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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 declares this is a read operation, that nothing is bought/ordered/paid, that no quote is guaranteed, that it is free, and it enumerates what is returned (recipients, consent wording, confirmation). It does not describe any side effects or failure modes, but for a zero-param read tool this is solid disclosure.

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 front-loaded and the body is a single tight sentence. There is mild redundancy in the near-synonym list "bought, ordered or paid," but it reads as deliberate emphasis on the non-transactional nature 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?

For a zero-param, no-output-schema describe tool, the description supplies the semantic context an agent needs: what the tool returns and what it is not. It is close to complete; only the relationship to enquiry_fields is absent.

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 per the rubric the baseline is 4. There is nothing for the description to clarify beyond what an empty schema already conveys.

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 that this tool returns plain-language documentation of what submit_enquiry does, naming the specific resource (the enquiry flow on PPC agency Leeds). It clearly distinguishes itself from the write-side submit_enquiry, though it never mentions the sibling enquiry_fields, so sibling differentiation is only partial.

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 cue relative to submit_enquiry, which is genuine when-to-use guidance. However, there is no mention of when not to use it or how it relates to enquiry_fields, leaving the alternative undocumented.

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 shape of the returned metadata, but never states that this is a non-mutating read, whether results are cached or stale, or whether the field set is locale/agency scoped.

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, zero filler, and the returned-attribute list is front-loaded before the downstream usage note. Nothing could be cut without losing 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?

With no output schema, the description must explain return values, and it does so by enumerating key, label, type, required, help text and options, plus how the output feeds submit_enquiry. An agent has enough to call and consume it, though it is silent on field ordering or conditional visibility rules.

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 correctly implies a parameterless, whole-form introspection call and adds the meaningful detail that field keys are the join key 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?

States concretely what the tool returns: the key, label, type, required flag, help text and allowed options for every field of the PPC agency Leeds enquiry. It is readily distinguishable from submit_enquiry, which it names directly, though it draws no explicit line against 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?

The closing sentence gives clear operational context: fetch the field metadata here, then pass answers to submit_enquiry keyed by field key, which establishes this as the pre-submission discovery step. It stops short of saying when to prefer this over the sibling enquiry_describe, so no exclusions are 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, the description carries the full burden and does so: it discloses the two-step protocol, that step 1 is validation-only and returns summary/consent line/token, that the real submission happens in step 2, that an email with a click-through link is sent, and that no provider sees the enquiry before that click. Side effects, gating and consent semantics are all surfaced.

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 not-a-purchase caveat, then cleanly split into Step 1 and Step 2. The verbatim consent sentence is long but is the legally operative text the agent must show, so it earns its place. Slightly dense overall but no 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?

For a complex, stateful, two-call tool with nested answers, no output schema, and no annotations, the description supplies the return values of step 1, the required carry-forward token, and the downstream email-confirmation state. An agent has everything needed to drive both invocations 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 baseline is 3. The description earns above baseline by explaining the relationship between parameters over time: 'answers' keyed by field key from enquiry_fields, consent=true in both steps, and crucially the 'confirmation' token only present on Step 2 after approval — context the schema's bare descriptions do not convey.

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+resource ('Submits an enquiry to PPC agency Leeds') and immediately narrows scope with 'NOT a purchase, NOT a guaranteed quote'. This distinguishes it clearly from siblings enquiry_describe and enquiry_fields, which describe/return fields rather than submit anything.

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?

Explicit when-to-use for both calls: Step 1 unconditionally with answers and consent=true, Step 2 'only if the person agrees'. It also names the source of truth for keys (enquiry_fields) and rules out the purchase/quote interpretation. Nothing is left to inference.

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