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Polar3D

Polar Cloud MCP

Official
by Polar3D

slice_and_queue

Slice a 3D model using Polar Cloud defaults and add it to your printer queue. Does not start the print. For multiple printers, include the serial number.

Instructions

Slice an object with Polar Cloud defaults (0.4 nozzle, 0.20mm, PLA) and add it to a personal printer queue. Does not start the print. If the user has multiple printers, pass serial_number.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
brimNo
nameNo
infillNoInfill percent, e.g. 15
supportNo
object_idYesPolar Cloud object id from generate_model or upload_model
layer_heightNo
tree_supportNo
serial_numberNoRequired when the account has more than one printer
Behavior4/5

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

With no annotations provided, the description bears full responsibility for behavioral disclosure. It clearly states the tool uses defaults (0.4 nozzle, 0.20mm, PLA), does not start the print, and requires serial_number for multi-printer accounts. It could be improved by noting if any parameters are required beyond object_id, but overall provides strong transparency.

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 two sentences with no wasted words. It front-loads the core action and defaults, then adds the critical note about not starting the print, then the multi-printer guidance. Every sentence earns its place.

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

Completeness4/5

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

Given 8 parameters (38% schema coverage, no output schema), the description is fairly complete. It explains the overall action, defaults, and key behavioral constraint. A small gap is that it does not mention what the tool returns (e.g., confirmation or queue item ID) since no output schema exists, but the agent might infer from context. Overall, it is sufficient for an agent to select and use correctly.

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 description coverage is 38%, so the description must compensate. The description itself does not explain individual parameters beyond noting serial_number is needed for multiple printers. However, it sets context for default slicing behavior, which helps an agent infer that infill, layer_height, etc. are optional overrides. The schema already has good descriptions for object_id, infill, support, and serial_number, so the baseline is 3.

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 slices an object with Polar Cloud defaults and adds it to a personal printer queue. It specifies the default settings (0.4 nozzle, 0.20mm, PLA) and distinguishes from sibling tools like 'preview_plate' or 'approve_and_queue' by noting it does not start the print.

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?

The description explicitly says the tool adds to a queue but does not start the print, and instructs the user to pass 'serial_number' when the user has multiple printers. This provides clear when-to-use and when-to-include guidance, distinguishing it from approval tools like 'approve_and_queue'.

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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