Print Failure Analystv1.0.0

A hobbyist messages that their print has "hair between parts and corners lifting." The skill runs diagnose.py with the description, then reads failure-types.md and slicer-fixes.md to present the most likely failure type with top causes and slicer-specific fixes. It offers to log the failure for future pattern tracking.

A user uploads a photo of a failed print showing visible stringing and warping. The skill maps observed visual symptoms to failure keywords, runs diagnose.py --symptoms for structured output, and returns a ranked diagnosis with actionable slicer settings.

A maker wants to track failures over time. The skill collects printer, material, failure type, description, and optional slicer settings, then runs log_failure.py to store the entry in assets/failure-log.json. Over time this builds a searchable personal database for troubleshooting.

After weeks of logging, a user asks for history or patterns. The skill runs history.py with filters such as --material PETG or --patterns to highlight recurring failure type plus material combinations and worst-performing printers. This helps users adjust workflows, drying routines, or slicer profiles.

A small print farm operator requests a report of recent failures. The skill runs report.py --days 30 to generate a markdown summary, optionally saving it to a file. The report provides a time-bounded view of failure trends for process improvement or client communication.

The core diagnostic and logging features are free for hobbyists, while advanced pattern analysis, unlimited history, and markdown reports require a paid subscription. This drives adoption through useful free tools and monetizes power users who print frequently.

3D printing farms and service bureaus pay for a team license that aggregates failure logs across printers and materials. The skill's history and report scripts feed into dashboards that identify systemic issues, reducing downtime and material waste.

Printer manufacturers and filament brands integrate the skill into their support portals or companion apps. Customers get instant diagnosis and fixes, reducing support tickets, while the vendor gains usage analytics and upsell opportunities for materials and accessories.