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Beckett — MCP for Godot

by beckettlab

set_debug_draw

Switch the running game's debug draw mode to isolate render stages: unshaded (albedo), wireframe (geometry), overdraw (transparency), normal_buffer (normals), lighting (light), normal (reset).

Instructions

Switch the RUNNING game's viewport debug draw mode, then screenshot to see one render stage in isolation. unshaded = albedo only (clears lighting/fog/exposure as suspects in one shot). wireframe = is the geometry even there (culled or degenerate meshes show as nothing). overdraw = transparency cost. normal_buffer = flipped or NaN normals. lighting = light contribution only. normal = back to the real image. Reach for this FIRST when the picture is wrong; render_probe then answers the same question in numbers.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeYesnormal | unshaded | lighting | overdraw | wireframe | normal_buffer
Behavior5/5

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

Although annotations are neutral, the description adds rich behavioral context by explaining what each debug mode visually reveals (e.g., 'unshaded = albedo only', 'wireframe = is the geometry even there'). It also shows the workflow of switching then screenshotting, making the tool's behavior transparent.

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 long but every sentence serves a purpose: it front-loads the core action, defines each mode with practical implications, and ends with a clear recommendation. No redundant or filler content.

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?

For a single-parameter tool with no output schema, the description is fully complete. It covers what the tool does, how to use it, what each mode means, and how it relates to the sibling tool render_probe. The user has everything needed 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?

Even though schema coverage is 100%, the description goes beyond listing enum values by explaining the diagnostic meaning of each mode (e.g., 'overdraw = transparency cost', 'normal_buffer = flipped or NaN normals'). This adds substantial value for correct parameter selection.

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 action: 'Switch the RUNNING game's viewport debug draw mode'. It specifies the resource (viewport debug draw) and distinguishes itself from sibling tools by noting that render_probe answers the same question in numbers.

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

Usage Guidelines5/5

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

Provides explicit when-to-use guidance: 'Reach for this FIRST when the picture is wrong'. It also describes the diagnostic role of each mode and names the alternative (render_probe), offering clear context for choosing this tool over siblings.

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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