Review our entire conversation from the beginning. Your goal is to distill a reusable learned skill that captures the workflow pattern, failure modes, and key corrections. Analyze the following aspects: 1. **Workflow Pattern**: What tools were used and in what sequence? What was the overall approach?2. **Failure Modes**: Where did things go wrong? What errors occurred? How were they recovered from?3. **User Corrections**: Where did the user steer the approach differently? What did they correct or improve?4. **Key Parameters**: What specific configurations, thresholds, or settings were important?5. **Reproducibility**: What would someone need to know to reproduce this workflow on a similar problem? Then call the `learn` tool with:- `name`: A descriptive kebab-case identifier (e.g., "debug-cuda-memory-leak", "deploy-vercel-prebuilt")- `description`: A one-line summary of what this skill teaches- `content`: A complete SKILL.md with this structure: ```---name: {name}description: {description}source: rsimetadata:    skill-author: /learn command--- # {name} ## Overview[What this skill covers and when to use it] ## Workflow Pattern[Numbered steps with tool names and key actions] ## Failure Modes & Recovery[What went wrong and how it was fixed — the most valuable part] ## User Corrections[Where the user steered the approach — captures human judgment] ## Key Parameters[Important configurations, thresholds, file paths] ## When to Use[Trigger conditions — what kind of problem/question matches this skill]``` $ARGUMENTS