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Kiln

Kiln

by codeofaxel
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python

analyze_print_failure_smart

Classify a 3D print failure and generate an actionable recovery plan using error messages, print progress, and failure history; optional nozzle-wear hypothesis when available.

Instructions

Classify a print failure and suggest recovery steps.

        Uses heuristics based on error messages, print progress, and
        failure history to classify the failure type and generate an
        actionable recovery plan.

        With kiln-pro installed the answer can also carry
        ``nozzle_wear_hypothesis``: whether the printer's nozzle wear
        likely contributed.  That check is Kiln Pro; below it, a failure wear could
        explain carries ``nozzle_wear_hypothesis_gated`` saying so once.

        Args:
            progress: Print progress at failure (0.0 - 1.0).
            error_message: Error message from the printer or system.
            printer_name: Name of the printer that failed.
            job_id: Job ID of the failed print.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "analyze_print_failure_smart"
  }
}

Input Schema

NameRequiredDescriptionDefault
job_idNoJob ID of the failed print.
progressNoPrint progress at failure (0.0 - 1.0). Default: 0.0.
printer_nameNoName of the printer that failed.
error_messageNoError message from the printer or system.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changedv1.5.1
    • addedInput schema / properties / error_message / description
      Added value: +"Error message from the printer or system."
    • addedInput schema / properties / job_id / description
      Added value: +"Job ID of the failed print."
    • addedInput schema / properties / printer_name / description
      Added value: +"Name of the printer that failed."
    • changedInput schema / properties / progress / description
      Previous value: -"Default: 0.0."New value: +"Print progress at failure (0.0 - 1.0). Default: 0.0."
  2. Changed5 schema fields changedv1.5.0
    • removedInput schema / properties / error_message / default
      Removed value: -null
    • removedInput schema / properties / job_id / default
      Removed value: -null
    • removedInput schema / properties / printer_name / default
      Removed value: -null
    • removedInput schema / properties / progress / default
      Removed value: -0
    • addedInput schema / properties / progress / description
      Added value: +"Default: 0.0."
  3. First observedv0.1.0

TDQS

B3.1/5.0
Behavior3/5

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

The description adds real value beyond the annotations by disclosing that classification is heuristic and that the nozzle-wear hypothesis is a kiln-pro-gated extra that degrades to a gated marker. It does not explain why the tool is declared non-read-only (annotations show readOnlyHint=false) — e.g. whether it persists the classification to failure history — which is the one behavior an agent most needs to know.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The opening sentence is well front-loaded, but the Args block is pure duplication of the schema and the kiln-pro paragraph is garbled ("below it, a failure wear could explain carries ... saying so once"), which costs comprehension for no informational gain.

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 no output schema, the description should characterize the returned classification and recovery plan; it only names one optional field (nozzle_wear_hypothesis). It is adequate to call the tool but leaves the result shape and the significance of omitted optional params largely unspecified.

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%, and the description's Args block simply restates the four schema descriptions verbatim (progress range, error message, printer name, job id). No added meaning such as whether a missing error_message degrades the heuristic quality, so the baseline 3 applies.

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 gives a specific verb+resource pair: "Classify a print failure and suggest recovery steps," plus the heuristic inputs used. However, it never explains the "_smart" qualifier or how this differs from the many sibling failure tools (analyze_print_failure, diagnose_print_failure_live, predict_print_failure_risk), so an agent cannot disambiguate from the name alone.

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

Usage Guidelines2/5

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

There is no when-to-use or when-not-to-use guidance. Given a crowded sibling set of failure/diagnosis/recovery tools, the description should state that this is for post-failure classification versus live diagnosis or risk prediction, but it offers only an implied "after a failure" context.

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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