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ask_in_game

Get real-time user input during gameplay by displaying a question and waiting for a typed response, enabling interactive confirmations.

Instructions

Ask a question in-game and wait for the user's response.

Use this instead of terminal confirmations when the user is playing. Shows the question via notification, opens keyboard, waits for response.

Common pattern for confirmations: result = ask_in_game("Write camber=0.1 to wheel 0? Type yes/no") if "yes" in result.lower(): # proceed with write

Args: question: The question to display in-game timeout_seconds: How long to wait for response (default 60)

Returns: The user's typed response

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
questionYes
timeout_secondsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

The description details the behavior: shows notification, opens keyboard, waits for response, and returns typed response. It mentions the timeout parameter but does not specify what happens when the timeout occurs or if the user cancels (e.g., returns empty string). Without annotations, this gap is notable.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact, using a few sentences and a code example without redundancy. The main purpose is front-loaded, and every sentence adds value—no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity (2 parameters, simple behavior) and the presence of an output schema, the description covers the what, when, how, and return value. No critical information is missing for an AI agent to invoke it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description fully compensates by explaining both parameters: 'question' as 'The question to display in-game' and 'timeout_seconds' as 'How long to wait for response (default 60)'. This adds critical meaning beyond the schema types and defaults.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: 'Ask a question in-game and wait for the user's response.' The verb 'ask' and resource 'question in-game' are specific, and the description distinguishes it from terminal confirmations, making its purpose unique among siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly advises using this tool 'instead of terminal confirmations when the user is playing,' providing clear context. It also demonstrates a common pattern for confirmations. However, it does not mention alternatives like 'await_user_message' which might exist among siblings, slightly reducing completeness.

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

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