duck-plan

Solid

Plan-review session with the rubber duck — verify the user understands decisions and trade-offs before execution. Use after a plan/spec/RFC was produced, or when they say "duck plan", "이 플랜 검수해". Not for plan authoring or code review.

AI & Automation 47 stars 4 forks Updated 4 days ago MIT

Install

View on GitHub

Quality Score: 87/100

Stars 20%
56
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

# Duck — Plan Review Mode **Read first**: [../duck/references/core.md](../duck/references/core.md) — persona, "Wait for their answer", Confidence Check (Plan Review row), Branch-first workflow, Intensity Scaling, Uncertainty Check, Session Wrap-up + gap persistence, Facilitation, Gotchas. They apply here. **Input**: The current plan — find it in conversation context, or ask the user to point to it (file path or message). ## Flow 1. **Extract assumptions and decisions** from the plan: - Technology/architecture choices - Scope decisions (included AND excluded) - Implicit assumptions not stated - Trade-offs that were made 2. **Walk through each one**, one at a time. Ask exactly ONE question per decision — do not combine two questions into one. Forbidden patterns: "Why X? What problem does Y solve?", "Why X? What would you lose?", "Why X — and what about [alternative]?": > **Your turn:** The plan chose [specific decision]. Why is this the right call? > > (You can also say confirm / change / remove.) 3. After their response, probe deeper (this is where follow-up questions go — not bundled into the first question): - "confirm" without explanation → "OK, but why? Why not [alternative]?" - "change" → "Change it how? What happens to [downstream dependency]?" - "remove" → "If we remove that, [consequence]. Is that acceptable?" 4. Continue until all decisions are covered. 5. **Confidence check** — run the Plan Review row from the [Confidence Check (shared)]...

Details

Author
LeeJuOh
Repository
LeeJuOh/claude-code-zero
Created
4 months ago
Last Updated
4 days ago
Language
Python
License
MIT

Integrates with

Similar Skills

Semantically similar based on skill content — not just same category