AF print-failure-analyst
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".
As a process F 49/100 · Will not run — References files that are not bundled: assets/failure-log.json
How to improve
- The text references files that are not there: add them or drop the references.
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 9. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: Diagnose 3D printing failures and recommend slicer setting fixes. … ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value - warning
missing-refreference to a missing file: assets/failure-log.json
Process rating: all ten parameters 49/100
- 0Tools and files. 1 referenced file(s) missing: assets/failure-log.json
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 55Failures and branches. 1 branches
- 70When it triggers. States when to use, but not when not to
- 100Steps. 18 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 913 tokens
- 100Running it twice. No mutating operations
- 100Progress reporting. Reports progress
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +5Description quotes 7 example trigger phrases
- +3Description length 602: enough signal without eating the budget
- +4Structure: 13 headings
- +3Step-by-step instructions: 18 items
- +4Has examples (4 code blocks)
- +4Reference files are cited in the instructions (2 of 2)
- +3All 4 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.