site

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

没有提供任何annotations，描述必须承担全部行为披露责任。描述只说明了输出类型（下一题或最终裁决），但'answer'语义暗示这是一个提交答案并推进状态的mutation操作，却未披露是否会修改状态、重复提交的行为、无效choice或未知question id的错误处理。对无注解覆盖的交互推进工具，这是显著的信息缺口。

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?

单一句话完整表达了输入条件和输出结果，前置条件、后置结果，零冗余信息。每个词都承载含义，且与工具标题精确对应，结构高效。

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?

对于只有2个参数且无输出schema的简单工具，描述覆盖了核心调用方式。但缺少边界行为（无效索引、未知question id）和流程上下文——这是一个状态机推进步骤（checker_start启动、checker_tree查看结构）。作为交互流程中的一环，信息刚好够调用，但不足以让agent处理异常情况。

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描述覆盖率为0%，描述成功补偿了关键语义：question被明确为question id（而非任意字符串），choice被解释为所选选项的索引，赋予了schema中仅有名字和类型的参数以业务含义。但未提供question id的具体格式或choice的取值上限，因此未到满分。

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?

描述使用具体动词'return'，明确说明输入（question id + choice index）和输出（next question 或 final verdict），与标题'Answer a question, get the next step'一致。虽然没有显式命名兄弟工具checker_start/checker_tree，但描述的机制（给定回答推进到下一题）自然区别于开始和树查看工具，不过缺少明确的区分语句，所以给4分。

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?

描述隐含了使用条件：当你已有question id并希望提交choice索引时调用。但它没有明确说明何时应使用checker_start或checker_tree替代，也没有排除条件、前提或调用顺序信息。用法靠推断而非明示，属于最低可用水平。

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 states that the tool is the first question of a decision guide; it does not say what happens when invoked, whether it returns a question, whether it creates state, or how the agent should proceed after 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?

The description is brief and free of fluff, but it is under-specified rather than efficiently concise. A single noun phrase leaves the agent without enough actionable structure about what the tool does or returns.

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 and no annotation context, the description should explain what the agent can expect from calling this tool and how it fits into the decision guide flow. It only labels the tool as the first question, leaving critical operational context 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 input schema is empty, so there are no parameter semantics for the description to clarify. A baseline of 4 is appropriate because no parameter documentation burden exists.

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 'Which trial route fits?' decision guide, so an agent can infer it is the entry point. However, it uses a noun phrase rather than a specific verb like 'starts' or 'returns', and it does not clearly distinguish the tool's function from checker_answer or checker_tree beyond its name.

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 guidance on when to call this tool versus alternatives such as checker_answer or checker_tree. The word 'first' implies usage at the beginning of the guide, but the description does not state prerequisites, next steps, or conditions for choosing a sibling 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 transparency burden. It discloses the content returned—every question, option, and verdict—but does not describe the return format, size, or whether the tool is purely read-only. Since it is a zero-parameter informational tool, this is a moderate gap rather than a contradiction.

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 compact sentence that front-loads the essential scope: 'Every question, option and verdict.' Each word earns its place, with no fluff, repetition, or unnecessary 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?

For a no-input tool, the description provides the core content scope and the intended use case ('reasoning end to end'). The sibling names help position it as the full-tree counterpart to more specific checker tools. It stops short of describing output structure or explicitly contrasting with siblings, but this is acceptable for this simple 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 the input schema is empty, so schema description coverage is effectively 100%. There is nothing for the description to add about parameter meaning. The baseline of 4 for no-parameter tools 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—the complete 'Which trial route fits?' decision tree—and enumerates its contents: every question, option, and verdict. It does not use a strong action verb like 'retrieve' or 'list', nor does it name a sibling directly, but 'whole decision tree' clearly contrasts with node-level tools like checker_answer and checker_start.

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 an implied use case: call this when you want the full guide in a single view. However, it never explicitly says when to use it instead of checker_answer or checker_start, and it offers no exclusions or alternative routing. Guidance is present but only implicit.

