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game_observe

Observe an Unreal Engine 5 game by capturing a screenshot and recent log lines, with optional coordinate grid and state inclusion for context-aware decisions.

Instructions

Look at the game: a screenshot plus the log lines since the last look.

grid=True overlays a labelled 0..1 coordinate grid -- turn it on when you intend to click something with game_mouse. show_ui=False hides the HUD/UMG overlays. log_pattern is a regex filter over the new log lines. state=True folds in game_state, so one call answers what the world looks like and what it actually contains.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
logNo
gridNo
imageNo
levelNo
stateNo
qualityNo
show_uiNo
max_sizeNo
log_limitNo
log_patternNo
Behavior4/5

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

With no annotations, the description carries full responsibility. It discloses that logs are 'since the last look' (incremental), that grid overlays a coordinate system, that show_ui hides overlays, and that state folds in game_state. It does not mention read-only status, rate limits, or side effects, but the 'look' verb implies non-destructive. Key behavioral nuances are surfaced.

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

Conciseness4/5

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

The description is compact: a one-line purpose followed by four backtick parameter hints. The essential information is front-loaded, and each sentence adds value. It avoids redundancy and reads naturally. Minor gap: it could include a note about output format, but overall it is well-structured.

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

Completeness3/5

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

With 10 optional parameters, no output schema, and no annotations, the description is only partially complete. It explains the primary behavior and four parameters, but does not address quality, max_size, log_limit, or level, nor what the returned screenshot/log looks like. For an observation tool with many knobs, more detail would be expected.

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

Parameters3/5

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

Schema coverage is 0%, so the description must add meaning to parameters. It explains grid, show_ui, log_pattern, and state, but leaves log, image, level, quality, max_size, and log_limit unexplained. The core parameters affecting output and interaction (grid for clicks, show_ui for overlay) are covered, but the rest are ambiguous to the agent.

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 it returns a screenshot plus log lines, combining visual and textual state. It distinguishes itself from siblings like game_log (logs only) and game_state (state only) by merging both, and hints at optional state inclusion. The verb 'observe' and resource 'game' are specific.

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?

It gives explicit usage hints for the grid parameter ('turn it on when you intend to click something with game_mouse') and explains when to use state=True. It implies this tool replaces separate calls to game_log and game_state, but does not explicitly say when not to use it. The guidance is concrete and actionable.

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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