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

No annotations are present, so the description must carry the burden. It describes the core return behavior but does not disclose whether the answer is recorded, whether any state changes, or how invalid inputs are handled.

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, front-loaded sentence with no fluff; the title reinforces the purpose.

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 and the description covers the essential input/output, but without an output schema it leaves the exact return shape of a 'next question' or 'final verdict' unspecified, and no error or terminal-state details are given.

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?

With 0% schema description coverage, the description adds crucial semantics: question is an id and choice is the zero-based index (minimum 0) among options. This goes beyond the bare schema, though it doesn't define the id format.

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 (answer), the input (question id and choice index), and the output (next question or final verdict). This clearly differentiates from siblings like checker_start/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 establishes the condition for use — when you have a question id and a chosen option — but does not explicitly contrast with alternatives or 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 only states it is the first question, implying it returns or presents a question, but does not describe whether it creates any session state, has side effects, or requires authentication. It is too minimal to inform an agent about expected behavior beyond the bare fact it starts a guide.

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, succinct sentence that communicates the essential purpose without any fluff. It is front-loaded with the key information ('first question') and stays within a reasonable length. 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?

Given the tool has no parameters and no output schema, the description is the sole source of context. It tells the agent this is the first question of a decision guide, but does not specify what the tool actually returns (e.g., a question object, a prompt, a status) or how the agent should handle the response. For a starting tool, this is minimally acceptable but leaves room for ambiguity about the interaction pattern.

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?

There are zero parameters, so the schema is fully covered vacuously. The description does not mention parameters because none exist, which is appropriate. According to the baseline rule for 0 parameters, a score of 4 is warranted; there is no missing parameter information to compensate for.

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 the tool's purpose: it is the first question of a decision guide. It names the specific resource ('Heat network duties checker') and implies an interactive step. It distinguishes itself from siblings like checker_answer and checker_tree by specifying it is the starting point. However, it does not explicitly say it initiates a session or presents a question, though 'first question' conveys that.

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 guidance on when to use this tool versus the siblings. The description does not mention that this should be called first before checker_answer or checker_tree, nor does it state any conditions or prerequisites. The agent must infer from the name and title that it starts the flow, but the description itself provides no explicit routing or usage context.

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 disclose the informational content returned: every question, option, and verdict. It does not describe the output format, size, or explicitly state that the operation is read-only and side-effect-free.

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. It lacks a finite verb like 'returns' or 'provides,' but it is compact and immediately communicates the tool's full content scope.

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 sufficiently explains what the tool contains and how it can be used for end-to-end reasoning. The main gap is the absence of explicit output format details, but that is minor given the simple static nature of the 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 tool has zero parameters and schema coverage is 100%, so the baseline is 4. No parameter-specific explanation is needed, and the description does not introduce any ambiguity.

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 whole decision tree of the Heat network duties checker, containing every question, option, and verdict. It implicitly differentiates from the stepwise checker_start/checker_answer siblings by presenting the complete tree rather than individual steps.

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?

'For reasoning end to end' implies this is the tool to use when you want the full decision structure rather than an interactive step-by-step flow. However, it does not explicitly state when not to use it or name the sibling 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?

With no annotations provided, the description carries the full burden of behavioral disclosure, and it delivers: it states that the enquiry is free, that nothing is bought/ordered/paid, that no quote is guaranteed, and that details go to human providers. It also describes return content. It does not explicitly state that calling enquiry_describe itself has no side effects, but nothing contradicts that and the attribution to submit_enquiry is unambiguous.

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?

Three sentences, appropriately sized, with the most important directive front-loaded ('Read first'). There is minor redundancy between the title ('not a purchase, not a guaranteed quote') and the description ('Nothing is bought, ordered or paid; no quote is guaranteed'), but every sentence otherwise 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 0-parameter, no-output-schema, no-annotation tool, the description covers what the tool does, what the underlying submission does not do, and what the tool returns (recipients, consent wording, confirmation mechanism). Lacking an output schema, it appropriately describes return content; slightly more format detail would be the only possible addition.

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 document about arguments. Per the baseline for 0-param tools, a 4 is appropriate; the description correctly spends no space on 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 specific purpose: 'States plainly what submit_enquiry does on Heat Network Check.' The tool's role as an explainer/read-first prerequisite is clear, and it is sharply distinguished from its sibling submit_enquiry by explicitly attributing the action to that sibling rather than itself.

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' gives explicit when-to-use guidance: consult this before acting (presumably before calling submit_enquiry). It does not name exclusions or compare explicitly against sibling alternatives like enquiry_fields or checker_start, but the sequencing cue is a clear and useful usage signal.

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 side effects. It does not state that this is a read-only operation or whether it requires authentication. While it likely only returns metadata, the description fails to explicitly communicate safety, leaving an agent to assume.

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 concise sentences. The first front-loads the tool's purpose and contents, the second provides a usage hint. No filler or 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?

For a simple read-only metadata tool with no output schema and no parameters, the description fully explains what is returned (field attributes) and how to use the result (key for submit_enquiry). Nothing an agent needs to call it 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?

The tool has zero parameters and the schema is empty, so schema description coverage is trivially 100%. The baseline is 4 for 0 params. The description adds no parameter semantics, but none are 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 clearly states the tool returns 'every field of the Heat Network Check enquiry' with specific attributes (key, label, type, required, help text, options). This distinguishes it from siblings like submit_enquiry (which submits answers) and enquiry_describe (which likely describes the enquiry itself). The verb is implicit but the resource is explicit.

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 provides a direct usage hint: 'Pass answers to submit_enquiry keyed by field key,' indicating this tool should be used to discover valid field keys before submission. It does not explicitly mention alternatives or when not to use it, but the context 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 burden of behavioral disclosure, and it delivers: it reveals the two-step validation/submission flow, the consent requirement, the email link that must be clicked before providers see the enquiry, and the non-purchase/non-quote nature of the action. This is unusually transparent for a tool with no annotations.

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 well organized with explicit 'Step 1' and 'Step 2' markers, and the key caveats are front-loaded ('NOT a purchase, NOT a guaranteed quote'). It repeats the consent text verbatim even though the schema already includes it, which adds slight redundancy, but every sentence still earns its place given the workflow complexity.

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, the description covers everything an agent needs: when to call, what to send, what to show the person, when to call again, what the second call does, and the email-link requirement. No critical operational detail 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?

Although the schema already describes all three parameters, the description adds workflow-level meaning: answers must be keyed by field key from enquiry_fields, consent=true reflects explicit agreement to the quoted consent line, and confirmation is the token returned from step 1. This connects each parameter to its role in the two-step process, going well beyond the schema.

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 Heat Network Check') and immediately distinguishes itself from a purchase or a guaranteed quote. It also clearly separates this tool from its siblings by framing the two-step submission workflow, so an agent can tell it apart from enquiry_fields and the checker 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 description gives explicit step-by-step instructions: call first with answers and consent=true, show the summary and consent line, then call again only if the person agrees, passing the confirmation token. It also cross-references enquiry_fields for the answer keys and states what the tool is not for, making the when-to-use guidance unambiguous.

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