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 explains that the underlying enquiry is not a purchase, no quote is guaranteed, and it is free, and it details what the describe tool returns. This goes beyond a generic 'describes submit_enquiry' statement.

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 three sentences, each earning its place: a directive to read first, a plain explanation of what the action does, and a summary of the returned information. It is front-loaded and free of 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 zero-parameter, no-output-schema tool, the description is complete. It tells the agent what the tool is for, clarifies important caveats about the underlying enquiry, and lists the specific information it returns.

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 parameter semantics are not applicable. Per the baseline for zero-parameter tools, this is a solid score; the description focuses on behavior and return value instead.

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 purpose: it explains what submit_enquiry does on Football Trials Database. The title and 'Read first' framing make it distinct from the sibling action tools, particularly submit_enquiry 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 instruction 'Read first' explicitly signals when to use this tool: before using submit_enquiry. It gives clear context about the enquiry process, although it does not explicitly name 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 burden of behavioral disclosure. It communicates that the tool exposes all enquiry fields and their metadata, implying a read-only metadata lookup. It does not discuss side effects, authentication, or whether the data is static or dynamically generated, but for a simple field-listing tool the description is not misleading.

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 with no filler. The first sentence front-loads the core content of the tool, and the second sentence adds a clear, actionable relationship to submit_enquiry. 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 zero-parameter metadata tool with no output schema, the description explains the return content well and connects it to the submission workflow. It could be slightly more explicit about the output shape, but the enumerated fields give an agent enough understanding to use the tool and interpret results.

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% by virtue of an empty schema, so the baseline is 4. The description adds useful semantic context by explaining what each field represents and how field keys are used downstream in submit_enquiry, which is valuable even though there are no parameters to document.

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 (the Football Trials Database enquiry fields) and enumerates exactly what is included: key, label, type, required flag, help text, and allowed options. It distinguishes itself from submit_enquiry by explaining that answers must be keyed by these fields, though it lacks an explicit verb like 'retrieve' or 'list'.

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 when to use the tool: when you need the field definitions to construct a submission, since it says to pass answers to submit_enquiry keyed by field key. However, it does not explicitly compare against siblings like checker_answer, checker_start, or enquiry_describe, nor state when this tool should not be used.

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 fully delivers. It discloses the stateful two-step behavior, that step 1 only validates, that an email with a click-link is required before any provider sees the enquiry, and the exact consent semantics. This is rich, accurate behavioral disclosure with no reliance on structured 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 long but justified by the tool's complexity: a two-step stateful flow, consent requirements, and email verification. It is front-loaded with the crucial 'NOT a purchase, NOT a guaranteed quote' caveat and organized into clear Step 1/Step 2 sections, so 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 complex stateful tool with no output schema and no annotations, the description is remarkably complete: it covers what step 1 returns, what step 2 does, the post-submission email-link requirement, and consent semantics. Minor gaps remain, such as failure modes, behavior when consent=false, or invalid-token handling, but nothing essential to correct invocation 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?

Schema coverage is 100%, so the baseline is 3. The description adds real value on top: it explains that answers must be keyed by field keys from enquiry_fields, that the confirmation parameter is the token produced by step 1, and it embeds the exact consent language tied to the consent parameter. This meaningfully deepens the agent's understanding beyond the bare 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?

States a specific verb and resource ('Submits an enquiry to Football Trials Database') and immediately disambiguates with 'NOT a purchase, NOT a guaranteed quote.' The two-step flow and title further clarify it is the submission action, distinct from the checker_* siblings and enquiry_describe/enquiry_fields which are clearly exploration or verification 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?

Provides an explicit step-by-step calling protocol: step 1 with answers and consent=true to obtain a token, step 2 only if the person agrees, using the same answers plus the token. It gives a clear when-not ('NOT a purchase') and references enquiry_fields as the source for field keys. However, it stops short of explicitly naming alternative tools and conditions for when to use them instead.

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