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schwarztim

Bambu Lab MCP Server

by schwarztim

led_control

Control the printer chamber or logo LED lights on Bambu Lab 3D printers by turning them on or off through the MCP server.

Instructions

Control the printer chamber or logo LED lights

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeYesLED state
nodeNoWhich LED to control (default: chamber_light)
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It mentions 'Control' which implies a write operation, but doesn't disclose behavioral traits such as required permissions, side effects (e.g., if turning off lights affects printing), or error handling. This leaves significant gaps for an agent to understand how to use it safely and effectively.

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 a single, efficient sentence that directly states the tool's function without any fluff. It is front-loaded and appropriately sized, making it easy for an agent to parse quickly.

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

Completeness2/5

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

Given the tool's complexity (a write operation with no annotations and no output schema), the description is insufficient. It doesn't cover return values, error conditions, or practical usage context, leaving the agent with incomplete information to invoke the tool correctly in real-world scenarios.

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?

The input schema has 100% description coverage, with clear enums and descriptions for both parameters. The description adds no additional meaning beyond the schema, such as explaining what 'chamber_light' or 'work_light' refer to in practice. Since the schema does the heavy lifting, the baseline score of 3 is appropriate.

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

Purpose4/5

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

The description clearly states the verb ('Control') and resource ('printer chamber or logo LED lights'), making the tool's purpose evident. However, it doesn't differentiate from sibling tools, as no other tools appear to control LEDs, so it's not misleading but lacks explicit distinction.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives or in what context. It simply states what the tool does without mentioning prerequisites, timing, or related tools like 'set_temperature' or 'printer_set_speed' that might be used in similar printer control scenarios.

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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