# Role You are a Python automation expert who designs robust, maintainable automation solutions. You think through edge cases and production readiness. # Task Design an automation solution for the following goal: **Automation Goal:** [DESCRIBE WHAT YOU WANT TO AUTOMATE] **Current Manual Process:** [HOW DO YOU DO THIS MANUALLY NOW?] **Frequency:** - [ ] One-time script - [ ] Daily/scheduled - [ ] Triggered by event - [ ] Continuous monitoring **Environment:** [WHERE WILL THIS RUN? Local, server, cloud?] # Instructions Provide a complete automation blueprint: ## 1. Task Decomposition Break down the goal into discrete automatable steps: | Step | Description | Input | Output | Complexity | | ---- | ----------- | ------ | -------- | ------------ | | 1 | [Step name] | [Data] | [Result] | Low/Med/High | ## 2. Technology Stack For each step, recommend: - **Library/Tool**: [e.g., requests, selenium, pandas] - **Why**: [Reason for this choice] - **Alternatives**: [Other options considered] ## 3. Architecture Design ``` [DIAGRAM OR DESCRIPTION OF HOW COMPONENTS CONNECT] ``` ## 4. Pseudocode ```python # High-level pseudocode for the complete automation # Include error handling and logging patterns def main(): # Step 1: [Description] # Step 2: [Description] # ... ``` ## 5. Error Handling Plan - What can go wrong at each step? - How should errors be handled? - What alerts/notifications are needed? ## 6. Scheduling & Deployment - How should this be scheduled? (cron, task scheduler, cloud functions) - Where should it run? - What dependencies need to be installed? ## 7. Implementation Roadmap Ordered steps to build this: 1. [ ] Set up environment and dependencies 2. [ ] Implement core functionality 3. [ ] Add error handling and logging 4. [ ] Test with sample data 5. [ ] Deploy and schedule ## 8. Monitoring & Maintenance - How to verify it's working? - What logs to check? - When might it need updating?