the disclosure is adequate.

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 content of the response is front-loaded and the routing instruction follows immediately — 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?

For a parameterless read tool with no output schema, the description covers both what comes back and what to do with it. The one missing piece is how it relates to the sibling enquiry_describe, leaving a small ambiguity about which discovery tool to call first.

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; there is no parameter meaning to add. The description's keyed-by-field-key note refers to the consumer's argument shape rather than this tool's own inputs.

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 — every field of the Restaurant SEO agency enquiry — and enumerates the attributes returned (key, label, type, required, help text, options), which is far more specific than the title alone. It does not explicitly distinguish itself from the sibling enquiry_describe, so it stops short of a 5.

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 an actionable next step: 'Pass answers to submit_enquiry keyed by field key,' naming the sibling tool and the linkage between them. There is no statement of when NOT to use it or how it differs from enquiry_describe, so it is clear context without exclusions.

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 disclosure burden and does so well: it reveals the two-phase confirmation gate, that step 1 returns a summary/consent line/token, that step 2 actually submits, and that an email double-opt-in link must be clicked before any provider sees the enquiry. This is exactly the kind of side-effect and consent-flow context an agent needs 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 critical constraint ('NOT a purchase') is front-loaded and the step sequence is easy to follow. It is somewhat dense and repeats consent=true, but nearly every clause carries procedural meaning, so the length is largely justified.

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 3-parameter mutation tool with no output schema, the description covers the full lifecycle: validation, return values, token reuse, actual submission, and the downstream email confirmation gate. 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 parameter shapes are already documented, giving a baseline of 3. The description goes further by explaining that answers are keyed by field key from enquiry_fields and that confirmation is only supplied on the second call after approval, adding sequencing semantics the schema cannot express.

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 human providers) and immediately disambiguates scope with 'NOT a purchase, NOT a guaranteed quote'. The two-step framing also distinguishes it from siblings like enquiry_fields (which supplies field keys) 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?

Gives an explicit when-to-use sequence: Step 1 with answers+consent to validate and get a token, Step 2 only if the person agrees. It also states the preconditions (person has read/agreed to the consent line) and the exclusion that this is not a purchase, so an agent knows exactly when each call is appropriate.

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