Retro Skill

YOU MUST EXECUTE THIS WORKFLOW. Do not just describe it.

Extract learnings from completed work and feed the knowledge flywheel.

Execution Steps

Given /retro [topic] [--vibe-results <path>]:

Step 1: Identify What to Retrospect

If vibe results path provided: Read and incorporate validation findings:

code

Tool: Read
Parameters:
  file_path: <vibe-results-path>

This allows post-mortem to pass validation context without re-running vibe.

If topic provided: Focus on that specific work.

If no topic: Look at recent activity:

bash

# Recent commits
git log --oneline -10 --since="7 days ago"

# Recent issues closed
bd list --status closed --since "7 days ago" 2>/dev/null | head -5

# Recent research/plans
ls -lt .agents/research/ .agents/plans/ 2>/dev/null | head -5

Step 2: Gather Context

Read relevant artifacts:

•Research documents
•Plan documents
•Commit messages
•Code changes

Use the Read tool and git commands to understand what was done.

Step 3: Identify Learnings

If vibe results were provided, incorporate them:

•Extract learnings from CRITICAL and HIGH findings
•Note patterns that led to issues
•Identify anti-patterns to avoid

Ask these questions:

What went well?

•What approaches worked?
•What was faster than expected?
•What should we do again?

What went wrong?

•What failed?
•What took longer than expected?
•What would we do differently?
•(Include vibe findings if provided)

What did we discover?

•New patterns found
•Codebase quirks learned
•Tool tips discovered
•Debugging insights

Step 4: Extract Actionable Learnings

For each learning, capture:

•ID: L1, L2, L3...
•Category: debugging, architecture, process, testing, security
•What: The specific insight
•Why it matters: Impact on future work
•Confidence: high, medium, low

Step 5: Write Learnings

Write to: .agents/learnings/YYYY-MM-DD-<topic>.md

markdown

# Learning: <Short Title>

**ID**: L1
**Category**: <category>
**Confidence**: <high|medium|low>

## What We Learned

<1-2 sentences describing the insight>

## Why It Matters

<1 sentence on impact/value>

## Source

<What work this came from>

---

# Learning: <Next Title>

**ID**: L2
...

Step 6: Write Retro Summary

Write to: .agents/retros/YYYY-MM-DD-<topic>.md

markdown

# Retrospective: <Topic>

**Date:** YYYY-MM-DD
**Scope:** <what work was reviewed>

## Summary
<1-2 sentence overview>

## What Went Well
- <thing 1>
- <thing 2>

## What Could Be Improved
- <improvement 1>
- <improvement 2>

## Learnings Extracted
- L1: <brief>
- L2: <brief>

See: `.agents/learnings/YYYY-MM-DD-<topic>.md`

## Action Items
- [ ] <any follow-up needed>

Step 7: Index for Future Discovery (if ao available)

bash

ao forge index .agents/learnings/YYYY-MM-DD-*.md 2>/dev/null

Step 8: Report to User

Tell the user:

•Number of learnings extracted
•Key insights (top 2-3)
•Location of retro and learnings files
•Knowledge has been indexed for future sessions

Key Rules

•Be specific - "auth tokens expire" not "learned about auth"
•Be actionable - learnings should inform future decisions
•Cite sources - reference what work the learning came from
•Write both files - retro summary AND detailed learnings
•Index knowledge - make it discoverable

The Flywheel

Learnings feed future research:

code

Work → /retro → .agents/learnings/ → ao forge index → /research finds it

Future sessions start smarter because of your retrospective.