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Kiln

Kiln

by codeofaxel
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python

get_print_confidence

Read-only

Score print success likelihood from printer history and material, optionally across your fleet, and include pipeline validation results for checked parts.

Instructions

Predict how likely a print will succeed based on your print history.

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_print_confidence"
  }
}

Input Schema

NameRequiredDescriptionDefault
materialYesFilament material (e.g. "PLA", "PETG", "ABS").
fleet_modeNoTrue to score against every printer in your fleet instead of this one printer's history. Default: false.
printer_idYesThe printer identifier (e.g. serial number or name).
pipeline_result_jsonNoJSON string of ValidationPipelineResult.to_dict() from the free pipeline (the ``result`` that ``validate_and_prepare_mesh`` returns). Pass "{}" if not available: the confidence then rests on the print history alone and says the part was not checked. Default: "{}".

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changedv1.5.1
    • changedInput schema / properties / fleet_mode / description
      Previous value: -"Default: false."New value: +"True to score against every printer in your fleet instead of this one printer's history. Default: false."
    • addedInput schema / properties / material / description
      Added value: +"Filament material (e.g. \"PLA\", \"PETG\", \"ABS\")."
    • changedInput schema / properties / pipeline_result_json / description
      Previous value: -"Default: \"{}\"."New value: +"JSON string of ValidationPipelineResult.to_dict() from the free pipeline (the ``result`` that ``validate_and_prepare_mesh`` returns). Pass \"{}\" if not available: the confidence then rests on the print history alone and says the part was not checked. Default: \"{}\"."
    • addedInput schema / properties / printer_id / description
      Added value: +"The printer identifier (e.g. serial number or name)."
  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, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds a real behavioral constraint, the Kiln Pro requirement, but says nothing about what the prediction returns, how it is computed, or what happens when history is sparse.

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 with the core purpose front-loaded and no wasted wording. 'Needs Kiln Pro' is terse to the point of being slightly cryptic, but it earns its place as a gating condition.

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?

With four parameters and no output schema, the description should at least indicate what the confidence result looks like, since nothing else describes the return value. The prerequisite is covered, but the output shape and behavior on missing history are left unaddressed.

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 all four parameters, including fleet_mode and pipeline_result_json, are already documented in the schema. The description adds no meaning beyond that, which is the expected baseline when the schema does the work.

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 states a specific verb and resource: predict the likelihood a print will succeed, scoped to the user's print history. It is clear on its own, but it does not distinguish itself from nearby siblings such as predict_print_failure, predict_print_failure_risk, or get_print_learning_summary, so an agent must infer the difference.

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?

'Based on your print history' implies the data source, and 'Needs Kiln Pro' gives a prerequisite, but there is no explicit when-to-use or when-not-to-use guidance and no named alternative for related prediction tools. Usage is only implied.

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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