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

Annotations are not provided, so the description must carry the burden of behavioral disclosure. It does disclose the core behavior: consuming a choice and returning the next step or final verdict. However, it does not mention side effects, whether this advances a session state, potential errors for invalid question IDs or out-of-range choices, or whether the operation is idempotent. This is acceptable for a simple query tool but leaves room for more transparency.

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, compact sentence that front-loads the core behavior and expected outcome. It is concise with no filler, while still conveying the essential purpose and flow.

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's simplicity (2 parameters, no output schema), the description covers the main function but omits some context an agent might need: what the 'final verdict' looks like, whether there is any statefulness (does it alter the question sequence?), and how it relates to checker_start/checker_tree. These gaps are not critical for a straightforward tool but are noticeable for a complete understanding.

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 does explain that `choice` is the index of the chosen option and that `question` is the question id, which adds meaning beyond the raw schema. However, it does not specify how the question id is obtained (e.g., from checker_start), the format of the question id, or the range of valid choice indices beyond the schema's minimum of 0. This partially compensates for missing schema descriptions but not fully.

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 action: given a question id and a choice index, return the next question or final verdict. It identifies the tool's key resource (question/answer progression) and distinguishes it from likely alternatives like checker_start. However, it does not explicitly name sibling tools or contrast with them, so it gets a 4 rather than 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 description implies the usage context: it is used after starting a question sequence and submitting an answer. It does not explicitly state when to use this tool versus alternatives such as checker_start or checker_tree, nor does it mention prerequisites. The guidance is sufficient for a straightforward state-advance tool but lacks explicit routing.

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 full responsibility for disclosing behavior. It only states what the tool is ('the first question') rather than what happens when invoked, such as whether it returns a question, starts a session, 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, compact sentence that conveys the tool's position in the decision guide without redundant phrasing or filler. It is appropriately sized for a tool with no parameters and simple semantics.

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, no-output-schema tool, the description is minimally adequate, but it leaves ambiguity about what the agent will receive after calling and how this connects to checker_answer or checker_tree. A brief mention of the return value or next step would make it 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?

The tool has zero parameters and 100% schema description coverage, so there is nothing for the description to clarify. Per the baseline for zero-parameter tools, this dimension is well satisfied.

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 as 'Food temperature record checker decision guide' and positions this tool as its 'first question,' which is more informative than a tautology. However, it lacks an explicit action verb such as 'returns' or 'starts,' so the agent must infer what calling it actually does.

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 word 'first' implies this tool is the entry point to the decision guide, giving the agent a weak usage signal. It does not explicitly compare against sibling tools like checker_answer or checker_tree, nor state 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 of behavioral disclosure. It does disclose content coverage and that the tool represents the whole guide tree, but it does not describe return format, traversal mechanics, or any side effects. There is no contradiction, but the behavioral detail is thinner than it could be.

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, compact sentence with no filler. The key information—complete coverage of questions, options, and verdicts—is front-loaded, and every phrase contributes meaning beyond the title.

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 no annotations, the description gives a reasonable sense of what is included but not exactly what the agent will receive or how this tree relates to the sibling checker tools. It is minimally viable but leaves room for more explicit guidance.

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 no parameters, so there is no parameter information for the description to add. The description therefore cannot be penalized for missing parameter guidance, and the zero-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 clearly identifies the resource as the complete decision tree for the Food temperature record checker and enumerates its contents ('every question, option and verdict'). It distinguishes itself from stepwise siblings like checker_answer and checker_start by emphasizing end-to-end coverage, though it lacks an explicit verb like '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 'for reasoning end to end' implies the tool should be used when the agent needs the full decision tree rather than a single step. However, it does not explicitly state when not to use it or name alternatives such as checker_start or checker_answer, leaving routing mostly to inference from sibling names.

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; it states the tool 'returns who receives the details, the consent wording, and how the person confirms' and clarifies what it does not do ('Nothing is bought, ordered or paid; no quote is guaranteed'). It reveals the output content and the non-transactional nature of the enquiry. It does not explicitly declare the tool itself side-effect-free, but the 'states/returns' framing makes its read-only nature reasonably evident.

