Print Failure Analyst
v1.0.0Diagnose 3D print failures from symptoms or images, recommend slicer setting fixes, and log or analyze recurring print problems.
⭐ 0· 49·0 current·0 all-time
byNew Age Investments@newageinvestments25-byte·duplicate of @newageinvestments25-byte/nai-print-failure-analyst
MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Benign
high confidencePurpose & Capability
Name/description match the included code and references. The scripts implement symptom-based diagnosis, logging, history/pattern detection, and markdown reports. Required capabilities (none) are proportional to the stated purpose.
Instruction Scope
SKILL.md instructs the agent to 'analyze the image' when a user provides an image, but none of the bundled scripts perform image analysis — diagnosis scripts accept textual symptoms/descriptions only. This is a mild mismatch: image-based diagnosis is possible only if the agent (or another tool) interprets the image and converts visual findings into symptom keywords before calling diagnose.py.
Install Mechanism
No install spec is provided (instruction-only + included Python scripts). All scripts declare they use only the Python stdlib. No external downloads, package installs, or archive extraction are present.
Credentials
The skill requests no environment variables, no credentials, and no config paths other than its own assets/failure-log.json. That local log file is the only persistent data it reads/writes — proportional to the logging/reporting purpose.
Persistence & Privilege
always is false and the skill does not require persistent platform-level privileges. It writes a local JSON log at assets/failure-log.json within the skill directory and does not modify other skills or system-wide settings.
Assessment
This skill appears to be what it claims: text-based diagnosis, slicer-setting recommendations, and a local failure log. Before installing/using it: (1) note that it will create and update assets/failure-log.json inside the skill directory — back up or review that file if you care about its contents; (2) it does not perform image analysis itself — if you expect automatic image-to-diagnosis, your agent must convert images into symptom keywords before invoking the scripts; (3) no network calls or secrets are requested, but review the included Python files if you want to confirm there's no unexpected behavior; (4) ensure you run the scripts in a trusted environment with Python available and that you are comfortable allowing the skill to write a local JSON file.Like a lobster shell, security has layers — review code before you run it.
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License
MIT-0
Free to use, modify, and redistribute. No attribution required.