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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 explaining behavior. It clearly states that nothing is bought, ordered, or paid, that no quote is guaranteed, that the service is free, and what information is returned. This gives an agent an accurate model of the tool's non-transactional, informational behavior.

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 three concise sentences with no filler. It front-loads the most important guidance ('Read first') and then delivers key behavioral facts and return-value details in a compact, well-ordered way.

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 is complete: it states what the tool does, what it does not do, and exactly what it returns (recipients of details, consent wording, confirmation method). An agent has enough to use and interpret the tool 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?

The tool has zero parameters, so there is no schema information needing elaboration. The description appropriately focuses on behavior and return content rather than inventing parameter details.

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 title and description clearly state that this tool explains what submit_enquiry does, rather than being a purchase or guaranteed quote. It names the specific resource (Forklift Servicing Cost enquiry) and the sibling tool (submit_enquiry), so an agent can distinguish it from the actual submission action.

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 explicit guidance to consult this tool before taking action, and the description frames it as a prerequisite for understanding submit_enquiry. It does not explicitly contrast with enquiry_fields, but the intended sequence and informational purpose are 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 full responsibility for behavioral disclosure. It transparently describes the returned data composition and implicitly marks the tool as an informational lookup by separating it from submission ('Pass answers to submit_enquiry'). It does not state read-only status or output format explicitly, but the content list is sufficient for a zero-parameter fields 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 entire definition is one compact sentence that front-loads the purpose and then lists the data elements and the linkage to submit_enquiry. Every part earns its place, with no filler 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?

For a tool with no parameters and no output schema, the description fully explains what the caller will receive (field metadata) and how to use it (keying submit_enquiry answers by field key). No critical information needed to invoke or interpret the result 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, so the baseline is 4. The description adds the useful semantic that answers should be keyed by field key when passed to submit_enquiry, which clarifies the meaning and purpose of the returned keys beyond the empty 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?

Description names a specific resource ('every field of the Forklift Servicing Cost enquiry') and specifies exactly what is returned: key, label, type, required status, help text, and allowed options. It lacks an explicit verb like 'lists' or 'returns', and it does not distinguish from sibling enquiry_describe, but the resource is clear enough for an agent.

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 sentence 'Pass answers to submit_enquiry keyed by field key' gives clear practical context for how to use the returned field keys, tying the tool to its sibling submit_enquiry. It does not explicitly state when not to use it or mention enquiry_describe, but the usage direction is unambiguous.

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 validation behavior, the returned artifacts (summary, consent line, confirmation token), the downstream side effect (email with a click-through link required before any provider sees the enquiry), the data-sharing scope (up to three local engineers), and the ability to stop further sharing. That 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?

Front-loaded with the key scope caveat, then structured as Step 1/Step 2, so the length is largely earned by the protocol it must convey. The main cost is the verbatim repetition of the long consent sentence already present in the schema, which adds bulk without new 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?

No annotations and no output schema, yet the description explains the return values of each step, the confirmation flow, and the consequences of submission. An agent has everything needed to run both steps correctly without inspecting 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?

Schema coverage is 100%, so the baseline is 3, but the description adds cross-parameter meaning the schema cannot: answers are keyed by field key from enquiry_fields, consent must be true in both steps, and confirmation is populated only on the second call. The consent text itself is duplicated from the schema description, so the added value is sequencing rather than new semantics.

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 Forklift Servicing Cost') and immediately bounds it with negatives ('NOT a purchase, NOT a guaranteed quote'), which is exactly the disambiguation an agent needs against quote/purchase tools. It also ties itself to the sibling enquiry_fields by naming where the answer keys come from.

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 to validate and obtain a token; Step 2 only 'if the person agrees', resubmitting with the token. The precondition for each call and the human-in-the-loop gate are spelled out, 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.