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πŸ¦€ ClawHub

Print Failure Analyst

by @newageinvestments25-byte

Diagnose 3D print failures from symptoms or images, recommend slicer setting fixes, and log or analyze recurring print problems.

Versionv1.0.0
Downloads326
TERMINAL
clawhub install print-failure-analyst

πŸ“– About This Skill


name: print-failure-analyst description: Diagnose 3D printing failures and recommend slicer setting fixes. Maintains a personal failure log to track recurring problems. Use when: user says "print failed", "3d print problem", "why did my print fail", "print diagnosis", or mentions stringing, warping, layer adhesion, delamination, under extrusion, over extrusion, elephant foot, layer shifting, bridging, pillowing, ringing, ghosting, z-banding, clogged nozzle, wet filament, first layer issues, seam visibility, or asks about slicer settings for a specific failure. Also triggers on "log a failure", "failure history", "print failure report".

Print Failure Analyst

Diagnose failures, recommend slicer fixes, and track a personal failure log.

References

  • references/failure-types.md β€” 18 failure types with keywords, causes, visual symptoms
  • references/slicer-fixes.md β€” Specific values for PrusaSlicer, Cura, OrcaSlicer per failure type
  • Read these when formulating diagnoses or recommending fixes. Do not recite them wholesale β€” extract relevant sections.

    Scripts

    All scripts use Python stdlib only. Log stored at assets/failure-log.json.

    diagnose.py β€” Identify failure mode from symptoms

    python3 scripts/diagnose.py --symptoms "stringing,warping"
    python3 scripts/diagnose.py --description "hair between parts and corners lifting"
    python3 scripts/diagnose.py --symptoms "stringing" --description "worse at layer transitions" --json
    

    Outputs: ranked failure types with confidence, causes, and slicer-specific fixes. Use --json when you need structured output to reason over.

    log_failure.py β€” Record a print failure

    python3 scripts/log_failure.py \
      --printer "Prusa MK4" \
      --material "PETG" \
      --failure-type "stringing" \
      --description "Heavy stringing between towers" \
      --slicer-settings '{"temperature": 235, "retraction_distance_mm": 1.0}' \
      --fixed-by "Reduced temp to 230C, enabled wipe" \
      --notes "Filament may be wet"
    

    Valid --failure-type values: stringing, warping, layer_adhesion, under_extrusion, over_extrusion, elephant_foot, layer_shifting, bridging, overhang, clog, pillowing, ringing, z_banding, seam, supports, first_layer, wet_filament, spaghetti, other

    history.py β€” View failure history and patterns

    python3 scripts/history.py                          # All failures
    python3 scripts/history.py --last 10               # Last 10
    python3 scripts/history.py --material PETG         # Filter by material
    python3 scripts/history.py --printer "Prusa MK4"  # Filter by printer
    python3 scripts/history.py --failure-type stringing
    python3 scripts/history.py --patterns              # Pattern analysis only
    

    report.py β€” Generate markdown report

    python3 scripts/report.py                  # Print to stdout
    python3 scripts/report.py --output r.md   # Save to file
    python3 scripts/report.py --days 30       # Last 30 days only
    

    Workflow

    User describes a failure

    1. Run diagnose.py --symptoms or --description with the user's input 2. Read references/failure-types.md for the top match to get full context 3. Read references/slicer-fixes.md for that failure type to get specific values 4. Present: most likely failure type, top 2–3 causes, and slicer fixes (ask which slicer if unknown) 5. Offer to log the failure with log_failure.py

    User provides an image

    1. Analyze the image to identify visual symptoms (stringing, warping, layer gaps, etc.) 2. Map observed symptoms to failure type keywords from references/failure-types.md 3. Run diagnose.py --symptoms "" for structured output 4. Present diagnosis with causes and fixes

    User asks to log a failure

  • Collect: printer, material, failure type, description. Ask for missing required fields.
  • Optional: slicer settings used, what fixed it, notes
  • Run log_failure.py with collected info
  • User asks for history or patterns

  • Run history.py with appropriate filters
  • Highlight any patterns flagged (recurring type+material combos, worst printer/material)
  • User asks for a report

  • Run report.py, optionally with --days if user wants a time-bounded view
  • Present the markdown output or save it and tell user where it is