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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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states that this is the first question, but does not say whether the tool returns a question, initializes a session, or simply provides static content. Important behavioral expectations such as statefulness or output format are not addressed.

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 front-loads the core purpose. It is appropriately brief for a simple tool, though it could be slightly more informative without becoming verbose.

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 no-parameter starting tool, the description provides enough context to identify the checker domain and position in the flow. However, it does not describe what the agent should expect in return or how to proceed to the next step, and with no output schema this information is not otherwise available.

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 are no parameter semantics for the description to clarify. This matches the baseline for a no-parameter tool, and no additional parameter-related information is necessary.

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 as the entry point to the Citizenship by descent checker by referring to 'the first question' of the decision guide. It is not a tautology, and it communicates the resource and stage, though it lacks an explicit verb like 'returns' or 'displays' and does not explicitly distinguish itself from 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?

Usage is implied: an agent can infer this tool should be used when beginning the citizenship-by-descent checker, since it presents the first question. However, there is no explicit guidance about when to use it versus checker_answer or checker_tree, and no mention of alternatives 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?

No annotations are provided, so the description must carry the full burden of explaining behavior. It states what the tree contains but does not explicitly say that calling the tool is read-only, what the returned structure looks like, or whether the result is large or expensive to fetch. Some behavior is implied by 'guide,' but explicit disclosure is missing.

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 sentence with no filler. It front-loads the essential content—'Every question, option and verdict'—and adds the purpose clause efficiently. 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?

For a parameterless tool with no output schema, the description is fairly complete: it names the domain, the scope, and the intended reasoning use. It could be slightly richer by clarifying the relationship to the step-by-step checker tools, but nothing critical is missing for invoking it.

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 coverage is 100%, so the description does not need to explain parameter meaning. The baseline for a no-parameter tool is 4, and no deduction is 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 identifies the resource: the complete Citizenship by descent checker guide, including every question, option, and verdict. This distinguishes it from likely step-by-step siblings like checker_start and checker_answer. It lacks an explicit verb such as 'retrieve' or 'list,' so it is not a full 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' gives clear context that this tool is intended when an agent needs the whole decision tree rather than a single step. It does not explicitly exclude alternatives or name when to use checker_start/checker_answer instead, but the intended use is reasonably 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, and it delivers: it clarifies that no purchase, order, or payment occurs, that no quote is guaranteed, that the service is free, and that the response includes who receives details, consent wording, and confirmation method. This is strong behavioral disclosure.

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 and front-loaded with "Read first," then uses each sentence to add meaningful context: what the tool explains, what it does not do, and what the response contains. No wasted words.

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 output schema, and no annotations, the description fully equips an agent to understand when to call this tool and what to expect from it. It covers purpose, boundaries, and return content sufficiently.

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 reflects this with empty properties, so there is nothing for the description to explain. Per the baseline for zero-parameter tools, a 4 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 clear purpose: it "states plainly what submit_enquiry does" on Citizenship Descent Checker, acting as a read-first explainer. It distinguishes itself from the actionable sibling submit_enquiry and from checker tools by emphasizing it is informational, not a purchase or guaranteed quote.

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" is an explicit cue to use this before interacting with submit_enquiry, giving clear when-to-use context. However, it does not explicitly mention alternatives or when-not-to-use scenarios, so it stops short of a full 5.

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?

There are no annotations, so the description must carry behavioral disclosure. It implicitly frames the tool as a read-only metadata lookup with no parameters, and it directs submission activity to submit_enquiry, which avoids implying mutation. However, it never explicitly says there are no side effects or what the response container looks like, and no output schema compensates for that.

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 compact, front-loaded sentences cover what the tool returns and how to consume it. There is no redundant phrasing or unnecessary context, making it easy for an agent to scan and understand.

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 no-parameter metadata lookup, the description supplies the essential information: the set of field attributes and the relationship to submit_enquiry via field keys. It does not specify the exact JSON shape, but the attribute enumeration is a reasonable stand-in given the absence of an output schema.

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 already exhaustively documents the input; the baseline for a no-parameter tool is 4. No parameter explanation is needed, and the description adds no irrelevant parameter detail.

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 Citizenship Descent Checker enquiry—and spells out the exact field attributes returned: key, label, type, required flag, help text, and allowed options. It is unambiguously about retrieving question metadata, though it relies on an implied verb 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 second sentence gives practical workflow guidance: use the returned field keys to pass answers to submit_enquiry. This establishes when the tool is relevant and connects it to a sibling, but it does not explicitly state exclusions or when to prefer another tool instead.

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 does so thoroughly. It discloses the two-step validation behavior, the confirmation-token requirement, the exact consent wording, that email notification happens, and that the provider only sees the enquiry after the person clicks the email link. This is exactly the kind of non-obvious behavior an agent needs to invoke the tool correctly.

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 sentence earns its place: the anti-purpose caveats, the two-step sequence, the consent line, and the email-link behavior are all operationally necessary. The Step 1/Step 2 structure front-loads the most important call sequence and makes the flow easy for an agent 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?

Given a two-step, multi-call workflow with no output schema, the description is remarkably complete. It explains what Step 1 returns, what Step 2 requires, what the consent condition is, and what downstream behavior the user should expect. There is no critical missing operational information for an agent to select and call the tool 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. The description adds real value by explaining that answers are 'keyed by field key from enquiry_fields,' that the same answers must be reused in Step 2, and that the confirmation parameter comes from Step 1's response. These relationships are not visible in the schema alone.

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 verb and resource: submitting an enquiry to Citizenship Descent Checker. It immediately distinguishes itself from a purchase and a guaranteed quote, and the two-step process uniquely separates it from the sibling checker and enquiry 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 procedural guidance for when to call the tool (Step 1 first, then Step 2 only after agreement) and includes important exclusions like 'not a purchase' and 'not a guaranteed quote.' It does not directly compare against sibling tool names, but the two-step workflow and linking to enquiry_fields provide sufficient context for correct use.

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