.claude/skills/ops-retrospect/SKILL.md
Counterfactual review of decision paths after Moderate+ tasks
npx skillsauth add d0nghyun/neuron ops-retrospectInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Review decision paths after task completion. Evaluate whether the chosen approach was optimal and extract reusable lessons.
/ops-retrospectSkip for Trivial tasks (conversation, status checks, simple lookups).
Identify the decision points from the just-completed task:
| Element | Question | |---------|----------| | Intent | What did the user actually want? | | Complexity | How did I classify it? (Trivial/Moderate/Complex) | | Approach | Direct / Delegate / Collaborate — which did I pick? | | Components | Which agents, skills, teams did I use? | | Branching | Where did I choose between alternatives? |
For each branching point, list what else could have been done:
Branch: {decision point}
Chosen: {what was done}
Alternative: {option A} — {why it might have been better or worse}
Alternative: {option B} — {why it might have been better or worse}
Focus on branches where:
Score each branching decision:
| Verdict | Meaning | |---------|---------| | Correct | Chosen path was optimal or near-optimal | | Acceptable | Worked but a better path existed | | Suboptimal | A clearly better alternative was available |
Only flag Acceptable and Suboptimal — correct decisions need no action.
For each non-correct verdict, write a lesson:
Signal: {what I should have noticed}
Rule: {decision heuristic for next time}
Scope: {when this rule applies}
Append to today's memo (vault/memory/YYYY-MM-DD.md):
## Retrospective
### {Task summary}
- **Path taken**: {approach chosen}
- **Verdict**: {Acceptable/Suboptimal}
- **Better alternative**: {what should have been done}
- **Lesson**: {signal} → {rule} (scope: {scope})
If today's memo doesn't exist, create it with only the Retrospective section.
Read recent memos (vault/memory/) for recurring lessons:
retrospect_result:
task: {summary}
branches_reviewed: {count}
verdicts:
correct: {count}
acceptable: {count}
suboptimal: {count}
lessons: [{signal, rule, scope}]
pattern_detected: true | false
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