Back to Prompt Library
planning
Data Ingestion and Preprocessing Setup
Inspect the original prompt language first, then copy or adapt it once you know how it fits your workflow.
Linked challenge: Predictive Anomaly Detection for BESS Thermal Runaway with AI-Driven Context
Format
Text-first
Lines
1
Sections
1
Linked challenge
Predictive Anomaly Detection for BESS Thermal Runaway with AI-Driven Context
Prompt source
Original prompt text with formatting preserved for inspection.
1 lines
1 sections
No variables
0 checklist items
Set up a simulated BESS telemetry data stream (e.g., Python script generating JSON payloads) for 100 cells across 10 modules. Implement a data ingestion pipeline that processes this stream, performs necessary feature engineering (e.g., moving averages, rate of change), and prepares it for time-series modeling. Document your data schema and preprocessing steps.
Adaptation plan
Keep the source stable, then change the prompt in a predictable order so the next run is easier to evaluate.
Keep stable
Preserve the role framing, objective, and reporting structure so comparison runs stay coherent.
Tune next
Swap in your own domain constraints, anomaly thresholds, and examples before you branch variants.
Verify after
Check whether the prompt asks for the right evidence, confidence signal, and escalation path.