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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 of behavioral disclosure and does so well: it states that nothing is bought, ordered, or paid, that no quote is guaranteed, and that it is free. It also discloses what the returned content includes, such as who receives the details and the consent wording. It stops short of explicitly saying the tool itself performs no mutations, but the explanatory framing makes this reasonably clear.

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 most important guidance, 'Read first.' Every sentence adds value: what the enquiry is, what it is not, and what the returned description contains. There is no filler or redundant repetition.

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-parameter describe tool with no output schema, the description is complete enough for an agent to understand what it returns and why it matters. It names the core product behavior, the key exclusions (no purchase, no guarantee), and the specific return elements, so an agent can correctly choose and invoke the 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?

The tool takes zero parameters and the schema is empty with full coverage, so parameter-level documentation is unnecessary. The description appropriately focuses on behavior and return content rather than parameters, leaving no semantic gap.

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 that enquiry_describe explains what submit_enquiry does on Party Wall Quotes, including that it starts an enquiry with human providers. It distinguishes itself from submit_enquiry by being the 'read first' explanatory tool, though it does not explicitly address how it differs from enquiry_fields.

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 directive 'Read first' clearly signals that this tool should be used before submit_enquiry, and the description frames it as the plain-language explanation of that sibling tool. It provides clear context for when to use it, though it does not mention exclusions or alternatives beyond the implicit distinction from the other siblings.

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 behavioral disclosure burden. It does this well by specifying exactly what information is returned and its scope ('Every field'). As a non-mutating metadata/introspection tool, side effects are unlikely, and nothing in the description suggests otherwise.

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: the first sentence defines the tool's scope and output content, while the second sentence provides actionable usage guidance. No words are wasted.

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, no-output-schema tool, the description covers the key facts: what fields are returned and how those field keys connect to submit_enquiry. It does not explicitly position itself against enquiry_describe, but the field-specific content is sufficient for an agent to make a correct selection.

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 documentation burden; the baseline of 4 applies. The description adds useful cross-tool context by clarifying that the field keys returned here are the same keys to use when calling submit_enquiry.

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 ('every field of the Party Wall Quotes enquiry') and enumerates the exact attributes returned: key, label, type, required, help text, and options. It lacks an explicit action verb like 'Returns' or 'Lists,' and it does not directly distinguish itself from enquiry_describe, though the field-level scope is apparent.

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 instruction to pass answers to submit_enquiry keyed by field key implies this tool is useful for discovering the fields needed for submission. However, it never explicitly states when to use this tool versus enquiry_describe or provide exclusion criteria, so usage guidance remains mostly 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 does most of the work: it discloses the validation-then-submit flow, that a confirmation email with a click-through link must be completed before any provider sees the data, and the exact consent scope ('up to three party wall surveyors'). It stops short of failure-mode behavior — what happens if validation fails, if the token is reused, or whether the token expires — which matters for a two-phase mutation.

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 critical disambiguation ('NOT a purchase'), then splits the remaining content into Step 1 and Step 2, which mirrors how the agent must call it. The long consent string is unavoidable quoted legal text, not 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 nested-object, no-annotation, no-output-schema mutation, the definition covers purpose, sequencing, return contents at each step, consent semantics, and the external verification gate. The remaining gap is recovery behavior when validation fails or a token is rejected, which an agent would have to discover by trial.

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 3 is the floor, and the description earns more: it explains that `answers` is keyed by field key from enquiry_fields and, crucially, gives `confirmation` a workflow role (absent in step 1, present in step 2 with the same answers and consent) that the schema's one-line token description only hints at.

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 Party Wall Quotes') and immediately fences off the two most likely misreadings: 'NOT a purchase, NOT a guaranteed quote'. It also indirectly separates itself from the sibling read helpers by telling the agent that field keys come from enquiry_fields, so an agent can route correctly without opening both schemas.

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 a literal two-call protocol: step 1 with answers + consent=true to validate and obtain a summary/consent line/token, step 2 only after the person agrees, with the token added. Explicit preconditions, explicit gating, and an explicit stop condition are all present.

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