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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 describe what the tool returns, whether it prompts the user, or how the response connects to subsequent checker tools. This is a significant gap for an executable tool.

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 with no wasted words, and the key information—'first question' and 'Malta work permit checker'—appears early. It is appropriately sized for a tool with no parameters, though slightly more detail about the return behavior would be welcome.

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, the description is minimally adequate: an agent knows this is the starting point of the decision guide and can call it without providing inputs. However, it does not explain what the agent should expect as output or how to proceed, which leaves some ambiguity given the sibling checker tools.

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 and schema description coverage is 100%, so there is nothing for the description to add about parameter semantics. The baseline of 4 applies because no parameter information 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 identifies the tool as the first question of the Malta work permit checker decision guide, making its role as an entry point clear. It does not explicitly state the action (e.g., 'starts' or 'displays'), but the title and 'first question' phrasing strongly convey the intended use.

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 no explicit guidance on when to use this tool versus alternatives. The phrase 'first question' implies it should be used at the start, but there is no mention of when not to use it or how it relates to checker_answer or checker_tree.

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 conveys that the tool exposes every question, option, and verdict, which implies a read-only informational retrieval, but it does not mention output format, size, or any potential limitations. The behavior is adequately hinted but not fully specified.

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 focused sentence that front-loads the scope ('Every question, option and verdict') and immediately states the purpose. There is no extraneous wording or repetition of 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 no-parameter tool with no output schema, the description tells the agent what content will be returned and why it is useful. It stops short of explaining the return structure or how the tree is organized, but the core information needed to invoke the tool correctly is present.

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 no parameter ambiguity. Per the baseline for zero-parameter tools, the description does not need to compensate for missing parameter documentation.

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 decision tree for the Malta work permit checker) and its intended use (reasoning end to end). It lacks an explicit verb like 'returns' or 'provides,' but it is not a tautology and is distinguishable from the checker_answer and checker_start siblings by its scope.

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 intended use case and implies this tool is for full-tree exploration rather than single-answer lookup. However, it does not explicitly state when to prefer this over checker_answer or checker_start, nor does it mention any exclusions.

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 fully carries behavioral disclosure: it states the action is free, non-committal, and involves human providers who quote directly. It also discloses what is returned—who receives details, consent wording, and confirmation method—providing a clear behavioral contract.

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 tight sentences front-load the critical 'Read first' instruction, then state the core behavior, exclusions, and return content. Every sentence earns its place and the description is compact enough to scan quickly.

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 no input parameters and no output schema, the description supplies everything an agent needs: when to call it, what the enquiry involves, cost and guarantee status, and what the response will contain. This is complete for a helper tool that introduces a sibling.

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 already covers this fully, so there is nothing extra for the description to explain. The baseline of 4 applies because there is no parameter surface to elaborate on.

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: it explains what submit_enquiry does, namely 'starts an enquiry with human providers who quote directly.' The title and description clearly differentiate it from the sibling submit_enquiry and from a purchase or guaranteed quote, so an agent knows this is the descriptive, read-first 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?

Opens with the direct instruction 'Read first,' explicitly telling the agent to use this before acting on submit_enquiry. It also clarifies when this tool is not the right path by emphasizing that nothing is bought, ordered, or paid and no quote is guaranteed, giving the agent an explicit exclusion.

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 burden. It discloses that the tool produces field metadata and implies a read-only, non-submitting role by pointing to submit_enquiry for actual answers. It does not explicitly state 'does not modify anything' or mention auth/rate limits, which keeps this at 4 rather than 5.

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 dense sentence packs the resource, the enumerated return fields, and the downstream usage instruction. There is no filler or redundancy; every phrase 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 and no annotations, the description fully compensates by enumerating exactly what will be returned and how to apply the result when calling submit_enquiry. Nothing essential is missing for correct invocation.

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 description does not need to explain parameter semantics. The baseline for a zero-parameter tool is 4, and the description adds useful meaning by explaining how the returned field keys should be used as input keys for submit_enquiry.

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 Malta Work Permit Checker enquiry') and the content delivered: key, label, type, required flag, help text, and allowed options. It is not phrased with an explicit verb like 'returns' or 'lists', but the title and sentence together leave little doubt. It does not explicitly differentiate from the sibling enquiry_describe, 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 description supplies clear workflow context by telling the agent to pass answers to submit_enquiry keyed by field key. It does not explicitly enumerate alternatives or when-not-to-use cases, but the intended use is obvious for a schema-like introspection tool.

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 so thoroughly: it discloses the two-step submission flow, validation and summary return, the role of the confirmation token, the email-link requirement before providers see anything, and the exact consent wording. No annotation contradiction exists.

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: primary action and caveats are front-loaded, then Step 1 and Step 2 are clearly separated. It avoids filler while covering all necessary workflow details.

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 and no annotations, the description is remarkably complete: it explains what Step 1 returns, what must be shown to the user, what the token is for, and what happens after Step 2. An agent has enough information to execute the full two-step flow 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?

Although schema coverage is 100%, the description adds substantial meaning beyond the schema: answers must be keyed by enquiry_fields, consent has a precise contractual meaning, and the confirmation token is only relevant for the second call. This resolves how the optional confirmation parameter should be used.

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') and immediately clarifies that this is NOT a purchase or a guaranteed quote. It further distinguishes the two-step nature of the operation and ties answers to enquiry_fields keys, making the tool's role unmistakable relative to its 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 explicit procedural guidance: call first with answers and consent=true, show the summary and consent line, then call again with the same answers and the confirmation token only if the person agrees. It does not explicitly name alternative tools or state when to prefer them, but the step sequence and consent condition are clearly defined.

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