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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 of behavioral disclosure. It states the operation (returns next question or final verdict) but doesn't disclose side effects, whether answers are recorded, what happens on invalid choice indexes, or whether this advances a persistent state in the checker flow.

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?

One sentence with no wasted words, and the core purpose is front-loaded. It's concise and readable, though it could use a second sentence for usage context.

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 annotations, no output schema, and 0% schema description coverage, the description is too thin. It doesn't explain the stateful flow (the title mentions 'next step'), what happens at the final question, how errors are surfaced, or how this tool relates to checker_start and 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?

Schema description coverage is 0%, so the description must compensate. It explains 'choice' as the chosen option's index and 'question' as the question id, which adds some meaning beyond the bare schema (integer minimum 0, string minLength 1). But it doesn't clarify what an invalid question id does, what the expected format of the question id is, or what values of choice.map are valid.

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 ('return') and resource (next question or final verdict), and identifies the two inputs (question id and chosen option). However, it doesn't distinguish itself from sibling tools like checker_start or checker_tree, and the name 'checker_answer' plus title 'Answer a question, get the next step' are only slightly expanded by the description.

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 a sequential flow (answer a question, get the next step) but provides no explicit guidance on when to use this tool instead of checker_start or checker_tree, and no mention of prerequisites or conditions.

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 explaining behavior, but it only states that the tool is the first question. It does not disclose whether invoking it starts a new session, simply returns the question text, or has any side effects, and gives no indication of how it behaves beyond being a label.

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 clear sentence with no filler or repetition. It front-loads the essential identity of the tool for a zero-parameter operation.

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 and no annotations, the description is too sparse. It never explains what the first question looks like, what output an agent should expect, or how this step connects to checker_answer and checker_tree, leaving important operational 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 the schema is empty, so there is no parameter detail for the description to add. The minimum baseline of 4 applies because the empty schema already fully documents the absence of arguments.

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 clearly identify this as the starting point of the Smoke control checker decision guide and specifically as its first question. This distinguishes it from the checker_answer and checker_tree siblings, though it lacks an explicit verb such as 'asks' or 'returns'.

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 tool is used to begin the decision guide, but there is no explicit guidance about when to use it versus checker_answer, checker_tree, or the enquiry tools. No alternative tools or exclusion conditions are mentioned.

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 disclose the content scope: every question, option, and verdict in the guide. However, it does not describe output format, size, pagination, or whether the data is a static snapshot, which leaves some behavioral uncertainty for a tool that likely returns a large complete tree.

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 filler. It front-loads the resource and scope, then states the intended reasoning use. Every word 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?

The description names the content scope and the intended use case, which is adequate for a parameterless retrieval tool. However, with no output schema and no explicit mention of how the returned tree is structured or how this tool relates to checker_start and checker_answer in the larger flow, an agent may not fully know what to expect.

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 the description has no parameter semantics to add. The empty schema is self-explanatory, and the description appropriately focuses on the tool's content rather than 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 identifies the resource ('Smoke control checker guide') and the full scope ('every question, option and verdict'), making the tool's purpose reasonably clear. The title reinforces that it exposes the whole decision tree. However, it lacks an explicit action verb like 'returns' or 'loads', so the behavior must be inferred from 'for reasoning end to end.'

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 this tool should be used when the agent needs the entire decision tree rather than stepping through it, contrasting with siblings like checker_start and checker_answer. But the description does not explicitly state when to prefer this over those alternatives, so usage guidance remains implicit.

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 fully discloses that the tool is non-transactional, free, not a guarantee, and that it returns concrete details such as who receives the enquiry, 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 compact, front-loaded with the most important instruction ('Read first'), and every sentence adds meaningful information. The title also reinforces the core distinction from transaction-oriented sibling tools without 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?

Given the tool has no parameters, no output schema, and no annotations, the description is complete: it states what the tool does, what it does not do, and what information it returns. No critical context 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?

The tool has zero parameters, so there is nothing for the description to explain. The baseline for zero-parameter tools is 4, and the description appropriately focuses on the tool's output rather than 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 clearly states a specific purpose: it explains what submit_enquiry does on Smoke Control Checker, including that it starts an enquiry with human providers. It also distinguishes itself from submit_enquiry by explicitly saying nothing is bought, ordered, or paid and that no quote is guaranteed.

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' is a clear usage signal: use this tool before acting with submit_enquiry. The description also clarifies what the tool is not (a purchase or guaranteed quote), which helps an agent avoid invoking the wrong sibling.

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 clearly states what the tool returns—key, label, type, required, help text, and allowed options—and says 'every field,' indicating exhaustiveness. It omits explicit statements about side effects or return format, but for a zero-parameter read-only field listing, these are minor 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 two concise sentences: the first enumerates what the tool exposes, and the second gives cross-tool guidance. There is no redundancy or filler; every word contributes to understanding.

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 zero-parameter tool, the description covers the content of the response and the purpose of the returned keys, making it essentially complete. It does not specify the exact return shape (array vs object), but given the absence of parameters, output schema, and nested structures, that omission is acceptable.

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 document; the baseline for zero parameters is 4. The description adds meaningful context by explaining how the returned field keys relate to calling submit_enquiry, which aids correct usage of both 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 identifies the resource ('every field of the Smoke Control Checker enquiry') and enumerates the details it exposes (key, label, type, required, help text, options), making its purpose evident. It lacks an explicit verb like 'retrieve' or 'list' but is unmistakable. It also distinguishes itself from submit_enquiry by explaining that answers go there keyed by these field keys.

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 offers a practical usage clue ('Pass answers to submit_enquiry keyed by field key'), implying this tool supplies the keys needed for submission. However, it never explicitly states when to choose this tool over the siblings enquiry_describe or checker_tree, nor does it mention exclusions or prerequisites. The guidance is useful but indirect.

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 behavioral burden and does so impressively: it discloses the two-step side effect, the consent requirement with exact wording, that the person receives an email, and that no provider sees the enquiry until the link is clicked. It also warns the action is not a purchase or guaranteed quote.

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 long but every sentence earns its place: front-loaded purpose, explicit Step 1/Step 2 structure, and the consent string are all essential for correct invocation. No filler or redundant restatement of the schema.

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-output-schema tool, it explains the step 1 return (summary, consent line, confirmation token) and the final outcome (email with click link). It doesn't describe validation failure behavior or the exact step 2 return payload, but the agent has enough to invoke the tool correctly and manage the user interaction.

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 real value by defining 'answers' as keyed by enquiry_fields, pinning the exact consent text, and explaining the 'confirmation' token's provenance from step 1. It stops short of describing individual answer fields, but those are delegated to enquiry_fields.

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?

States a specific action ('Submits an enquiry to Smoke Control Checker') and immediately distinguishes itself from purchases/quotes via the title and description. The two-step confirmation flow is explicit, making the tool's role unambiguous relative to sibling checker/enquiry info tools.

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?

Provides clear procedural guidance: call once with answers+consent to validate, then call again with the confirmation token only after the person agrees. It doesn't explicitly name sibling alternatives or state 'do not use when...', but the 'NOT a purchase/quote' caveat and stepwise conditions give strong usage context.

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