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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. It discloses meaningful behavioral facts — the enquiry is free, nothing is bought or paid, no quote is guaranteed, and the tool returns recipient details, consent wording, and confirmation method. However, it never states its own side-effect profile (read-only, purely informational), and slightly conflates the describe-tool's output with the behavior of the tool it describes.

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?

Roughly sixty words with a front-loaded directive ('Read first'), a clear purpose statement, an exclusion list, and an output summary. Every sentence earns its place. Minor deduction: the title is a full sentence rather than a compact label, which adds slight 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 0-param informational tool with no output schema, the description adequately covers what the agent receives. But it never connects the tool to its siblings — it doesn't say what to do after reading (call submit_enquiry?) or how this relates to enquiry_fields — leaving the workflow context implied rather than explicit.

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 an empty schema, so there is no parameter documentation burden. Per baseline, a 0-param tool warrants a 4, and the description correctly spends no space on inputs.

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 — it 'states plainly what submit_enquiry does' — and names the subject resource explicitly. The title reinforces the semantic scope ('an ENQUIRY with a human, not a purchase'). It clearly sits apart from submit_enquiry (which performs the action) but never explicitly differentiates 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' implies the tool should be invoked before acting, giving the agent a sense of when in a workflow to use it. However, it never explicitly says when to use this versus enquiry_fields or submit_enquiry, and there are no exclusion statements ('do not use when...'). Guidance is implied rather than stated.

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 of behavioral transparency. It does not explicitly state whether the tool is read-only, has side effects, or requires any authorization. It only describes the content of the response, not the behavior or safety profile. This is a gap for a tool that is likely a data retrieval, but the description does not confirm that.

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 two sentences with no redundant wording. The first sentence enumerates the exact attributes returned, and the second sentence explains the relationship to submit_enquiry. It is front-loaded with the core purpose and keeps additional guidance to one essential note.

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 covers the essential information: what is returned (field attributes) and how to use it (keyed for submit_enquiry). It does not mention return format or error conditions, but for a simple listing tool that is probably acceptable. However, the presence of a sibling tool enquiry_describe is not addressed, which could leave ambiguity about when to use this tool. Overall, it is sufficiently complete for its complexity.

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 input schema is empty, so there are no parameters to describe. Per the baseline for tools with zero parameters, a score of 4 is appropriate since the description does not need to elaborate on parameters. The description does not add parameter semantics, but that is not required 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 explicitly states that this tool returns every field of the enquiry with key, label, type, required flag, help text, and options. It clearly names the resource (the enquiry fields) and the action (listing them), and also references how to use the output with submit_enquiry, distinguishing it from that sibling. This is a specific and unambiguous purpose statement.

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 context on how to use the results with submit_enquiry ('Pass answers to submit_enquiry keyed by field key'), but it does not explicitly state when to use this tool versus the sibling enquiry_describe. There is no exclusion or comparison, so an agent must infer when this tool is the right choice. The usage guidance is implicit rather than explicit.

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 behavioral disclosure. It does this well: it explains validation, the intermediate summary and token, the second submission step, the email link requirement, and the exact meaning of consent. This is far beyond what structured annotations would typically convey.

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 dense but every sentence earns its place: purpose, step 1, step 2, and the exact consent text. It is structured as a walkthrough with front-loaded purpose and clear sequential instructions, not padded with fluff.

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 lack of an output schema, the description appropriately covers return behavior for both steps: a summary, consent line, confirmation token, then an email with a click link after submission. It also covers the consent prerequisite and the two-step conditional flow. Error-handling details are absent, but the core workflow is complete enough for an agent to call 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 schema already has 100% coverage, so the baseline is 3, but the description adds significant meaning: answers must be keyed by field key from enquiry_fields, consent has a specific quoted meaning, and confirmation is the token from step 1. One minor gap is that the schema does not mark confirmation as required even though the description says it is needed in step 2.

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 the verb ('Submits an enquiry'), the resource ('Find A Co-Packer'), and explicitly what it is NOT ('NOT a purchase, NOT a guaranteed quote'). It is easy to distinguish from sibling tools because it focuses on the submission workflow rather than describing or listing 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 description provides a precise two-step procedure: first call with answers and consent to get a summary/token, then call again only after the person agrees, using the token. It also states the exact consent condition and notes that the person must click an email link before providers see the enquiry, leaving little ambiguity about when and how to invoke the tool.

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