--- description: Run a retrospective on completed work. Captures learnings and creates improvement issues in the AI repo. argument-hint: [task-description] --- # Retrospective Capture learnings from completed AI-assisted work to improve the workflow. ## Process 1. **Gather context**: If $1 is provided, use it as the task description. Otherwise, ask the user what task was just completed. 2. **Reflect on the work**: Ask the user (or summarize from conversation context if obvious): - What friction points were encountered? - What worked well? - Any specific improvement ideas? 3. **Analyze and categorize**: Group learnings into: - **Prompt improvements**: Better instructions for commands/skills - **Missing capabilities**: New commands or skills needed - **Tool issues**: Problems with tea CLI, git, or other tools - **Context gaps**: Missing documentation or skills 4. **Generate improvement issues**: For each actionable improvement, create an issue in the AI repo using: ```bash tea issues create -r flowmade-one/ai --title "" --description "<body>" ``` ## Issue Format Use this structure for retrospective issues: ```markdown ## Context What task triggered this learning (brief). ## Problem / Observation What was the friction point or insight. ## Suggested Improvement Concrete, actionable change to make. ## Affected Files - commands/xxx.md - skills/xxx/SKILL.md ``` ## Labels Add appropriate labels: - `retrospective` - Always add this - `prompt-improvement` - For command/skill text changes - `new-feature` - For new commands/skills - `bug` - For things that are broken ## Guidelines - Be specific and actionable - vague issues won't get fixed - One issue per improvement (don't bundle unrelated things) - Reference specific commands/skills when relevant - Keep issues small and focused - Skip creating issues for one-off edge cases that won't recur