reflow_machine_maintenance_guidance

This skill should be considered when you need to answer reflow machine maintenance questions or provide detailed guidance based on thermocouple data, MES dat...

This skill appears to be what it says (reflow metrics and guidance) but has two practical gaps you should address before installing: (1) It references DATA_DIR and reads MES/thermocouple CSVs but does not declare where those files live or how access is granted — verify and restrict which directories the agent may read to avoid accidental exposure of sensitive MES/manufacturing data. (2) The examples use Python libraries (pandas) but the skill doesn't declare dependencies; decide if the agent environment should provide these libraries, or add an install spec. Recommended actions: supply explicit paths or environment variables for handbook and dataset locations; limit file-system permissions for the agent; confirm a trusted source for the handbook; consider adding a declared dependency list (and a vetted install method) and, if concerned about autonomous runs, restrict user-invocable/autonomous invocation or monitor logs for unexpected file access.

Type: OpenClaw Skill Name: reflow-machine-maintenance-guidance Version: 0.1.0 The skill bundle provides legitimate guidance and reference Python code for analyzing industrial reflow machine maintenance data. The code in SKILL.md uses standard data processing libraries (pandas, numpy) to calculate manufacturing metrics such as ramp rates and time-above-liquidus (TAL) from CSV datasets (mes_log.csv, thermocouples.csv). No indicators of data exfiltration, malicious execution, or harmful prompt injection were found.