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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 full burden. It discloses that the tool consumes a 'question id' and 'choice index' and returns 'next question or final verdict', but does not explain side effects (e.g., whether it records an answer), authorization needs, or error behavior. For a tool named 'checker_answer', the lack of detail on whether it persists the answer is a notable 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?

One concise sentence that front-loads the function and outputs, with no extraneous wording. Every clause serves a 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?

Given two required parameters, no output schema, and no annotations, the description is too sparse. It omits critical context: what the 'next question' looks like (structure), whether 'final verdict' is always present, and how to handle invalid question ids or out-of-range choices. For a tool that likely drives a quiz flow, an agent needs more behavioral expectations.

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 that 'question' is a question id and 'choice' is an option index, providing minimal semantics beyond the schema. It does not clarify the format of the question id (e.g., string identifier) or whether the choice index is zero-based (schema minimum is 0, so implicit but not stated in description).

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 verb ('return') and resource ('next question or final verdict') tied to inputs ('question id and chosen option'), which distinguishes it from typical CRUD tools. It doesn't explicitly differentiate from siblings like 'checker_start' or 'checker_tree', but the core purpose is unambiguous.

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 context: use this tool after having a 'question id' and a selected choice index. It lacks explicit when-not-to-use guidance or alternatives (e.g., when to use checker_start to begin or checker_tree to view options), but the basic trigger is inferable.

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 behavioral disclosure. It hints that this tool exposes the first question of a guide, but it does not say whether calling it returns a prompt, creates session state, has side effects, or what the response contains.

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 with no filler, front-loading the resource and its position in the guide. It is not overly verbose, though its brevity comes at the cost of behavioral and 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?

With no annotations, no output schema, and zero parameters, the description still needed to explain what happens when the tool is invoked and how it connects to checker_answer and checker_tree. The single phrase leaves too much to inference for an agent to confidently invoke and interpret 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 input schema has zero properties and schema coverage is 100%, so there are no parameter semantics for the description to explain. The baseline of 4 for a zero-parameter tool 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 identifies the resource (MiCA requirements checker) and its stage ('first question'), but it never states the action the tool performs, such as returning, displaying, or starting a question. The word 'first' weakly distinguishes it from sibling decision-guide tools, but the missing verb leaves the purpose implied rather than 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?

There is no explicit guidance on when to use this tool versus checker_answer, checker_tree, or the enquiry_* tools. However, 'first question of the ... decision guide' implies that this is the entry point, so usage context is present but not clearly spelled out.

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 behavioral disclosure. It does state the tool provides all questions, options, and verdicts, which signals a read-only, comprehensive retrieval. However, it does not disclose potential size/volume, output format, or any side-effect/pagination behavior, leaving some behavioral aspects unspecified.

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 efficiently captures the tool's content and purpose. It contains no filler or redundant information. It could be slightly more structured (e.g., stating 'returns the full tree'), but it is appropriately concise.

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 low complexity (no parameters, no annotations, no output schema), the description is largely sufficient: it tells the agent exactly what data the tool exposes and hints at the end-to-end reasoning use case. It does not explain how the tree relates to the sibling checker tools, which prevents a perfect score, but for zero-param invocation this is a minor gap.

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 an empty object with 100% coverage. The baseline for 0 params is 4, and the description adds no unnecessary parameter commentary. It correctly conveys that no input is needed to retrieve the whole tree.

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 tool's content: every question, option, and verdict of the MiCA requirements checker guide. The phrase 'whole decision tree' in the title and 'Every...' in the description convey that this is the complete dataset. However, it lacks an explicit action verb like 'returns' or 'retrieves', and it does not directly name sibling tools to differentiate itself, so it stops short of 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 phrase 'for reasoning end to end' implies this tool is meant for scenarios requiring the full decision tree rather than step-by-step interaction. No explicit guidance is given on when to use this versus checker_start, checker_answer, or the enquiry_* siblings, making the usage context only implied rather than clearly stated.

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 and meets it: it states that nothing is bought, ordered, or paid, that no quote is guaranteed, that it is free, and that the tool returns the recipient details, consent wording, and confirmation method. This gives an agent a clear safety and side-effect profile before calling it.

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 deliver the essential facts with the directive 'Read first' front-loaded. Every sentence contributes: what the tool describes, what it does not do, and what it returns, 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 parameterless, read-only explainer tool with no output schema, the description fully covers invocation timing, safety of the underlying flow, and the content of the returned explanation. An agent has enough information to decide to call it and 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, so there are no parameters to document; baseline 4 applies. The description adds no parameter-specific information, which is appropriate.

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: it 'States plainly what submit_enquiry does on MiCA Requirements,' naming the verb, the resource (submit_enquiry), and the context. The title reinforces the distinction by clarifying the result is an enquiry with a human, not a purchase or guaranteed quote, which separates this descriptive tool from the actual submission workflow.

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?

'Read first' gives an explicit temporal cue to use this tool before submit_enquiry, and the rest of the description makes clear it is the explanatory prerequisite. It does not explicitly list when-not-to-use or name the checker_* alternatives, but the primary routing to submit_enquiry 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 explaining behavior. It discloses the expected content of the tool's response: key, label, type, required flag, help text, and allowed options. It also indirectly signals that this tool is informational rather than a submission action by directing actual answers to submit_enquiry.

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 sentences long, with no filler. The first sentence states what the tool exposes, and the second provides the key usage pointer. 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?

For a zero-parameter introspection tool with no output schema, the description sufficiently explains what will be returned and how the result should be used downstream. The sibling tools are mostly distinct, and the connection to submit_enquiry is explicitly made.

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 input parameters, so there is nothing for the description to explain. The mention of field keys is not about this tool's parameters but about how to use the returned data with submit_enquiry, which is still useful context.

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 tool's resource: every field of the MiCA Requirements enquiry, listing the attributes included (key, label, type, required, help text, allowed options). It is easy to understand what the tool returns, though it lacks a direct action verb like 'lists' or 'returns' and does not explicitly distinguish itself from the sibling enquiry_describe.

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 context by telling the agent to pass answers to submit_enquiry keyed by field key, implying this tool is the lookup step before submission. It does not explicitly mention when not to use it or compare against sibling tools, so it falls just short of full 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 provided, the description carries the full behavioral disclosure burden. It thoroughly covers the two-step behavior, the exact consent text, the return of a summary/consent line/token, and the post-submission email link requirement before providers see the enquiry.

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 every part earns its place: the non-purchase clarification, the step-by-step flow, the consent language, and the email-link condition. The Step 1/Step 2 structure makes a complex two-step interaction easy to follow.

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, the description explains the key return values and final outcome well. It could be slightly more complete by explicitly telling the agent to call enquiry_fields first and by covering validation-failure behavior, but overall it is functionally sufficient.

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 schema coverage is 100%, the description adds significant meaning: answers are keyed by field key from enquiry_fields, consent must match the exact consent statement, and confirmation is the token returned from step 1. This goes well beyond the bare parameter names in 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 opens with a specific verb and resource: 'Submits an enquiry to MiCA Requirements.' It also explicitly distinguishes itself from a purchase and a guaranteed quote, making the tool's scope unmistakable even before considering siblings.

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, detailed usage context: call once for validation, show the summary and consent line, then call again with the confirmation token only if the person agrees. It does not name sibling tools as alternatives, but it provides enough step-by-step guidance to know when and how to invoke the tool.

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