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

With no annotations, the description carries the burden of disclosing behavior. It makes clear this is an informational tool that describes behavior and returns specific details, implying no submission or side effect occurs. It also discloses what the returned content covers, which is useful beyond the tool name.

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.' Each sentence adds useful information about what the tool does, what it clarifies, and what it returns, with no 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 simple informational tool with no parameters and no output schema, the description fully covers the tool's purpose, the key facts it communicates, and the content of its return value. The agent has everything needed to decide when and how to call it.

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 accepts zero parameters, and the schema confirms this with an empty properties object. The description adds no parameter detail, but none is needed; the baseline for a zero-parameter tool is appropriately strong.

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 this tool explains what submit_enquiry does, naming the specific resource and the behavior it describes. It differentiates itself from the sibling tools by positioning itself as the 'Read first' companion to 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' explicitly tells the agent to use this tool before submit_enquiry, providing clear contextual guidance. It does not name alternatives explicitly, but in context the usage is unmistakable.

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 provided, the description carries the full burden of explaining behavior. It clearly implies a read-only introspection operation returning field metadata, and it states the scope of the data returned. It does not mention authentication or side effects, but for a fields lookup this is not a significant 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 concise sentences with no filler. The core content is front-loaded, and the cross-tool guidance is kept to a single sentence.

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?

Given the absence of an output schema, the description provides a reasonable picture of the returned data and its intended use. It could be more explicit about the response structure, such as whether the result is a list or object, but the listed attributes and keying instruction cover the essential context.

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 input schema contains nothing that needs explanation. The description adds a useful convention by saying answers to submit_enquiry should be keyed by field key, which is helpful context even though it is not an input parameter of this 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 names a specific resource: every field of the Event Hire Costs enquiry, and enumerates exactly what is returned: key, label, type, required flag, help text, and allowed options. This makes the tool's purpose obvious and distinguishes it from submit_enquiry by clarifying that it provides the field keys used for submission.

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 description gives clear workflow context by instructing agents to pass answers to submit_enquiry keyed by field key. It does not explicitly contrast with enquiry_describe, but it explains enough about when and why to use this tool.

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 meets it thoroughly. It discloses that step 1 only validates and returns artifacts, that step 2 actually submits the enquiry, and that the enquiry is not sent to providers until the person clicks the emailed link. It also states the exact consent wording, making behavioral expectations fully transparent.

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 long but densely informative, with each sentence serving a distinct operational purpose. It front-loads the most critical caveat ('NOT a purchase, NOT a guaranteed quote') and logically sequences the two steps without wasted words.

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 fully compensates by explaining what step 1 returns (summary, consent line, confirmation token) and what happens after step 2 (email with a link, provider visibility only after click). The agent has enough context to execute the workflow correctly and manage the user's expectations.

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?

Even though schema coverage is 100%, the description adds essential semantics beyond the schema: answers are keyed by field keys from enquiry_fields, confirmation is the token returned in step 1, and consent has an exact quoted meaning. This helps the agent correctly populate and sequence the parameters.

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 action ('Submits an enquiry to Event Hire Costs') and immediately disambiguates from a purchase or guaranteed quote. It also clearly identifies the two-step nature of the tool, so an agent understands exactly what the tool accomplishes and what it does not.

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 description provides an explicit two-step usage protocol: call first with answers and consent=true to get a summary and confirmation token, then call again with the same answers plus the token only if the person agrees. It also specifies the consent condition and the email-link requirement, giving clear when-to-invoke guidance.

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