About plan-flow
Plan Flow is a repository-agnostic skill for analyzing codebase redundancy and turning findings into file-level execution plans. It enforces a one-step-at-a-time cycle of implementation, testing, and status updates with recorded evidence.
Key features
- 01Inventory architecture and identify redundancy
- 02Prioritize findings by impact, effort, and risk
- 03Create phased, file-level execution plans
- 04Implement, test, and update status step by step
- 05Check plan state and test evidence
Use cases
- 01Reviewing duplicate implementations in a codebase
- 02Planning a phased refactor with actionable steps
- 03Tracking test results during incremental changes
Install
Copy the command and run it in a terminal.
$
npx skills add https:/ / github.com/ majiayu000/ spellbook --skill plan-flowAfter installing, type/plan-flowin Claude Code to confirm it loaded.
Bundled files
References and scripts installed along with SKILL.md.
references/analysis-playbook.mdplan-accomplishments.mdplan-template.mdrisk-impact-scoring.mdscripts/findings_to_plan.pyplan_lint.pyredundancy_scan.shDetails
From the project READMEPlan Flow
Overview
Use this skill when the user needs:
- A complete analysis of duplicated/redundant design in a codebase.
- A detailed TODO plan with explicit file-level steps.
- Strict execution evidence: change one step, test it, then update plan status.
This skill is repository-agnostic. It defines how to analyze and plan, not only what was done in one specific repo.
Core Workflow (Analyze -> Plan -> Execute)
- Establish scope and constraints.
- Confirm target directories/modules and out-of-scope areas.
- Capture compatibility requirement, risk tolerance, and testing expectations.
- Record baseline (
git status --short, current branch, known blockers).
- Run structured redundancy analysis first.
- Build an inventory of architecture anchors:
- Domain models and schemas
- Factory/registry entry points
- HTTP/storage/cache/logging abstractions
- Route/service/provider adapters
- Identify duplicate/redundant candidates with evidence:
- Same concept, multiple conflicting definitions
- Same responsibility, parallel implementations
- Exported but unconnected modules
- Dead/legacy paths still affecting readability
- For each finding, record:
- Exact files and symbols
- Call path or usage evidence
- Risk if changed
- See
references/analysis-playbook.md.
- Prioritize and convert analysis into executable plan.
- Score each finding by impact/effort/risk/confidence.
- Group into phases (
P0,P1,P2) and sequence low-risk/high-signal steps first. - Create or update
plan/<task>.mdfromreferences/plan-template.md. - Keep exactly one step in
in_progress. - Use statuses:
pending/in_progress/completed/blocked. - See
references/risk-impact-scoring.md.
- Execute with strict step-test-update loop.
- Implement only the current step and only in listed files.
- Run step-level tests immediately, then project health checks.
- Update plan status and execution log before touching next step.
- On failure, record root cause and run fix loop before continuing.
- Close with phase/final verification.
- Run phase matrix checks and final regression set.
- Report residual risks, deferred work, and explicit coverage gaps.
Quality Gates
- No finding enters the plan without file-level evidence.
- No step is
completedwithout test command evidence. - No next step starts before plan status/log update is written.
- If full regression is unavailable, record exact reason and nearest fallback checks.
Reference Map
references/analysis-playbook.md- How to detect duplicate/redundant design with reproducible evidence.
references/risk-impact-scoring.md- How to prioritize findings into phases and step order.
references/plan-template.md- Reusable plan skeleton including analysis table, step template, and log format.
references/plan-accomplishments.md- One completed real example (for style and granularity only, not as mandatory scope).
Scripts
scripts/redundancy_scan.sh <target_dir>- Fast first-pass scan for duplicate symbol names, parallel factory/builders, and legacy/dead-code hints.
scripts/findings_to_plan.py --target-dir src --output plan/<name>.md- Convert scan findings into a draft execution plan with scoring and phased order (
P0/P1/P2).
- Convert scan findings into a draft execution plan with scoring and phased order (
scripts/plan_lint.py <plan/file.md>- Validate plan state machine, test evidence, and execution-log completeness for completed steps.
Trigger Cues
Trigger this skill when user asks for:
- "分析这个库有哪些重复设计/冗余设计"
- "做一个非常完整详细的 todolist/执行计划"
- "每改一处就测试并更新计划状态"
- "按步骤推进并可追踪"
Execution Rules
- Prefer small, reversible steps over large refactors.
- Keep plan language specific to file paths, symbols, and commands.
- Avoid mixing analysis conclusions with unverified assumptions.
- If new evidence contradicts earlier assumptions, revise plan before coding.
Comments
Markdown supported