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

No annotations are provided, so the description carries the full burden. It discloses the stateful behavior (progressing to next step or verdict) but does not mention side effects (e.g., whether answers are recorded, if the flow is mutable, or if calling this repeatedly changes state). The lack of clarity on whether 'choice' is a 0-based index into options and the absence of error handling details are gaps.

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 one succinct sentence, front-loading the core behavior. It earns its place without fluff, though it could add a second sentence to clarify parameter semantics without becoming verbose.

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 2-parameter tool with no output schema or annotations, the description provides the essential flow but lacks details on return format (e.g., structure of the next question or verdict), possible failure modes (e.g., invalid question ID), and prerequisites (e.g., must have called checker_start first). It is adequate for a simple tool but not fully complete.

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 0%, so the description must compensate, but it only names 'question id' and 'chosen option' without clarifying the exact format of 'question' (e.g., is it an ID string?) or that 'choice' is an index into an options list. It adds minimal meaning beyond the schema's basic types and required fields, missing the chance to explain the relationship between 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 clear action ('return the next question or the final verdict') and identifies the key resource (question id and chosen option). It distinguishes itself from a general lookup by specifying the step-by-step flow, though it does not explicitly contrast with sibling tools like checker_start or checker_tree.

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 implies the tool is used to advance a quiz or decision flow by answering a question, and the mention of 'next question or final verdict' gives context. However, it does not explicitly state when to use this tool versus alternatives (e.g., starting a check with checker_start or viewing the tree with checker_tree), leaving some inference needed.

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 disclosure. It only states that this is the first question, with no information about whether starting creates state, returns a question, or has side effects.

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 a single, front-loaded sentence with no filler. Every word contributes to identifying what the tool represents.

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 tool with no output schema and a simple purpose, the description is largely complete: it identifies the resource and the tool's role as the entry point. It could add a bit more behavioral context, but the low complexity limits the need.

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 has zero parameters, so the description has no parameter details to add. The baseline of 4 applies because there is nothing to document.

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 a specific resource—the Drone licence checker decision guide—and its position as the first question, which distinguishes it from siblings like checker_answer and checker_tree. However, it lacks a direct action verb such as "displays" or "starts," so it does not fully meet the 5-level bar.

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 implies usage at the beginning of the decision guide by calling this the first question. It does not explicitly state when to use it versus the sibling tools or mention any exclusions.

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 disclosure. It explains what content is included (questions, options, verdicts), but says nothing about return format, whether the tool is read-only/static, output size, or how the data is structured. This leaves operational behavior largely inferred.

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?

A single, dense sentence with no filler. It front-loads the resource and content, and every phrase ('every question, option and verdict', 'for reasoning end to end') earns its place by clarifying what the tool provides and why.

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-argument tool, this is close to adequate: the agent knows the tool returns the complete decision tree and that it is meant for end-to-end reasoning. However, with no annotations and no output schema, the lack of any mention of return structure or relationship to step-wise siblings leaves some context 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 and an empty input schema, so there is no parameter documentation gap. Per the baseline for zero-parameter tools, a score of 4 is appropriate; the description does not need to add parameter-level detail.

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 the exact resource (the Drone licence checker guide's decision tree) and specifies its content: 'every question, option and verdict'. 'Whole' and 'end to end' clearly distinguish it from the step-wise sibling tools checker_start and checker_answer, making selection unambiguous.

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 phrase 'for reasoning end to end' gives a clear use case, but it does not explicitly state when to prefer this tool over checker_start/checker_answer or mention exclusions. The guidance is implied rather than directly 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?

With no annotations, the description fully carries the burden of disclosure, and it does so well: it states that nothing is bought or paid for, no quote is guaranteed, the service is free, and it details what information is returned including recipient, consent wording, and confirmation method.

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 short, front-loaded with the 'Read first' directive, and every sentence adds meaningful information. It avoids filler while covering purpose, exclusions, cost, and return content in just three sentences.

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 no output schema, the description adequately explains what the tool returns: who receives the details, consent wording, and how confirmation happens. It fully covers expectations for this simple zero-parameter tool, leaving no significant gap for an agent to call it 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 and the schema description coverage is 100%, so there are no parameter semantics for the description to clarify. The description adds useful context about the returned content, which is appropriate for a parameterless informational 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 clearly states that this tool describes what submit_enquiry does, explicitly differentiating it from a purchase, order, payment, or guaranteed quote. It names the related submit_enquiry tool and positions itself as the read-first informational counterpart, making its purpose unmistakable.

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' provides an explicit usage signal that this tool should be consulted before engaging with the enquiry process. It sets expectations about what the enquiry is and is not, though it does not discuss alternatives like the checker_* tools or specify when to skip 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 behavioral disclosure burden. It does disclose what data the tool exposes and implies a read-only metadata lookup, but it never explicitly states that there are no side effects or how the field list is returned. For a low-risk metadata tool this is acceptable, but the absence of an explicit behavioral statement keeps it at a 3.

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 filler: the first enumerates the returned field metadata, and the second links those field keys to submit_enquiry. The most important content is front-loaded and 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 tool, the description sufficiently explains what is returned and how the output relates to submit_enquiry. It does not explicitly differentiate from enquiry_describe, which could cause ambiguity among sibling tools, but the core usage is complete enough for an agent to invoke 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 and an empty schema, so there is nothing for the description to clarify about parameter syntax or meaning. The mention of keying answers to submit_enquiry by field key adds useful domain context even though it is not a parameter. A zero-parameter tool gets a baseline 4, and the description meets that bar.

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 as the field structure of the Drone Licence Checker enquiry and enumerates the exact metadata exposed (key, label, type, required, help text, options). It also connects the tool to submit_enquiry, giving the agent a concrete purpose. It loses one point because it lacks an explicit verb such as 'lists' or 'returns', and the title is noun-like.

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 one useful routing hint: 'Pass answers to submit_enquiry keyed by field key,' which tells the agent how to use the returned field keys. However, it does not explicitly state when to use enquiry_fields over sibling tools like enquiry_describe or checker_tree, and there are no exclusions. Usage guidance is implied 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 fully carries the behavioral burden. It discloses the two-step side-effect boundary, returns a summary/consent line/token, requires the token for submission, sends an email with a click link before providers see the enquiry, and quotes the exact consent wording.

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: it front-loads the critical 'not a purchase' disclaimer, numbers the steps, and integrates user consent and provider visibility constraints without 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 complex two-step tool with no output schema and no annotations, this description is remarkably complete. It covers inputs, validation, outputs, the consent gate, the confirmation token handoff, email follow-up, and the condition under which the provider sees the enquiry.

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 real workflow semantics: answers are keyed by enquiry_fields keys, consent embeds the exact consent text, and confirmation is the token from step 1 passed only in step 2. It explains how all three parameters are used across the two calls.

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 verb and resource: 'Submits an enquiry to Drone Licence Checker', and explicitly disambiguates it from a purchase or guaranteed quote. The two-step framing also makes the tool's workflow and purpose immediately distinct.

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?

It gives an explicit two-step protocol: step 1 validates and returns a token, step 2 submits only after user approval. It also states the prerequisite that answers must be keyed by field keys from enquiry_fields and that consent must be true only after the person has agreed, providing clear when-to-call and when-not-to-call guidance.

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