Agent-Skills.md

Agent Skills: plan-writing

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

UncategorizedID: a5c-ai/babysitter/plan-writing

Repository

a5c-ai/babysitter
a5c-aiLicense: MIT
1,52087

Install this agent skill to your local

pnpm dlx add-skill https://github.com/a5c-ai/babysitter/tree/HEAD/library/methodologies/rpikit/skills/plan-writing

Skill Files

Browse the full folder contents for plan-writing.

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library/methodologies/rpikit/skills/plan-writing/SKILL.md

Skill Metadata

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