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

With no annotations provided, the description carries the full burden and does well: it states that nothing is bought, ordered, or paid, that no quote is guaranteed, that it is free, and that it returns details about recipients, consent wording, and confirmation. This gives the agent a clear model of expected behavior without relying on structured metadata.

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 compact and front-loaded with the imperative 'Read first.' Every sentence adds distinct information: what the tool explains, what it does not do, and what it returns. There is no wasted text or redundancy.

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?

The description is sufficiently complete for a parameterless informational tool with no output schema. It explains the tool's role, key exclusions, and the specific content it returns. A small gap is that it does not explicitly contrast itself with enquiry_fields, though the 'Read first' framing makes the intended placement clear.

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, so there is no parameter semantics to clarify. The description appropriately focuses on the tool's behavior and return content rather than inputs, meeting the baseline for a parameterless 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 clearly states what the tool does: it explains what submit_enquiry does on Dilapidations Quotes, including that it starts an enquiry with human providers. It also distinguishes the scope from a purchase or guaranteed quote, which differentiates it from sibling tools like 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?

The opening 'Read first' implies the tool should be used before submitting an enquiry, and the description explicitly references submit_enquiry as the action being explained. It does not explicitly name alternatives or exclusions, but the intended usage context is clear.

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. It conveys that the tool returns a comprehensive field listing including options and flags, which is useful. It does not explicitly state that this is a read-only introspection operation, but the content strongly implies it. There is no mention of error behavior, ordering, or output shape, though for a zero-parameter metadata tool this is a moderate 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 compact sentences with no filler. The first sentence enumerates exactly what the tool provides, and the second gives an actionable pointer to submit_enquiry. The most important information is front-loaded.

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 simple, zero-parameter metadata retrieval tool, the description covers the returned fields and their role in the submission workflow. It lacks an explicit statement about the absence of side effects and does not mention what happens if no fields exist, but these are minor for this use case.

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 no parameters and the schema reflects that, so parameter semantics are nearly irrelevant. The description still adds value by explaining that the returned field keys should be used as keys when calling submit_enquiry, which connects this tool's output to the sibling's input even though no parameters exist here.

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 clearly identifies the resource (Dilapidations Quotes enquiry) and the data returned (field key, label, type, required, help text, options). It is not phrased with an explicit verb like 'returns' but is unambiguous. It mentions submit_enquiry but does not explicitly distinguish itself from sibling 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 last sentence, 'Pass answers to submit_enquiry keyed by field key,' implies this tool is for gathering the field keys needed before submission. However, it does not explicitly state when to use this tool versus enquiry_describe, nor does it give exclusions or alternatives beyond the implicit submission workflow.

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 exist, so the description carries the full burden and does so: it discloses that the tool is not a purchase or guaranteed quote, that step 1 validates and returns a summary/consent line/token, that nothing reaches providers until the person clicks an email link, and exactly what consent authorizes (details to up to three named surveyors, with the ability to stop).

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-loads the key distinction (not a purchase) and then walks the two steps in order. It is long, largely because it inlines the verbatim consent text, but that text is operationally load-bearing 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 two-phase tool with a nested answers object and no output schema, the description supplies everything an agent needs: the return values of step 1, the token round-trip, and the post-submission email-verification gate. Nothing material 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 the baseline is 3, but the description adds sequencing semantics the schema cannot: answers must be keyed by field key from enquiry_fields, consent must be true, and confirmation is the step-1 token only after the summary is approved. That explains the relationship between the three parameters rather than restating them.

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 Dilapidations Quotes) and immediately scopes it with 'NOT a purchase, NOT a guaranteed quote.' It also ties itself to the sibling enquiry_fields by naming it as the source of field keys, so the agent can place it in the flow.

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=true, then step 2 only after the person agrees, adding the confirmation token. When-to-call and the gating condition are spelled out rather than inferred.

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