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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 explaining behavior. It only says that this is 'the first question' of a decision guide, which implies a read-only presentation of a question but does not disclose whether state is created, whether the guide can be restarted, what the response contains, or any 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 concise sentence that adds useful information beyond the title ('first question') without any filler or repetition. It is appropriately sized for such a simple tool.

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 low-complexity with no parameters, so the description is minimally sufficient to justify calling it first. However, there is no output schema and no mention of what the response will look like or how to proceed after receiving the first question, which leaves the agent without explicit next-step 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 tool has zero parameters, so there is nothing for the description to clarify about parameter meaning. The baseline for a zero-parameter tool is 4, and the description correctly adds no unnecessary parameter details.

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' of a specific decision guide, which clearly signals it is the entry point. It distinguishes itself from sibling tools like checker_answer and checker_tree by establishing its position at the start of the flow, though it lacks an explicit verb like 'starts' 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 that this tool should be called at the beginning of the Malta VAT registration checker flow, and that checker_answer or checker_tree would be used afterwards. However, it does not explicitly state when to use this tool versus its siblings or mention any conditions or prerequisites.

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 accurately reveals the tool's content scope ('every question, option and verdict') but does not describe the output format, size, or whether it is a static snapshot. This is a moderate disclosure for a read-like tool without 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 a single, front-loaded sentence that states the subject, scope, and intended purpose without any filler. Every phrase contributes to the agent's 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 parameterless tool with no output schema, the description provides the key facts: it returns the complete decision tree of the checker guide for end-to-end reasoning. It could add structure details, but the current content is sufficient for an agent to decide to call it and know what it will receive.

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 properties and schema description coverage is 100%, so there are no parameters to document. The baseline for zero-parameter tools applies; 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 identifies a specific resource (the Malta VAT registration checker guide) and explicitly states its scope: every question, option, and verdict in the decision tree. This clearly distinguishes it from sibling tools such as checker_answer or checker_start, which handle individual steps or starting points.

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' gives a clear context for when an agent should use this tool: when the full decision tree is needed, not a single answer. It does not explicitly list exclusions or alternative tool names, but the usage context is sufficiently implied.

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 behavioral disclosure burden. It clearly states this is informational: it describes what submit_enquiry does, emphasizes that nothing is bought, ordered, or paid, notes no quote is guaranteed, and says it is free. It also reveals what the call returns (recipient details, consent wording, confirmation method), though it does not explicitly say 'this call performs no external 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 tight and front-loaded: it opens with the imperative 'Read first', then delivers the essential facts in two sentences. Every clause adds value—scope, non-purchase, free, non-guaranteed, and output contents—with no filler or repetition.

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 informational tool, the description is complete: it tells the agent what the tool does, what content it returns, and the key limitations. There are no missing parameters or return-value expectations that an agent would need to call it 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 tool has zero parameters and an empty input schema, so there are no parameter semantics to clarify. Per the baseline rule for zero-parameter tools, a score of 4 applies since the schema fully covers the call signature and the description adds no parameter-related confusion.

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 specific verb and resource: it 'states plainly what submit_enquiry does' on Malta VAT Registration, clearly identifying the tool as a descriptive companion rather than the action itself. The title reinforces the non-transactional scope ('not a purchase, not a guaranteed quote'), and the description distinguishes it from submit_enquiry by clarifying nothing is bought, ordered, or paid.

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 explicitly says 'Read first', which instructs the agent to consume this tool before calling submit_enquiry. It provides clear context for when to use the description tool, though it does not explicitly contrast it with the checker_* siblings or state when not to use them.

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 burden of disclosing behavior. It clearly implies a read-only metadata retrieval operation by describing the field attributes returned, and the instruction to pass answers to submit_enquiry emphasizes that this tool itself does not submit. It does not explicitly state side effects or auth, but for a simple zero-parameter getter the behavior is adequately 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?

Two dense, front-loaded sentences with no wasted words. The first sentence states the resource and output fields; the second sentence gives a direct usage hint. Every clause 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 simple zero-parameter introspection tool, the description covers the key information: what fields are listed and how the output should be used with submit_enquiry. It does not specify the exact return container (array vs object), but the list of attributes and the keyed-answers hint give enough context for an agent to proceed.

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 the baseline is 4. The description needs to explain no parameters, and it appropriately focuses on the output rather than parameter semantics.

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 Malta VAT Registration enquiry') and enumerates exactly what is returned: key, label, type, required, help text, and allowed options. This differentiates it from siblings like submit_enquiry and checker_start by focusing on field metadata.

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 clear usage context by instructing 'Pass answers to submit_enquiry keyed by field key,' linking this tool to the submission workflow. It does not explicitly contrast with alternatives like enquiry_describe, but the intended usage is obvious from the field-key connection.

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 behavioral burden and does so thoroughly: it discloses validation behavior, the exact return contents of step 1 (summary, consent line, token), the email-verification requirement before any provider sees the data, and the downstream consequence (contact details sent to up to three MFSA-authorised providers with opt-out rights).

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 highest-value disambiguation ('NOT a purchase') and organized as Step 1 / Step 2. It is long, and the full consent sentence is duplicated between the description and the consent parameter's own schema description, which is somewhat redundant, but the structure remains scannable and each element serves the 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?

With no output schema, the description must describe returns, and it does: step 1 yields a summary, a consent line and a token; step 2 triggers an email with a verification link. Given the nested 'answers' object and the two-phase flow, an agent has everything needed to call this 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?

Schema coverage is 100%, so the baseline is 3, but the description adds real meaning: it links 'answers' to the field keys produced by the sibling tool enquiry_fields and explains that 'confirmation' is the token returned by step 1 and must only be sent after approval, which is step-ordering context the schema alone does not convey.

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 verb and resource ('Submits an enquiry to Malta VAT Registration') and immediately disambiguates the most likely misinterpretation with 'NOT a purchase, NOT a guaranteed quote.' An agent can distinguish it from siblings like enquiry_fields and enquiry_describe, which gather/describe data rather than submit it.

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?

Explicitly lays out the two-step protocol: step 1 with answers + consent=true, then step 2 only if the person agrees, with the confirmation token. The gating condition for the second call is stated outright, leaving nothing to inference.

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