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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 it does so thoroughly. It states what the tool returns, key behavioral traits of the underlying enquiry process, and critical caveats: nothing is bought, ordered, or paid, no quote is guaranteed, and the enquiry is free.

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, front-loaded with 'Read first,' and every sentence adds information. It covers purpose, behavioral caveats, and return value without filler or 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 zero-parameter documentation tool with no output schema, the description is complete. It explains what the tool does, what it returns, and the important restrictions around the enquiry process, leaving no critical ambiguity for an agent deciding whether 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 has zero parameters, and schema description coverage is 100%, so there are no parameter semantics for the description to clarify. The baseline of 4 applies because nothing is missing regarding 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 title and description make the purpose unmistakable: this tool describes what submit_enquiry does rather than performing the action. It uses a specific verb ('States plainly') and resource ('submit_enquiry on Grain Storage Costs'), and clearly distinguishes itself from the actual submit operation with anti-confusion language like 'not a purchase, not a guaranteed quote.'

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 opens with 'Read first,' which is an explicit signal that this tool should be consulted before acting on submit_enquiry. It establishes the context for use, though it does not explicitly contrast this tool with enquiry_fields or list exclusions such as 'do not use this to submit an enquiry.'

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?

There are no annotations, so the description carries the full burden. It discloses that this is a metadata/field-listing operation, describes the shape of the returned data, and clarifies that actual submission happens through submit_enquiry. The absence of mutation language makes this a clearly passive lookup, though it doesn't explicitly state read-only or permission requirements.

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 with no filler. The first sentence front-loads the resource and the full list of returned attributes; the second adds the actionable connection to submit_enquiry. Every sentence earns its place.

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 metadata lookup with no output schema, the description is complete: it names the specific enquiry, lists all returned dimensions, and explains how to use the results. Nothing essential is missing for selecting and invoking 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 parameter detail to document. The empty input schema is fully covered, and the description adds practical guidance by telling the agent to pass answers to submit_enquiry keyed by field key.

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 identifies the exact resource ('Every field of the Grain Storage Costs enquiry') and enumerates the output attributes: key, label, type, required flag, help text, and allowed options. This makes it easy to distinguish from siblings: submit_enquiry sends answers, while this tool exposes the field definitions to use with those answers.

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 context for when this tool is useful: to learn the field keys before calling submit_enquiry. It doesn't explicitly say 'do not use this to submit answers,' but the instruction to pass answers to submit_enquiry keyed by these fields implies the division of responsibility well.

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 of behavioral disclosure. It reveals that the first call does not submit, that a confirmation token is required for the second call, that an email link must be clicked before providers see the enquiry, and the exact consent wording. This is unusually transparent about side effects and sequencing.

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 longer than average, but every sentence earns its place. It is front-loaded with the critical 'NOT a purchase, NOT a guaranteed quote' caveat, then organized into clear numbered steps, with the consent quote included verbatim to avoid ambiguity. No extraneous 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 tool with no output schema, the description explains exactly what step 1 returns (summary, consent line, confirmation token) and what happens after step 2 (email with a clickable link). It also references enquiry_fields for valid answer keys, giving the agent everything needed to call the tool correctly in both steps.

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 description coverage is 100%, so the baseline is 3. The description adds meaningful process context beyond the schema: answers are keyed by field keys from enquiry_fields, consent must match the exact quoted text, and confirmation is only needed for the second call. This elevates the semantics beyond simple parameter definitions.

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 Grain Storage Costs' — and immediately clarifies what it is not: 'NOT a purchase, NOT a guaranteed quote.' This distinguishes it from the sibling tools (enquiry_describe and enquiry_fields), which handle description and field enumeration, not 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 two-step workflow is explicitly defined: step 1 validates and returns a summary and confirmation token; step 2 submits only if the person agrees. It also gives clear exclusions ('not a purchase') and directs the agent to use field keys from enquiry_fields, making the appropriate usage unmistakable.

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