plan-flow
Use when deep architecture review or convergence planning requires analyzing repository-level duplicate/redundant design first, then building and executing a strict step-test-update plan in docs/plan.
Works with
Agent Skills format with YAML frontmatter. Claude Code reads it as-is.
--- name: "plan-flow" description: "Use when deep architecture review or convergence planning requires analyzing repository-level duplicate/redundant design first, then building and executing a strict step-test-update plan in docs/plan." license: "MIT" --- # Plan 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) 1. 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). 2. 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`. 3. 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>.md` from `references/plan-template.md`. - Keep exactly one step in `in_progress`. - Use statuses: `pending` / `in_progress` / `completed` / `blocked`. - See `references/risk-impact-scoring.md`. 4. 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. 5. 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 `completed` without 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`). - `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.
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