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

With no annotations, the description must carry the behavioral disclosure burden. It clearly indicates a read-like operation ('return the next question or the final verdict') and reveals the two possible outcomes, but it does not disclose side effects, prerequisites, or error handling for invalid choices. The description adds some behavioral context beyond the title but omits important details.

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, well-structured sentence with the condition front-loaded and the result clearly stated. Every word earns its place, and there is 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?

The tool is simple (2 params, no output schema, no annotations), and the description explains the core behavior, but it leaves gaps: the agent is not told the structure of the returned question/verdict, whether the 'question' parameter expects an ID string, or how to handle an invalid choice. It is minimally viable but not fully complete for an agent invoking it in an unfamiliar workflow.

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 for both parameters. It maps 'question' to a question id and 'choice' to a choice index, which provides partial meaning, but it does not clarify whether choice is zero-based or one-based, nor does it explain the relationship between the id and the question-answer flow. For a schema with zero coverage, this is minimal compensation.

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: given a question id and a chosen option, return the next question or the final verdict. This clearly conveys the tool's role in a question-answering flow and is distinguishable from siblings like checker_start (likely starts a flow) and checker_tree (likely shows structure).

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 in a sequential question-answering context but provides no explicit guidance on when to prefer this over alternatives. It does not mention checker_start, checker_tree, or enquiry_describe, leaving the agent to infer the appropriate context from the tool name alone.

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 must carry the full burden of behavioral disclosure. It only says the tool is 'the first question' of a guide, without explaining what happens when it is called, what it returns, whether it asks a question, or how it relates to subsequent steps. This is a minimal hint rather than transparent behavior.

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 sentence with no wasted words and the key 'first question' idea is front-loaded. It is concise, but it is also so minimal that it borders on under-specification, so it does not earn a higher score.

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 and no annotations, the description should clarify what invoking 'start' actually does and how it fits into the decision guide flow. It only states that it is the first question, leaving the agent without enough context to know what result to expect or how to proceed to checker_answer or checker_tree.

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 and the tool has zero parameters, so there is nothing for the description to document. The baseline for 0-parameter tools is 4, and no parameter information is needed.

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 first question in the 'Which lever applies?' decision guide, which gives some sense of its role as a starting point. However, it is a noun phrase rather than a clear verb+resource statement, and it largely restates the title, so the tool's actual action remains vague.

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?

No explicit guidance is given about when to use this tool versus siblings like checker_answer or checker_tree. The phrase 'first question' implies it comes at the beginning, but there is no clear statement about prerequisites, exclusions, 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, the description carries the burden of disclosure. It states the tool's output scope ('every question, option and verdict') and intended purpose, making the read-only retrieval behavior clear. It does not describe the exact output format, but for a zero-parameter static resource this is a minor 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?

A single, dense sentence that front-loads the core content ('every question, option and verdict') and states the intended reasoning use. No 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?

For a zero-parameter tool with no output schema, the description adequately conveys what the tool returns and why it would be used. It could be more explicit about how the tree is structured or that it returns the complete guide in one response, but overall it is sufficient for an agent to decide 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 input schema has zero parameters, so the baseline is 4. The description adds no parameter-specific details, but none are needed since the tool accepts no input.

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 the tool provides every question, option, and verdict from the 'Which lever applies?' guide, which identifies the resource and content. It is understandable and distinct from siblings like checker_answer or checker_start, though it does not explicitly name them.

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 a use case: when an agent needs the full decision tree rather than a single step or verdict. However, the description offers no explicit guidance on when to choose this tool over sibling tools like checker_answer or checker_start.

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 behavioral disclosure burden. It does this well by explicitly stating that nothing is bought, ordered, or paid, that no quote is guaranteed, and that the tool is free. It also discloses what the tool returns: who receives details, consent wording, and how the person confirms.

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 and front-loaded with 'Read first,' then delivers the essential behavioral facts in two more sentences. Minor redundancy with the title and the unexplained 'STR Rules Check' abbreviation keep it from being a perfect 5.

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 descriptive tool, the description covers what the tool does, what effects it does not have, and what information it returns. It is complete enough for its likely role as an explainer before submit_enquiry, though 'STR Rules Check' remains undefined and no output format is described.

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 are no parameter semantics for the description to explain. The description appropriately focuses on behavior and return value rather than inputs, which aligns with the baseline for no-parameter tools.

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 the tool 'States plainly what submit_enquiry does on STR Rules Check' and lists the key behaviors and returns. It references a specific sibling tool, submit_enquiry, which helps distinguish it from the checker and enquiry sibling tools. The phrase 'STR Rules Check' is unexplained, which slightly reduces clarity.

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' strongly implies that this tool should be consulted before using submit_enquiry. However, it never explicitly states when to use this tool versus alternatives like enquiry_fields or submit_enquiry itself, and it provides no exclusion criteria.

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. It usefully implies this is a read-only metadata retrieval operation and distinguishes it from submit_enquiry by directing answers there. It does not disclose authentication requirements, error behavior, or response format, but for a zero-parameter metadata tool the implied behavior is reasonably clear.

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 tight sentences with no filler. The first sentence enumerates the tool's output content, and the second connects it to the sibling tool that consumes those keys. 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?

With no output schema and no annotations, the description adequately covers what the agent receives by naming the field attributes and the key relationship to submit_enquiry. It is complete enough for a simple, zero-parameter retrieval tool, though it does not describe response formatting or edge cases.

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 no parameters, so the baseline of 4 applies. The description adds relevant conceptual meaning by explaining that the returned field keys should be used as answer keys in submit_enquiry, which is more useful than the empty schema alone.

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 — the fields of the STR Rules Check enquiry — and enumerates exactly what is included: key, label, type, required flag, help text, and allowed options. It lacks an explicit verb such as 'lists' or 'returns', but the meaning is unambiguous and it is distinct from the submit_enquiry sibling.

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 workflow context by saying 'Pass answers to submit_enquiry keyed by field key,' which implies this tool is used to discover the available fields before submitting. However, it does not explicitly say when to prefer this tool over related siblings like enquiry_describe or checker_tree, nor does it state 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?

With no annotations, the description carries the full behavioral burden and does so thoroughly: it discloses the two-step nature, that step 1 does not submit and only validates, that step 2 requires the token, that an email link must be clicked before providers see the enquiry, and the exact consent wording. This gives the agent a strong mental model of 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 front-loaded with the most important caveat ('NOT a purchase, NOT a guaranteed quote') and then organized into clear Step 1 and Step 2 instructions. Every sentence carries necessary operational or consent information, with no 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, consent-gated submission with no output schema and no annotations, the description is remarkably complete. It explains what each call returns, when to make the second call, what the consent string is, and the post-submission email-link behavior, so an agent has the full calling contract.

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 adds extra value by explaining that answers must be keyed by field key from enquiry_fields, that consent must match the quoted text, and that confirmation is the token returned from the first step. This sequencing context goes beyond the schema's isolated parameter descriptions.

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 this tool submits an enquiry to STR Rules Check and explicitly disambiguates it as 'NOT a purchase, NOT a guaranteed quote.' It also frames the action as a two-step human-provider submission, making its purpose distinct from the sibling lookup tools like enquiry_fields and checker_answer.

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 spelled out explicitly: first call with answers and consent=true, then a second call with the confirmation token only if the person agrees. It does not explicitly name alternative tools or say when not to use this tool, but the step conditions and consent requirement provide clear usage context.

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