ask_user

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

Annotations (readOnlyHint=true, idempotentHint=true) are consistent with asking a user. The description adds behavioral context beyond annotations by noting support for multiple questions, options, and importance, and that it can be used at any time. No contradictions with 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 concise and front-loaded with the purpose. Every sentence adds value, and there is no redundant or wasted text. It effectively communicates the tool's functionality in a compact form.

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 simple input schema and lack of output schema, the description covers when to use and what it does. However, it does not explain the expected response format or behavior on errors, which could be helpful for a tool that interacts with users.

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 100% with parameter-level descriptions. The tool description provides an overview of parameter capabilities but does not add significant semantic value beyond what the schema already provides. Baseline score of 3 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 clearly states the tool's purpose: to ask users questions when the AI needs more information or encounters uncertainty. It specifies that it supports single/multiple questions, options, and importance marking, which distinguishes it from sibling tools like search_memory or interview.

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 provides explicit when-to-use guidance: '当 AI 需要更多信息、遇到不确定因素时使用' (use when AI needs more info or uncertainty). It also notes it can be used at any time. However, it does not explicitly state when not to use or mention alternatives, which would improve clarity.

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