Skip to main content
Glama
Sign In
Kiln

Kiln

by codeofaxel
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python

get_optimal_settings

Read-only

Predicts effective 3D print settings based on historical success for a given printer, material, and optional geometry type to reduce failed prints.

Instructions

Predict the best print settings based on historical success.

Needs Kiln Pro.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "printer_id": "<printer_id>",
      "material": "<material>"
    },
    "name": "get_optimal_settings"
  }
}

Input Schema

NameRequiredDescriptionDefault
materialYesFilament material (e.g. "PLA", "PETG", "ABS").
printer_idYesThe printer identifier.
geometry_typeNoOptional geometry type (e.g. "organic", "mechanical"). Default: "".

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv1.5.1
    • changedInput schema / properties / geometry_type / description
      Previous value: -"Default: \"\"."New value: +"Optional geometry type (e.g. \"organic\", \"mechanical\"). Default: \"\"."
    • addedInput schema / properties / material / description
      Added value: +"Filament material (e.g. \"PLA\", \"PETG\", \"ABS\")."
    • addedInput schema / properties / printer_id / description
      Added value: +"The printer identifier."
  2. Addedv1.5.0

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds two pieces beyond them: the prediction is grounded in historical success data, and it requires a Kiln Pro entitlement. It says nothing about what happens for insufficient history or how confident/limited the output is.

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?

Two short sentences, front-loaded with the purpose and followed by the hard prerequisite. No filler; the only weakness is the missing differentiation that would make the brevity safe.

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?

A read-only, three-parameter prediction tool with full schema coverage and no output schema is nearly covered by the given text, and the Kiln Pro gate is stated. It still leaves the agent unsure what comes back (a settings bundle?) and how it differs from sibling predictors, which matters given the crowded namespace.

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 100%, so printer_id, material, and geometry_type are already documented with examples. The description adds no extra meaning about how material/printer combinations interact or whether geometry_type materially changes the prediction, leaving it at the baseline.

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?

States a specific verb+resource ('Predict the best print settings') with the basis ('based on historical success'). It does not distinguish itself from near-identical siblings such as predict_print_settings, recommend_settings, infer_print_settings, or get_auto_tuned_settings, so an agent cannot tell from the text which predictor to pick.

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

Usage Guidelines3/5

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

The prerequisite 'Needs Kiln Pro' is a genuinely useful gating condition that steers away from calling it on a free tier. However, there is no guidance on when to use this over the many sibling settings-prediction/recommendation tools, which is the main ambiguity an agent faces here.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server

Other Tools