Refactored the vision system to separate concerns: - vision.md remains the stable "north star" philosophy document - Gitea milestones now track goals with automatic progress via issue counts - Updated /vision, /retro, and /create-issue commands to auto-assign milestones 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
93 lines
2.9 KiB
Markdown
93 lines
2.9 KiB
Markdown
---
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description: Run a retrospective on completed work. Captures learnings, creates improvement issues, and updates product vision.
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argument-hint: [task-description]
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---
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# Retrospective
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Capture learnings from completed AI-assisted work to improve the workflow and refine the product vision.
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@~/.claude/skills/vision-management/SKILL.md
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## Process
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1. **Gather context**: If $1 is provided, use it as the task description. Otherwise, ask the user what task was just completed.
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2. **Reflect on the work**: Ask the user (or summarize from conversation context if obvious):
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- What friction points were encountered?
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- What worked well?
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- Any specific improvement ideas?
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3. **Analyze and categorize**: Group learnings into:
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- **Prompt improvements**: Better instructions for commands/skills
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- **Missing capabilities**: New commands or skills needed
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- **Tool issues**: Problems with tea CLI, git, or other tools
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- **Context gaps**: Missing documentation or skills
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4. **Connect to vision** (if `vision.md` exists in the target repo):
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- Did this work make progress on any vision goals?
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- Did learnings reveal new priorities that should become goals?
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- Did we discover something that should be a non-goal?
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- Should the current focus shift based on what we learned?
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If any vision updates are needed:
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- Present suggested changes to `vision.md`
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- Ask for approval
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- Update the vision file and sync to Gitea
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5. **Generate improvement issues**: For each actionable improvement:
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- Determine the appropriate milestone (see Milestone Categorization below)
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- Create an issue in the AI repo with the milestone assigned:
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```bash
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tea issues create -r flowmade-one/ai --title "<title>" --description "<body>" --milestone "<milestone>"
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```
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## Milestone Assignment
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Before creating issues, fetch available milestones:
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```bash
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tea milestones -f title,description
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```
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For each issue, automatically assign to the most relevant milestone by matching:
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- Issue content/problem area → Milestone title and description
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- If no clear match, ask the user which milestone (goal) the issue supports
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- If no milestones exist, skip milestone assignment
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## Issue Format
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Use this structure for retrospective issues:
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```markdown
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## Context
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What task triggered this learning (brief).
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## Problem / Observation
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What was the friction point or insight.
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## Suggested Improvement
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Concrete, actionable change to make.
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## Affected Files
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- commands/xxx.md
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- skills/xxx/SKILL.md
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```
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## Labels
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Add appropriate labels:
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- `retrospective` - Always add this
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- `prompt-improvement` - For command/skill text changes
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- `new-feature` - For new commands/skills
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- `bug` - For things that are broken
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## Guidelines
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- Be specific and actionable - vague issues won't get fixed
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- One issue per improvement (don't bundle unrelated things)
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- Reference specific commands/skills when relevant
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- Keep issues small and focused
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- Skip creating issues for one-off edge cases that won't recur
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