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

With no annotations, the description carries the full burden. It does disclose the key behavior—returning either the next question or a final verdict—but it does not mention whether the flow state is mutated, what happens for invalid choices, or any session/state 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?

A single, information-dense sentence. The title and description work together without repetition or filler, and the key input/output behavior is front-loaded.

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?

Adequate for a two-parameter tool: it names both inputs and describes the possible return. However, with no output schema and no annotations, it falls short of fully describing the response shape, error behavior, or what the caller should do with the returned next question/final verdict.

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 has 0% description coverage, so the description's clarification that `question` is a question id and `choice` is the chosen option's index is essential. It adds meaning beyond the raw property names and types, though it omits details like how to obtain valid question ids or bounds beyond minimum 0.

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 operation: given a question id and a choice index, return the next question or final verdict. This clearly differentiates it from sibling tools like checker_start or checker_tree, which have different roles in the flow.

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?

Usage is implied: use this when a user has answered a question and the flow should advance. However, it does not explicitly state when not to use it, what prerequisites exist (e.g., starting with checker_start), or how it relates to alternatives.

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 disclosing behavior. It only states that this is the first question of the guide; it does not say what calling the tool returns, whether it initializes state, or what the agent should expect in the response. This is thin behavioral disclosure for an unannotated 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 description is a single short sentence with no wasted words. It is front-loaded with the key information that this is the entry point to the decision guide.

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-parameter, no-output-schema tool, the description gives baseline context about where the tool sits in the workflow. However, it does not describe the expected response or the transition to checker_answer, so the agent is left to infer the next step and the return shape.

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 there is nothing for the description to add about parameter semantics. The schema is effectively complete, and the 0-parameter baseline of 4 applies.

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 tool as the entry point of the Licence entitlement checker decision guide, which is specific enough to distinguish it from siblings such as checker_answer and checker_tree. It lacks an explicit action verb like 'starts' or 'returns', but the title and 'first question' wording make the purpose reasonably clear.

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 'first question' implies this should be called at the beginning of the decision guide, and sibling names hint that checker_answer handles subsequent steps. However, the description gives no explicit guidance about when to use this tool versus alternatives or when not to use it.

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. It does describe what the tool exposes (full decision tree content) and its intended use (end-to-end reasoning), which gives some sense of expected behavior. It does not mention output format, size, or side effects, but for a zero-parameter content retrieval tool this is a reasonable, if minimal, disclosure.

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 tight sentence that clearly states the full scope of the tool. Every word earns its place, and the key idea—whole decision tree—is front-loaded. No redundant or filler content.

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 parameterless tool with no output schema, the description gives enough information for an agent to understand what it will receive and why it might be useful. It could more explicitly say 'returns all questions, options, and verdicts,' but the current wording is sufficient for correct invocation in the context of the sibling checker tools.

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 parameter documentation is unnecessary. The baseline of 4 applies because there is no parameter burden for the description to carry. The description appropriately focuses on what the tool returns rather than 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 clearly identifies the resource: every question, option, and verdict of the Licence entitlement checker guide. It also signals scope ('whole decision tree') and purpose ('reasoning end to end'), which distinguishes it from the interactive checker siblings. However, it lacks an explicit verb like 'retrieve' or 'get', so it stops just short of a 5.

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' implies the tool is for viewing the complete tree rather than stepping through it interactively. But it does not explicitly state when to choose this tool over checker_start or checker_answer, nor does it mention any exclusions. Usage context is present only by implication.

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 clearly states that the tool describes a submission process rather than performing it, that nothing is bought, ordered, or paid, that no quote is guaranteed, and that it is free. It also discloses what the description returns: recipient details, consent wording, and confirmation method. This is thorough for an informational 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 description is two sentences with no filler. 'Read first' is a succinct, front-loaded directive. Every clause adds value: it explains the tool's purpose, what submit_enquiry does, what it does not do, and what information the description provides.

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 is complete. It explains the tool's role, the nature of the submission process, limitations, costs, and the content of the returned description. An agent has everything needed to decide whether and when 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, so parameter documentation is not needed. The schema coverage is vacuously 100%, and the description adds no parameter-related content, which is appropriate. Baseline for zero-parameter tools is 4.

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 the tool's function: it 'States plainly what submit_enquiry does' on What Can I Drive. The title and description clarify that it is an informational description, not the actual submission action, thus clearly distinguishing it from submit_enquiry. The purpose is specific and 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 opening 'Read first' explicitly instructs the agent to use this tool before submitting an enquiry, establishing clear usage context. It also contrasts the enquiry with a purchase or guaranteed quote, helping the agent understand when this tool's information is relevant. It does not explicitly name alternative tools, but the positioning is 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 the full behavioral disclosure burden. It does well by specifying the exact kinds of information returned (key, label, type, required, help text, allowed options) and implies this is a read-only introspection tool by directing submission to submit_enquiry. It could be more explicit about the return shape or side-effect-free nature, but the behavior is largely 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 two tight sentences with no wasted words. It front-loads the core content about what fields include, then adds a single practical usage 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?

Given zero parameters and no output schema, the description is complete: it tells the agent exactly what information the tool provides and how to use that information with submit_enquiry. 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 input schema has zero parameters, so the baseline is 4. The description adds no parameter-specific semantics because none are needed, and its guidance about keying answers for submit_enquiry refers to a sibling tool rather than this one.

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 ('Every field of the What Can I Drive enquiry') and enumerates what is included, so an agent understands the tool returns field metadata rather than performing an action. However, it lacks an explicit verb like 'lists' or 'returns', and it does not distinguish itself from the sibling enquiry_describe.

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 practical context by instructing the agent to pass answers to submit_enquiry keyed by field key, which clarifies when this tool's output is needed. It does not explicitly state when not to use this tool or mention alternatives such as enquiry_describe, but the intended usage is 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 the full burden and does so: it discloses that this is not a purchase or guaranteed quote, that submission is two-phase with a validation pass first, that the enquiry is not visible to providers until the person clicks an emailed link, and that details go to up to three providers with opt-out rights. It also defines consent verbatim, which is the actual authorization condition.

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 purpose and the two negations, then organized as Step 1 / Step 2 / consent definition, so the critical routing information comes first. It is long, and the full consent text is repeated verbatim from the schema's consent description, which is mild redundancy — though defensible given the agent must echo it to the user.

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 output schema exists, so the description compensates by describing what step 1 returns (summary, consent line, confirmation token) and what step 2 produces (submission plus an email with a click-through link). Nothing an agent needs to complete the two-phase flow correctly 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?

Schema coverage is 100%, so the baseline is 3; the description goes beyond it by explaining the sequencing role of 'confirmation' (present only in step 2, after approval) and by tying 'answers' to the field keys returned by enquiry_fields. It adds workflow meaning rather than duplicating the schema's type information.

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?

Names a specific verb and resource (submits an enquiry to What Can I Drive) and immediately bounds it with two negations — 'NOT a purchase, NOT a guaranteed quote' — which separates it from the checkout/quote tools an agent might otherwise reach for. Siblings (enquiry_fields, enquiry_describe) are preparatory, and the two-step framing here makes the distinction clear.

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 explicit when-to-call instructions per phase: step 1 with answers keyed by field key plus consent=true, step 2 only after the person agrees and with the confirmation token. The gating condition ('only if the person agrees') and the human-facing action (show the summary and consent line) are spelled out rather than inferred.

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