site

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

With no annotations, the description carries the disclosure burden. It transparently states what the tool returns ('who receives the details, the consent wording, and how the person confirms') and clarifies the underlying process ('it is free; no quote is guaranteed'). It stops short of explicitly declaring the tool itself read-only, but the framing 'States plainly what...' strongly implies no side effects.

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 short sentences with the two-word imperative 'Read first.' front-loaded, followed by purpose and then return details. Every sentence earns its place without redundancy or 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-parameter informational tool with no output schema, the description fully covers what the tool does, the context (Measured Survey Cost), the return contents (recipients, consent wording, confirmation), and the important caveats (free, no purchase, no guaranteed quote). Nothing an agent needs to decide whether to call it 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?

The tool has zero parameters and an empty input schema, so there is no parameter-level meaning to add. A baseline of 4 is appropriate for the no-parameter case, and the description correctly spends no space on 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 verb-resource relationship: 'States plainly what submit_enquiry does on Measured Survey Cost.' The title reinforces the scope by contrasting 'an ENQUIRY with a human' with 'not a purchase, not a guaranteed quote,' which distinguishes it from the action-oriented sibling submit_enquiry.

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 ordering cue that places this tool before submit_enquiry, and the emphasis that 'nothing is bought, ordered or paid' signals a safe, no-commitment understanding step. It does not explicitly name enquiry_fields as the alternative for collecting fields, so exclusions are implied rather than stated.

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 burden and states the tool returns every field and its attributes, which is a clear behavioral description. It doesn't mention side effects, but a field-listing operation has none implied. It doesn't discuss auth/rate limits, a minor omission for a presumably safe query.

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. First sentence lists the payload, second sentence gives a forward pointer to submitting answers.

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?

No output schema exists, but the description enumerates exactly what the response will contain and how the field keys are meant to be used in submit_enquiry. Since there are no parameters, any agent can invoke it successfully from this definition.

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 explain. Per baseline for 0-param tools, this is fully adequate.

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 ('Measured Survey Cost enquiry') and enumerates the exact components returned (key, label, type, required, help text, allowed options), making its function unmistakable. It also links to submit_enquiry, setting it apart from the submission tool.

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 statement 'Pass answers to submit_enquiry keyed by field key' gives a clear usage context: call this before submitting to learn valid keys. It doesn't explicitly contrast with enquiry_describe, so it stops short of fully explicit alternatives/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?

No annotations are provided, so the description carries the full burden and does so richly: it discloses validation behavior, the returned summary/consent line/confirmation token, the post-submission email-link gate before any provider sees the data, and exactly what consent authorises (details to up to three firms, notification per firm, right to stop). This is well beyond what a bare mutation tool would state.

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 critical caveat ('NOT a purchase') and structured as a clear two-step sequence. It is long, but most of the length is the legally-relevant consent text; the only waste is that this consent wording is duplicated verbatim from the schema's consent description.

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?

There is no output schema, yet the description explains what step 1 returns (summary, consent line, confirmation token) and what happens after a successful step 2, so an agent has everything needed to drive the flow correctly. Nothing material is missing for a 3-parameter, two-call tool.

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, but the description adds meaning the schema does not: 'answers' are keyed by field key from enquiry_fields, consent must be true, and 'confirmation' is the token returned by step 1 rather than an arbitrary string. The only shortfall is that the consent value is quoted verbatim from the schema, which adds no new information.

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 Measured Survey Cost) and immediately disambiguates with 'NOT a purchase, NOT a guaranteed quote'. This cleanly separates it from the sibling tools enquiry_describe and enquiry_fields, which are clearly about describing/listing rather than submitting.

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 with the precise condition that gates step 2 ('only if the person agrees'), and what to do with step 1's output ('show the person the summary and the consent line'). The when-to-call-next logic is fully spelled out rather than implied.

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