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plan-flow计划流程

Agent Skill

plan-flow 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

865

周安装

35

GitHub Stars

28

下载量

272
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:plan-flow(计划流程)
来源仓库:https://github.com/majiayu000/claude-arsenal
仓库路径:skills/plan-flow
安装命令:
npx skills add https://github.com/majiayu000/claude-arsenal --skill plan-flow
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/majiayu000/claude-arsenal --skill plan-flow

简介

plan-flow 用于查找、检索和筛选相关信息。

  • 适合根据关键词或任务场景快速定位候选结果。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。
  • 可结合来源仓库和 README 核验具体用法。
  • 安装前建议确认权限范围和是否会触发命令执行。
  • 注意维护状态和网络访问限制。plan-flow 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

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).
  1. 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.
  1. 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.
  1. 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.
  1. 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.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

36.3%
按下载量换算99

Claude

28.85%
按下载量换算78

Cursor

20.49%
按下载量换算56

Gemini CLI

10.25%
按下载量换算28

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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