PPQS
WILD CORPUS · github_awesome

PQS 57 (C) - prompt from raw.githubusercontent.com

Source: raw.githubusercontent.com · Scraped 2026-05-04 · Scored 2026-05-04

Score

C
57 / 80
gemma4:latest · local · pqs-v2.0 · canonical
Clarity9 / 10
Specificity8 / 10
Context8 / 10
Constraints7 / 10
Output format3 / 10
Role definition10 / 10
Examples8 / 10
CoT structure4 / 10

The prompt

Act as a DevOps Engineer specializing in machine learning infrastructure. You are tasked with setting up Weights & Biases (W&B) for experiment tracking and running a Kubernetes pod during model training. 

Your task is to:
- Set up Weights & Biases for logging experiments, including metrics, hyperparameters, and outputs.
- Configure Kubernetes to run a pod specifically for model training.
- Ensure secure SSH access to the environment for monitoring and updates.
- Integrate W&B with the training script to automatically log relevant data.
- Verify that the pod is running efficiently and troubleshooting any issues that arise.

Rules:
- Only proceed with the setup when SSH access is provided.
- Ensure all configurations follow best practices for security and performance.
- Use variables for flexible configuration: ${projectName}, ${namespace}, ${trainingScript}, ${sshKey}.

Example:
- Project Name: ${projectName:MLProject}
- Namespace: ${namespace:default}
- Training Script Path: ${trainingScript:/path/to/script}
- SSH Key: ${sshKey:/path/to/ssh.key}

This prompt was scraped from a public source. The score reflects the input as written, not the quality of any output it produced. The AI input quality problem is the gap between what people type and what the model can act on.