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MaxEllis

orcaslicer-mcp

by MaxEllis

Diagnose plate issues

diagnose_plate
Read-only

Diagnose why a model won't slice or fit: returns app/slice status, plate objects, bed and skirt/brim settings, and last slice warnings in one call.

Instructions

One-call plate diagnosis: app/slice status, objects on the plate, bed + active skirt/brim/clearance settings, and the last slice's warnings - so you don't have to chain status->objects->config. Start here for 'why won't this slice / fit'.

Slice warnings are only as complete as the fork exposes today (see get_slice_warnings). For a 'does it fit the bed' estimate, pair with check_placement.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

Annotations already declare readOnlyHint=true, and description adds meaningful context: that it aggregates multiple data sources, that slice warnings are only as complete as the fork exposes, and that it's a starting point. This goes beyond the annotation by explaining the tool's synthetic nature and caveats.

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?

Two sentences, front-loaded with the main purpose, and the second sentence adds important caveats and pairing advice. No wasted words or repetition of schema/annotation info.

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 zero parameters and no output schema, the description is the primary source of semantic info. It lists the key categories (app/slice status, objects, bed settings, warnings), notes the limitations of warnings, and points to complementary tools. This is complete enough for an agent to understand the tool's behavior and decide when to invoke it.

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

Parameters4/5

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

The tool has zero parameters, so baseline is 4. The description does not need to explain parameters; instead it compensates by explaining the tool's scope and what it checks, enriching the agent's understanding despite the absence of inputs.

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 uses a specific verb ('diagnose') and resource ('plate'), and enumerates exactly what it covers (status, objects, bed settings, warnings). It distinguishes itself from sibling tools by positioning as a one-call aggregation that avoids chaining status->objects->config.

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?

Explicitly provides when to use ('Start here for why won't this slice / fit'), and names alternatives/partners: 'see get_slice_warnings' for completeness and 'pair with check_placement' for bed fit. This is clear guidance on usage vs. alternatives.

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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