Cms Migration logo

Cms Migration

Organization
payloadcms
cms-migration

Use when user wants to migrate content from another CMS (WordPress, Contentful, Strapi, Sanity, Webflow, etc.) to Payload CMS

Overview

Publisherpayloadcms
Repositoryskills
Skill namecms-migration
Stars
156
Forks
4
Bundled files
1
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.

  • 1 bundled files

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

  • Open source

    Published by payloadcms on GitHub. Read the source before you install it.

Installation

Install the Cms Migration 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.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/payloadcms/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/cms-migration .claude/skills/cms-migration
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cms Migration 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 Cms Migration 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 Cms Migration 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.

CMS Migration to Payload

Interactive workflow to design Payload collections from source CMS data. Config-first approach: establish the data structure through conversation before any data import.

Workflow

Start
Ask for data sample
Analyze data shape
Propose collection config
User reviews ──────────────┐
  │                        │
  ├─ changes needed ───→ Adjust config ──→ (back to User reviews)
  └─ looks good ───→ Config confirmed
                    More collections? ──────┐
                            │               │
                            ├─ yes ──→ (back to Ask for data sample)
                            └─ no ───→ All collections confirmed
                                      Discuss migration approach
                                            Done

Phase 1: Data Analysis

When user provides data (JSON, CSV, or describes their schema):

  1. Identify field types - text, number, date, relationships, media, rich text
  2. Spot patterns - IDs, timestamps, nested objects, arrays
  3. Note relationships - foreign keys, embedded refs, linked content types
  4. Flag ambiguities - fields that could be multiple types, unclear purposes

Phase 2: Propose Collection Config

Present a Payload collection config based on analysis:

typescript
// Example output format
export const Posts: CollectionConfig = {
  slug: 'posts',
  fields: [
    { name: 'title', type: 'text', required: true },
    { name: 'content', type: 'richText' },
    { name: 'author', type: 'relationship', relationTo: 'users' },
    // ...
  ],
}

Explain your reasoning for each field choice. When something could go multiple ways (group vs JSON, text vs textarea, select vs relationship), ask rather than assume.

Phase 3: Iterate with User

Work through uncertainties: required fields, hasMany relationships, rich text vs HTML, custom timestamps vs built-in. Continue until the user confirms the config.

Phase 4: Additional Collections

After each confirmation, ask:

"Are there other content types we should create collections for?"

If yes, loop back to Phase 1 with new data sample.

Common related collections to prompt for:

  • Media/uploads
  • Users/authors
  • Categories/tags
  • Settings (global)

Phase 5: Migration Approach

Only after ALL collections are confirmed, discuss data import:

  1. Order matters - which collections have no dependencies? Migrate those first
  2. Relationship mapping - how to resolve source IDs to Payload IDs
  3. Media handling - download/re-upload vs external URLs
  4. Rich text - HTML conversion needs or keep raw

Offer to generate a seed script or walk through manual import.

Things to Clarify

Throughout the process, watch for these:

  • ID references - are they relationships to other collections?
  • Image/file URLs - upload fields or keep as external URLs?
  • Nested objects - group, array, or blocks?
  • Localization - any fields need per-locale values?
  • Access control - who can read/write this collection?
  • Related content types - categories, tags, authors that need their own collections?

Critical: Select vs Relationship

This is the most common migration mistake. Data that looks static often needs to be dynamic.

When you see repeated string values (categories, tags, types, statuses):

json
{ "category": "Technology" }
{ "category": "News" }
{ "category": "Technology" }

Don't assume it's a select field. Ask:

"I see category has values like 'Technology', 'News'. Should this be:

  • A select field with fixed options (values won't change)
  • A relationship to a Categories collection (users can add/edit/remove categories later)"

Default to relationship for anything that looks like:

  • Categories, tags, topics, labels
  • Authors, assignees, reviewers
  • Statuses beyond simple draft/published
  • Types that might expand over time

Use select only for:

  • Truly fixed enums (yes/no, draft/published/archived)
  • Options defined by business logic, not content (payment status, priority levels)
  • Values that would break functionality if changed (role types with code dependencies)

If creating a relationship, remember to add the related collection (Categories, Tags, etc.) to the migration plan.

Reference Documentation

Common Pitfalls

IssueHow to Handle
User provides partial dataAsk for more samples, especially edge cases
Unclear relationshipsAsk user to describe how content types connect
Rich text ambiguityClarify: Lexical editor, Slate, or store raw HTML
Missing media collectionAlways confirm upload collection exists before referencing
Overly complex nested dataConsider flattening or using blocks instead of deep groups

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 Cms Migration AI skill do?

Use when user wants to migrate content from another CMS (WordPress, Contentful, Strapi, Sanity, Webflow, etc.) to Payload CMS

Why use Cms Migration on TypingMind?

Because you install it once and use it with any model. Cms Migration 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 Cms Migration in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/payloadcms/skills/tree/main/skills/cms-migration. 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 Cms Migration?

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 Cms Migration?

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

Is the Cms Migration AI skill free?

It is published on GitHub by payloadcms. Check the repository for licensing terms. 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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