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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 useful work: it states nothing is bought, ordered or paid, no quote is guaranteed, and the service is free. It also previews the returned content (recipient, consent wording, confirmation method). It could say more about whether calling it has any side effects, but the expectations of the flow are well set.

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?

'Read first' is a good front-loaded opener, but the second sentence is a run-on packing purpose, side-effect disclaimers, and return contents together. It is adequately sized but the density makes it harder to scan than it needs to be.

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 zero parameters, no output schema, and no annotations, the description is the only carrier of meaning, and it covers purpose, side-effect expectations, and the shape of what is returned. An agent has enough to know what it gets without opening anything else.

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 there is nothing for the description to disambiguate; per the rubric this is the baseline of 4. The schema is trivially complete.

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 resource (an ENQUIRY on a law-firm local SEO flow) and the verb (describe/states plainly + returns details), and the title reinforces that this is informational rather than a purchase. It is separable from siblings because submit_enquiry is the action and this tool explains it. The phrasing is somewhat circular ('states what submit_enquiry does') but the intent is clear.

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 invocation ordering relative to submit_enquiry, which is real when-to-use guidance. It does not spell out when NOT to use it or name enquiry_fields as the alternative, so it stops short of a full 5.

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 are supplied, so the description carries the full behavioral burden. It usefully discloses the return shape (fields with key/label/type/required/help/options) even though no output schema exists, and the keyed-by-field-key contract is a real behavioral detail. It says nothing about whether the field set is static or tenant-configurable, caching, or auth, which for a zero-annotation tool is a remaining gap.

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 payload contents come first and the actionable integration hint (keying answers into submit_enquiry) comes second, so the agent gets the essential facts immediately.

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 parameters, the description correctly compensates by enumerating the returned field attributes, which is exactly what an agent needs to construct a valid submit_enquiry call. It leaves the relationship with enquiry_describe unexplained, which is the one substantive omission.

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 there are no argument semantics to document and the baseline of 4 applies. The description does add the shape of the field keys that answers must be keyed by, which is the closest thing to parameter meaning this tool has.

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 Local SEO for law firm enquiry', and then enumerates the exact payload contents (key, label, type, required, help text, options), so an agent knows precisely what it gets back. It does not, however, distinguish itself from the sibling enquiry_describe, leaving the boundary between the two ambiguous.

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 a genuine workflow cue: pass answers to submit_enquiry keyed by field key, which tells the agent how this tool feeds the next step. But there is no statement of when to call this versus enquiry_describe, and no prerequisites or ordering guidance beyond that single downstream hint.

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 are supplied, so the description carries the full burden and does so: it discloses that step 1 only validates and returns a summary/consent line/token, that step 2 triggers an email requiring a click before any provider sees it, and spells out exactly what consent attests to. This is unusually rich behavioral disclosure 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 constraints (not a purchase, not a quote) are front-loaded and the two steps are clearly sequenced. It is dense and slightly repeats the consent wording already present in the schema, which is minor redundancy rather than filler.

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, the description compensates by describing what each step returns (summary, consent line, token; then submission plus a confirmation email). For a nested-object, two-phase tool, an agent has everything needed to call it 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 coverage is 100%, so the structured fields already define the three parameters; the description goes further by explaining that answers are keyed by field key from enquiry_fields and that confirmation is the token returned from step 1 after approval. That sequencing context is genuine added meaning 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 (submits) and resource (an enquiry to Local SEO for law firm), and immediately bounds scope with 'NOT a purchase, NOT a guaranteed quote.' It also cross-references the sibling enquiry_fields as the source of answer keys, so an agent can place it in the tool family.

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 with answers + consent, step 2 only after the person approves, passing the same answers plus the confirmation token. It also names exclusions (not a purchase, not a quote), leaving nothing to inference.

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