clarify_with_user

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

With no annotations provided, the description fully carries the burden of behavioral disclosure. It explains the short-circuit behavior (clarificationNeeded: false), the structure of each question (suggested_answer, options, dimension), and the effect of the force flag. It also notes that passing a category skips questions about category/platform. This is comprehensive for a non-destructive 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 thorough but not overly verbose. It front-loads the core purpose and then expands on behavior and structure. Every sentence contributes useful information. Could be slightly more compact, but it remains efficient.

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 9 parameters (1 required), high schema coverage, and no output schema, the description provides complete context. It explains the tool's behavior, response format, short-circuit logic, and ties to sibling tools (optimize_prompt). No critical gaps are 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?

Schema coverage is 89%, so the schema already documents most parameters. The description adds value by explaining the structure of the generated questions (suggested_answer, options, dimension) and the effect of force: true. It also clarifies how category can skip certain questions. These details enhance understanding beyond 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 clearly states the tool's purpose: 'Given an ambiguous draft prompt, return 1–3 targeted clarifying questions instead of guessing.' It specifies the verb (return), resource (clarifying questions), and distinguishes from alternative behaviors (short-circuiting). This is specific and 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 provides explicit when-to-use and when-not-to-use guidance: it explains the short-circuit behavior when the analyzer is highly confident and the prompt is non-trivially long, and mentions pipelining in front of optimize_prompt. It also describes the force parameter for overriding the short-circuit. This clearly differentiates usage contexts.

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