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legacy-modernizer遗产现代化者

Agent Skill

legacy-modernizer 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。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

2,157

周安装

89

GitHub Stars

76

下载量

705
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

3

许可证

MIT

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:legacy-modernizer(遗产现代化者)
来源仓库:https://github.com/404kidwiz/claude-supercode-skills
仓库路径:skills/legacy-modernizer
安装命令:
npx skills add https://github.com/404kidwiz/claude-supercode-skills --skill legacy-modernizer
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/404kidwiz/claude-supercode-skills --skill legacy-modernizer

简介

legacy-modernizer 专长于渐进式重构遗留系统,无需全量重写即可实现现代化。

  • 采用 Strangler Fig 模式、防腐层和数据捕获技术保障迁移过程平稳过渡。
  • 通过 npx 安装后,可协助设计双写场景、评估代码优先级或实施 CDC 同步。
  • 操作前需确认业务连续性要求,避免在生产环境中直接执行高风险变更。
  • 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。

SKILL.md

Legacy Modernizer

Purpose

Provides expertise in incrementally modernizing legacy systems without full rewrites. Specializes in migration patterns like Strangler Fig, Change Data Capture (CDC), and Anti-Corruption Layers to safely evolve systems while maintaining business continuity.

When to Use

  • Planning migration from monolith to microservices
  • Implementing Strangler Fig pattern
  • Designing Anti-Corruption Layers between old and new systems
  • Setting up Change Data Capture for data synchronization
  • Modernizing legacy databases incrementally
  • Replacing legacy APIs while maintaining compatibility
  • Assessing legacy codebase for modernization priority
  • Managing dual-write scenarios during transitions

Quick Start

Invoke this skill when:

  • Migrating legacy monoliths to modern architectures
  • Implementing Strangler Fig or Branch by Abstraction
  • Designing Anti-Corruption Layers
  • Setting up CDC for data sync between systems
  • Planning incremental modernization roadmaps

Do NOT invoke when:

  • Greenfield microservices design → use /microservices-architect
  • General refactoring without migration → use /refactoring-specialist
  • Database optimization without migration → use /database-optimizer
  • API design without legacy concerns → use /api-designer

Decision Framework

Migration Strategy?
├── Replace Incrementally
│   └── Strangler Fig: Route traffic to new service gradually
├── Abstract and Replace
│   └── Branch by Abstraction: Interface → implement new → switch
├── Data Sync Required
│   └── CDC with Debezium/similar for real-time sync
└── Protect New from Old
    └── Anti-Corruption Layer: Translate between domains

Core Workflows

1. Strangler Fig Implementation

  1. Identify bounded context to extract
  2. Create facade/proxy in front of legacy system
  3. Build new service implementing same interface
  4. Route subset of traffic to new service
  5. Gradually increase traffic percentage
  6. Retire legacy component when fully migrated

2. Anti-Corruption Layer Setup

  1. Define clean domain model for new system
  2. Identify integration points with legacy
  3. Build translator layer between models
  4. Implement adapters for legacy APIs/data
  5. Add monitoring for translation failures
  6. Document mapping rules

3. CDC Data Migration

  1. Set up CDC tool (Debezium, AWS DMS)
  2. Configure change capture on legacy database
  3. Build consumer to apply changes to new system
  4. Handle schema differences with transformations
  5. Implement validation and reconciliation
  6. Plan cutover and fallback strategy

Best Practices

  • Migrate incrementally—avoid big-bang rewrites
  • Maintain feature parity during transition
  • Use feature flags to control traffic routing
  • Implement comprehensive monitoring during migration
  • Keep legacy and new systems in sync until cutover
  • Document all integration points and dependencies

Anti-Patterns

Anti-PatternProblemCorrect Approach
Big-bang rewriteHigh risk, long timelineIncremental migration
No Anti-Corruption LayerNew system polluted by legacyIsolate with ACL
Dual-write without CDCData inconsistencyUse CDC for sync
Migrating everything at onceOverwhelming complexityPrioritize by business value
No rollback planStuck if migration failsAlways plan fallback

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

04

需要参考平台分布和安装热度时

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

补充不同宿主或平台的使用分布数据

能力 5

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

Claude Code

30.09%
按下载量换算212

OpenCode

22.75%
按下载量换算160

Codex

18.63%
按下载量换算131

Cursor

12.24%
按下载量换算86

Gemini CLI

6.75%
按下载量换算48

windsurf

3.03%
按下载量换算21

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。

来源信息

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