try to restructure the agents and skills given the new skills and command merge
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old/skills/retro/SKILL.md
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---
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name: retro
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description: >
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Run a retrospective on completed work. Captures insights as issues for later
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encoding into skills/agents. Use when capturing learnings, running retrospectives,
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or when user says /retro.
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model: haiku
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argument-hint: [task-description]
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user-invocable: true
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---
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# Retrospective
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Capture insights from completed work as issues on the architecture repo. Issues are later encoded into learnings and skills/agents.
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@~/.claude/skills/vision-management/SKILL.md
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@~/.claude/skills/gitea/SKILL.md
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## Flow
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```
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Retro (any repo) → Issue (architecture repo) → Encode: learning file + skill/agent
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```
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The retro creates the issue. Encoding happens when the issue is worked on.
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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. **Identify insights**: For each insight, determine:
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- **What was learned**: The specific insight
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- **Where to encode it**: Which skill or agent should change?
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- **Governance impact**: What does this mean for how we work?
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4. **Create issue on architecture repo**: Always create issues on `flowmade-one/architecture`:
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```bash
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tea issues create -r flowmade-one/architecture \
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--title "[Learning] <brief description>" \
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--description "## Context
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[Task that triggered this insight]
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## Insight
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[The specific learning - be concrete and actionable]
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## Suggested Encoding
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- [ ] \`skills/xxx/SKILL.md\` - [what to add/change]
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- [ ] \`agents/xxx/agent.md\` - [what to add/change]
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## Governance
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[What this means for how we work going forward]"
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```
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5. **Connect to vision**: Check if insight affects vision:
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- **Architecture repo**: Does this affect `manifesto.md`? (beliefs, principles, non-goals)
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- **Product repo**: Does this affect `vision.md`? (product direction, goals)
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If vision updates are needed, present suggested changes and ask for approval.
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## When the Issue is Worked On
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When encoding a learning issue, the implementer should:
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1. **Create learning file**: `learnings/YYYY-MM-DD-short-title.md`
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```markdown
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# [Learning Title]
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**Date**: YYYY-MM-DD
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**Context**: [Task that triggered this learning]
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**Issue**: #XX
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## Learning
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[The specific insight]
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## Encoded In
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- `skills/xxx/SKILL.md` - [what was added/changed]
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## Governance
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[What this means for how we work]
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```
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2. **Update skill/agent** with the encoded knowledge
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3. **Close the issue** with reference to the learning file and changes made
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## Encoding Destinations
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| Insight Type | Encode In |
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|--------------|-----------|
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| How to use a tool | `skills/[tool]/SKILL.md` |
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| Workflow improvement | `skills/[skill]/SKILL.md` (user-invocable) |
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| Subtask behavior | `agents/[agent]/agent.md` |
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| Organization belief | `manifesto.md` |
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| Product direction | `vision.md` (in product repo) |
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## Labels
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Add appropriate labels to issues:
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- `learning` - Always add this
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- `prompt-improvement` - For skill text changes
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- `new-feature` - For new skills/agents
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- `bug` - For things that are broken
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## Guidelines
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- **Always create issues on architecture repo** - regardless of which repo the retro runs in
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- **Be specific**: Vague insights can't be encoded
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- **One issue per insight**: Don't bundle unrelated things
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- **Encoding happens later**: Retro captures the issue, encoding is separate work
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- **Skip one-offs**: Don't capture insights for edge cases that won't recur
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