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 imperative 'Read first,' and each clause adds a distinct point: target tool, non-purchase behavior, and return content. There is minor redundancy with the title, but no wasted 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 zero parameters, no annotations, and no output schema, the description provides enough orientation: what the tool is for, its target, and its returns. It mentions the consent wording and confirmation flow, which are actionable for deciding whether to call submit_enquiry. It could name alternative/successor tools, but that is not essential for calling this simple describe tool.

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 schema itself is already complete; the baseline for a no-parameter tool is 4. The description reinforces the informational nature but has no parameter details to add.

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 uses a concrete verb ('states plainly') and names the subject ('what submit_enquiry does on Temperature Log'), so an agent understands this is an informational tool about a specific sibling. The title also clarifies the outcome is 'not a purchase, not a guaranteed quote,' distinguishing it from action-oriented tools like submit_enquiry. This clearly separates it from the sibling 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?

The opening 'Read first' explicitly tells an agent to consult this tool before acting, and the body explains it is the plain-language guide to submit_enquiry's behavior. It does not explicitly discuss alternatives or exclusions, so it stops one step short of full routing guidance.

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 explaining behavior. It does disclose the exact kind of data returned and the expected downstream usage, which is helpful. However, it never explicitly states that this is a read-only retrieval operation, nor does it mention potential errors or limitations, leaving some behavioral ambiguity.

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 that front-loads the core purpose, then lists the contained data attributes, and ends with a practical usage pointer. Every clause earns its place with no redundancy or 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 no-input, no-output-schema metadata tool, the description is complete. It explains what data the tool returns, enumerates the fields, and clearly connects it to submit_enquiry, which is the main action an agent would need to take with that data.

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 full schema description coverage, so there are no parameter semantics for the description to add. The baseline for zero parameters is 4, and the description appropriately focuses on the output and how it should be used rather than inventing parameter guidance.

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 exposes every field of the Temperature Log enquiry, including key, label, type, required status, help text, and allowed options. The purpose is specific and the resource is named, though it does not explicitly differentiate itself from the sibling enquiry_describe tool.

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 actionable usage context: 'Pass answers to submit_enquiry keyed by field key.' This tells the agent why the tool matters and how the returned field keys should be used. It does not explicitly contrast this tool with alternatives, but the usage direction 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 provided, the description carries the full disclosure burden and meets it impressively. It reveals the stateful two-step behavior, that step 1 validates and returns a summary/consent line/token, that an email with a click-link is required before any provider sees the enquiry, and the exact meaning of consent. These are precisely the behavioral traits an agent cannot infer from the schema.

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 earns its length: every sentence carries protocol, consent semantics, or side-effect information that the schema cannot express. The differentiator ('NOT a purchase, NOT a guaranteed quote') is front-loaded, and the verbatim consent quote prevents paraphrase drift in a legally sensitive string. There is no fluff or repetition beyond what operationalizes the consent requirement.

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 high-complexity tool with no annotations and no output schema, the description covers the full critical path: both call steps, the step-1 return values, the email/click-through side effect, and consent preconditions. Minor gaps remain — the step-2 success response is not described and validation-failure/error behavior is not covered — but nothing an agent needs to invoke the tool correctly on the happy path 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%, setting a baseline of 3, but the description adds meaningful sequencing semantics beyond the schema: answers must come from enquiry_fields and must be identical across both calls, consent=true is required in BOTH steps, and confirmation is only used in step 2. Notably, it resolves the schema's ambiguity where confirmation is not marked required — the description clarifies it becomes required for the second call.

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 opens with a specific verb and resource — 'Submits an enquiry to Temperature Log' — and immediately disambiguates with 'NOT a purchase, NOT a guaranteed quote.' It clearly conveys the two-step nature of the operation, which is its defining trait, and is readily distinguishable from the sibling checker_* and enquiry_describe/enquiry_fields tools that describe or validate rather than submit.

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 an explicit, sequenced protocol: step 1 call with answers and consent=true, show the summary and consent line, then step 2 call again with the same answers plus the confirmation token only if the person agrees. It also references the sibling tool enquiry_fields as the source of answer keys and states what the tool is NOT for (purchases, guaranteed quotes). This is unambiguous when-to-use and when-not-to-use guidance.

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