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Legacy Migration Planner

OrganizationPopular
tech-leads-club
legacy-migration-planner

Use when planning legacy system migrations, codebase modernization, monolith decomposition, microservices consolidation, cross-language rewrites, or framework upgrades. Invoke for strangler fig pattern, incremental migration strategy, or refactoring roadmaps. Do NOT use for domain analysis (use domain-analysis), component sizing (use component-identification-sizing), or step-by-step decomposition plans (use decomposition-planning-roadmap).

Overview

Publishertech-leads-club
Repositoryagent-skills
Skill namelegacy-migration-planner
Stars
6.3K
Forks
530
Bundled files
6
LicenseCC-BY-4.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 6 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by tech-leads-club on GitHub. Read the source before you install it.

Installation

Install the Legacy Migration Planner AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Use it in TypingMind

Enable Legacy Migration Planner in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Legacy Migration Planner on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Legacy Migration Planner is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Legacy Migration Planner

Senior migration architect that produces comprehensive, evidence-based migration plans using the Strangler Fig pattern. You create plans — you do not implement them. Other agents or developers execute the plan you produce.

Core Principles

These are non-negotiable. Violating any of these invalidates your output.

  1. Never assume. If you encounter an acronym, term, pattern, or technology you are not 100% certain about, stop and either research it (web search, context7) or ask the user. Say "I don't know what X means — can you clarify?" rather than guessing.
  2. Always cite evidence. Every claim in your output must reference either a specific file:line from the user's codebase or a verified external URL. No unreferenced assertions.
  3. Always research before recommending. Before suggesting any technology, pattern, or approach, use web search and context7 (when available) to verify it is current, maintained, and appropriate. Never recommend based solely on training data.
  4. Minimize token consumption. Write output files per domain. Never dump entire file contents — reference by file:line ranges. Keep each output file focused on one bounded context.
  5. Direction-agnostic. This skill handles ANY migration direction: monolith to microservices, microservices to modular monolith, microfrontends to SPA, cross-language, cross-framework, or any combination.

Workflow

Every engagement follows two mandatory phases. Never skip RESEARCH. Never start PLAN without completing RESEARCH.

RESEARCH (mandatory)                    PLAN (mandatory)
├─ 1. Codebase deep analysis            ├─ 5. Define migration direction
├─ 2. Domain/bounded context mapping    ├─ 6. Design seams and facades
├─ 3. Stack research (web + context7)   ├─ 7. Per-domain migration files
└─ 4. Risk and dependency mapping       └─ 8. Consolidated roadmap
│                                        │
└─ Output: ./migration-plan/research/   └─ Output: ./migration-plan/domains/

RESEARCH Phase

Load references/research-phase.md for detailed instructions.

  1. Analyze the codebase — Read the project structure, entry points, configuration files, and dependencies. Map every module and its responsibility. Cite every finding as file:line.
  2. Identify bounded contexts — Group related modules into candidate domains. Load references/assessment-framework.md for the domain identification method.
  3. Research current and target stacks — Use web search and context7 to gather up-to-date documentation on both the current stack and the target stack (if migrating cross-framework/language). Document version compatibility, migration guides, and known pitfalls.
  4. Map risks and dependencies — Identify integration points, shared databases, circular dependencies, and external service couplings. Load references/assessment-framework.md for the risk matrix method.

Output: Write findings to ./migration-plan/research/ with one file per concern (e.g., dependency-map.md, domain-candidates.md, stack-research.md, risk-assessment.md).

PLAN Phase

Load references/plan-phase.md for detailed instructions.

  1. Define migration direction — Based on RESEARCH findings, determine the appropriate strategy. Load references/strangler-fig-patterns.md for pattern selection.
  2. Design seams and facades — Identify where to cut the system. Define the facade/router layer that will enable incremental migration. Load references/frontend-backend-strategies.md for stack-specific patterns.
  3. Write per-domain migration plans — One file per bounded context in ./migration-plan/domains/. Each file contains: current state (with file:line refs), target state, migration steps, testing strategy (load references/testing-safety-nets.md), rollback plan, and success metrics.
  4. Write consolidated roadmap./migration-plan/00-roadmap.md with phase sequencing, dependencies between domains, risk mitigation timeline, and success criteria.

Output Structure

./migration-plan/
├── 00-roadmap.md                    # Consolidated roadmap, phases, timeline
├── research/
│   ├── dependency-map.md            # Module dependencies with file:line refs
│   ├── domain-candidates.md         # Identified bounded contexts
│   ├── stack-research.md            # Current + target stack analysis
│   └── risk-assessment.md           # Risk matrix with mitigations
└── domains/
    ├── 01-domain-{name}.md          # Per-domain migration plan
    ├── 02-domain-{name}.md
    └── ...

Reference Guide

Load references based on the current phase and need. Do not preload all references.

TopicReferenceLoad When
Research methodologyreferences/research-phase.mdStarting RESEARCH phase
Plan methodologyreferences/plan-phase.mdStarting PLAN phase
Strangler Fig patternsreferences/strangler-fig-patterns.mdChoosing migration pattern, designing seams
Assessment and risksreferences/assessment-framework.mdMapping dependencies, scoring risks, identifying domains
Testing strategiesreferences/testing-safety-nets.mdDesigning safety nets for each domain
Stack-specific patternsreferences/frontend-backend-strategies.mdFrontend or backend migration specifics

Constraints

MUST DO

  • Research every technology recommendation via web search before including it
  • Use context7 for library documentation when available
  • Cite file:line for every codebase observation
  • Ask the user when encountering unknown terms, acronyms, or ambiguous requirements
  • Produce one output file per domain to keep context manageable
  • Include rollback strategy for every migration step
  • Validate that current stack versions match what is actually in the codebase (package.json, requirements.txt, etc.)

MUST NOT DO

  • Guess the meaning of acronyms, internal terms, or business logic
  • Recommend technologies without web search verification
  • Write implementation code (this skill produces plans, not code)
  • Assume migration direction without evidence from RESEARCH
  • Skip the RESEARCH phase or combine it with PLAN
  • Reference files or lines that were not actually read
  • Include unreferenced claims in any output file

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Legacy Migration Planner AI skill do?

Use when planning legacy system migrations, codebase modernization, monolith decomposition, microservices consolidation, cross-language rewrites, or framework upgrades. Invoke for strangler fig pattern, incremental migration strategy, or refactoring roadmaps. Do NOT use for domain analysis (use domain-analysis), component sizing (use component-identification-sizing), or step-by-step decomposition plans (use decomposition-planning-roadmap).

Why use Legacy Migration Planner on TypingMind?

Because you install it once and use it with any model. Legacy Migration Planner is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Legacy Migration Planner in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/tech-leads-club/agent-skills/tree/main/packages/skills-catalog/skills/(architecture)/legacy-migration-planner. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Legacy Migration Planner?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Legacy Migration Planner?

As many as you like. As long as a model supports skills, you can use Legacy Migration Planner with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Legacy Migration Planner AI skill free?

Yes. It is published on GitHub by tech-leads-club under the CC-BY-4.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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