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Kiln

Kiln

by codeofaxel
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python

get_print_diagnostic

Read-only

Diagnose 3D print quality problems by cross-referencing material, symptom, and printer data to return root causes, fixes, and storage tips in one actionable response.

Instructions

Get a comprehensive print diagnostic combining multiple knowledge sources.

        This is the PRIMARY tool for debugging print problems.  Combines
        troubleshooting data (symptom matching, root causes, fixes),
        printer compatibility (upgrade requirements, known issues),
        storage requirements (drying temps, humidity limits), and
        post-processing tips (strengthening options) into a single
        actionable response.

        Call this FIRST when a user reports any print quality problem.
        It cross-references all knowledge sources so the agent doesn't
        need to make multiple tool calls.

        Examples:
            material="petg", symptom="stringing", printer="ender3"
            material="abs", symptom="warping", printer="bambu_a1"
            material="nylon", symptom="brittle"

        Args:
            material: Material being printed (e.g. "pla", "petg").
            symptom: What's going wrong (e.g. "stringing", "warping",
                "poor adhesion", "clog", "brittle").
            printer: Optional printer model for compatibility context
                (e.g. "ender3", "bambu_x1c").

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": {
      "material": "<material>",
      "symptom": "<symptom>"
    },
    "name": "get_print_diagnostic"
  }
}

Input Schema

NameRequiredDescriptionDefault
printerNoOptional printer model for compatibility context (e.g. "ender3", "bambu_x1c").
symptomYesWhat's going wrong (e.g. "stringing", "warping", "poor adhesion", "clog", "brittle").
materialYesMaterial being printed (e.g. "pla", "petg").

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv1.5.1
    • addedInput schema / properties / material / description
      Added value: +"Material being printed (e.g. \"pla\", \"petg\")."
    • addedInput schema / properties / printer / description
      Added value: +"Optional printer model for compatibility context (e.g. \"ender3\", \"bambu_x1c\")."
    • addedInput schema / properties / symptom / description
      Added value: +"What's going wrong (e.g. \"stringing\", \"warping\", \"poor adhesion\", \"clog\", \"brittle\")."
  2. Changed1 schema field changedv1.5.0
    • removedInput schema / properties / printer / default
      Removed value: -null
  3. Changed4 schema fields changedv1.3.0
    • removedInput schema / properties / symptom / anyOf
      Removed value: -[
-  {
-    "type": "string"
-  },
-  {
-    "type": "null"
-  }
-]
    • removedInput schema / properties / symptom / default
      Removed value: -null
    • addedInput schema / properties / symptom / type
      Added value: +"string"
    • changedInput schema / required
      Previous value: -[
-  "material"
-]New value: +[
+  "material",
+  "symptom"
+]
  4. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnly, non-destructive, and closed-world, so safety is covered. The description adds what the call actually returns — a single cross-referenced response spanning four knowledge sources — which is meaningful behavior beyond the annotations. It does not mention response size, latency, or what happens when a symptom/material pairing is unknown, leaving a small gap.

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?

Front-loaded with the purpose and the 'call first' directive before supporting detail, which is the right ordering. It loses a point for the Args block duplicating schema descriptions verbatim and for slightly padded phrasing ('so the agent doesn't need to make multiple tool calls').

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?

With no output schema, the description carries the burden of explaining the return value and does so at a useful level of abstraction (four aggregated knowledge domains, actionable form). What it lacks is any hint of failure behavior or fallback for unrecognized symptoms/materials, which matters for a diagnostic lookup tool.

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?

Schema coverage is 100%, so the Args section merely restates the schema at baseline. The value-add comes from the worked examples, which demonstrate realistic material/symptom/printer pairings and show that printer is optional and safely omitted (the nylon/brittle example). That is useful meaning beyond the raw type declarations.

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?

States a specific verb and resource ('print diagnostic') and enumerates exactly what it aggregates: troubleshooting data, printer compatibility, storage requirements, and post-processing tips. It also explicitly positions itself against siblings such as troubleshoot_print_issue or diagnose_print_failure_live by declaring itself 'the PRIMARY tool for debugging print problems.'

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?

Gives an unambiguous trigger ('Call this FIRST when a user reports any print quality problem') plus the rationale that it prevents multiple tool calls. The concrete example invocations show which parameter combinations are valid, so an agent knows exactly when and how to reach for it.

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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