plan-writing

Solid

Transform research findings into actionable implementation plans with stakes-based rigor, test-first strategy, and granular task decomposition.

AI & Automation 814 stars 53 forks Updated today MIT

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Quality Score: 93/100

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100
Frontmatter 20%
70
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Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

# Plan Writing ## Overview Convert research findings into actionable implementation plans. Scales planning rigor to stakes level. Every code-changing task specifies tests before implementation. ## When to Use - After research phase identifies what needs to change - Before implementing any medium or high stakes changes - When requirements are clear and codebase is understood ## Process 1. **Load research** - Find `*-<topic>-research.md` in `docs/plans/` 2. **Classify stakes** - Low (isolated, reversible), Medium (multiple files), High (architectural) 3. **Define success criteria** - Functional, non-functional, and acceptance criteria 4. **Decompose tasks** - Granular steps with file paths, line references, verification methods 5. **Plan tests** - Test specification as first sub-step per task (test-first) 6. **Assess risks** - Breaking changes, performance, security, dependencies, rollback strategy 7. **Write plan document** - `docs/plans/YYYY-MM-DD-<topic>-plan.md` 8. **Approval gate** - Human approves, requests changes, or returns to research ## Anti-Patterns to Avoid - Vague task descriptions without specific file references - Missing verification criteria for any step - Combining test writing and implementation into single steps - Planning rigor mismatched to stakes level - Proceeding without explicit user approval ## Tool Use Invoke via babysitter process: `methodologies/rpikit/rpikit-plan`

Details

Author
a5c-ai
Repository
a5c-ai/babysitter
Created
4 months ago
Last Updated
today
Language
JavaScript
License
MIT

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