request_user_input

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

Without annotations, the description fully discloses behavior: pop-up display, return of user response or timeout after 60 seconds, context maintenance, graceful handling of empty responses, and formatting with project context. No contradictions.

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 well-structured with sections but is lengthy (many sentences). Some redundancy between importantNotes and bestPractices (e.g., both emphasize frequent use). Could be tightened without losing clarity.

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 3-parameter tool with no output schema, the description is exceptionally complete: covers purpose, usage guidance, features, best practices, and examples. Leaves no gaps in understanding.

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 baseline 3. The description's parameters section adds context beyond schema: e.g., projectName is 'used in prompt formatting', predefinedOptions are optional. This adds meaningful value.

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 sends a question to the user via a pop-up command prompt, with explicit purpose of clarifying requirements, confirming plans, or resolving ambiguity. It distinguishes from sibling tools like ask_intensive_chat by specifying a pop-up prompt rather than a chat message.

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?

A dedicated 'whenToUseThisTool' section provides exhaustive scenarios, and 'bestPractices' explicitly instructs not to use the tool when another tool can answer the question, offering clear alternatives. This provides excellent decision support.

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