Building Storefronts logo

Building Storefronts

Organization
medusajs
building-storefronts

Load automatically when planning, researching, or implementing Medusa storefront features (calling custom API routes, SDK integration, React Query patterns, data fetching). REQUIRED for all storefront development in ALL modes (planning, implementation, exploration). Contains SDK usage patterns, frontend integration, and critical rules for calling Medusa APIs.

Overview

Publishermedusajs
Repositorymedusa-agent-skills
Skill namebuilding-storefronts
Stars
218
Forks
27
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 medusajs on GitHub. Read the source before you install it.

Installation

Install the Building Storefronts 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/medusajs/medusa-agent-skills.git /tmp/medusa-agent-skills
mkdir -p .claude/skills
cp -r /tmp/medusa-agent-skills/plugins/medusa-dev/skills/building-storefronts .claude/skills/building-storefronts
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Building Storefronts 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 Building Storefronts 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 Building Storefronts 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.

Medusa Storefront Development

Frontend integration guide for building storefronts with Medusa. Covers SDK usage, React Query patterns, and calling custom API routes.

When to Apply

Load this skill for ANY storefront development task, including:

  • Calling custom Medusa API routes from the storefront
  • Integrating Medusa SDK in frontend applications
  • Using React Query for data fetching
  • Implementing mutations with optimistic updates
  • Error handling and cache invalidation

Also load building-with-medusa when: Building the backend API routes that the storefront calls

CRITICAL: Load Reference Files When Needed

The quick reference below is NOT sufficient for implementation. You MUST load the reference file before writing storefront integration code.

Load this reference when implementing storefront features:

  • Calling API routes? → MUST load references/frontend-integration.md first
  • Using SDK? → MUST load references/frontend-integration.md first
  • Implementing React Query? → MUST load references/frontend-integration.md first

Rule Categories by Priority

PriorityCategoryImpactPrefix
1SDK UsageCRITICALsdk-
2React Query PatternsHIGHquery-
3Data DisplayHIGH (includes CRITICAL price rule)display-
4Error HandlingMEDIUMerror-

Quick Reference

1. SDK Usage (CRITICAL)

  • sdk-always-use - ALWAYS use the Medusa JS SDK for ALL API requests - NEVER use regular fetch()
  • sdk-existing-methods - For built-in endpoints, use existing SDK methods (sdk.store.product.list(), sdk.admin.order.retrieve())
  • sdk-client-fetch - For custom API routes, use sdk.client.fetch()
  • sdk-required-headers - SDK automatically adds required headers (publishable API key for store, auth for admin) - regular fetch() missing these headers causes errors
  • sdk-no-json-stringify - NEVER use JSON.stringify() on body - SDK handles serialization automatically
  • sdk-plain-objects - Pass plain JavaScript objects to body, not strings
  • sdk-locate-first - Always locate where SDK is instantiated in the project before using it

2. React Query Patterns (HIGH)

  • query-use-query - Use useQuery for GET requests (data fetching)
  • query-use-mutation - Use useMutation for POST/DELETE requests (mutations)
  • query-invalidate - Invalidate queries in onSuccess to refresh data after mutations
  • query-keys-hierarchical - Structure query keys hierarchically for effective cache management
  • query-loading-states - Always handle isLoading, isPending, isError states

3. Data Display (HIGH)

  • display-price-format - CRITICAL: Prices from Medusa are stored as-is ($49.99 = 49.99, NOT in cents). Display them directly - NEVER divide by 100

4. Error Handling (MEDIUM)

  • error-on-error - Implement onError callback in mutations to handle failures
  • error-display - Show error messages to users when mutations fail
  • error-rollback - Use optimistic updates with rollback on error for better UX

Critical SDK Pattern

ALWAYS pass plain objects to the SDK - NEVER use JSON.stringify():

typescript
// ✅ CORRECT - Plain object
await sdk.client.fetch("/store/reviews", {
  method: "POST",
  body: {
    product_id: "prod_123",
    rating: 5,
  }
})

// ❌ WRONG - JSON.stringify breaks the request
await sdk.client.fetch("/store/reviews", {
  method: "POST",
  body: JSON.stringify({  // ❌ DON'T DO THIS!
    product_id: "prod_123",
    rating: 5,
  })
})

Why this matters:

  • The SDK handles JSON serialization automatically
  • Using JSON.stringify() will double-serialize and break the request
  • The server won't be able to parse the body

Common Mistakes Checklist

Before implementing, verify you're NOT doing these:

SDK Usage:

  • Using regular fetch() instead of the Medusa JS SDK (causes missing header errors)
  • Not using existing SDK methods for built-in endpoints (e.g., using sdk.client.fetch("/store/products") instead of sdk.store.product.list())
  • Using JSON.stringify() on the body parameter
  • Manually setting Content-Type headers (SDK adds them)
  • Hardcoding SDK import paths (locate in project first)
  • Not using sdk.client.fetch() for custom routes

React Query:

  • Not invalidating queries after mutations
  • Using flat query keys instead of hierarchical
  • Not handling loading and error states
  • Forgetting to disable buttons during mutations (isPending)

Data Display:

  • CRITICAL: Dividing prices by 100 when displaying (prices are stored as-is: $49.99 = 49.99, NOT in cents)

Error Handling:

  • Not implementing onError callbacks
  • Not showing error messages to users
  • Not handling network failures gracefully

How to Use

For detailed patterns and examples, load reference file:

references/frontend-integration.md - SDK usage, React Query patterns, API integration

The reference file contains:

  • Step-by-step SDK integration patterns
  • Complete React Query examples
  • Correct vs incorrect code examples
  • Query key best practices
  • Optimistic update patterns
  • Error handling strategies

When to Use MedusaDocs MCP Server

Use this skill for (PRIMARY SOURCE):

  • How to call custom API routes from storefront
  • SDK usage patterns (sdk.client.fetch)
  • React Query integration patterns
  • Common mistakes and anti-patterns

Use MedusaDocs MCP server for (SECONDARY SOURCE):

  • Built-in SDK methods (sdk.admin., sdk.store.)
  • Official Medusa SDK API reference
  • Framework-specific configuration options

Why skills come first:

  • Skills contain critical patterns like "don't use JSON.stringify" that MCP doesn't emphasize
  • Skills show correct vs incorrect patterns; MCP shows what's possible
  • Planning requires understanding patterns, not just API reference

Integration with Backend

⚠️ CRITICAL: ALWAYS use the Medusa JS SDK - NEVER use regular fetch()

When building features that span backend and frontend:

  1. Backend (building-with-medusa skill): Module → Workflow → API Route
  2. Storefront (this skill): SDK → React Query → UI Components
  3. Connection:
    • Built-in endpoints: Use existing SDK methods (sdk.store.product.list())
    • Custom API routes: Use sdk.client.fetch("/store/my-route")
    • NEVER use regular fetch() - missing publishable API key causes errors

Why the SDK is required:

  • Store routes need x-publishable-api-key header
  • Admin routes need Authorization and session headers
  • SDK handles all required headers automatically
  • Regular fetch() without headers → authentication/authorization errors

See building-with-medusa for backend API route patterns.

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 Building Storefronts AI skill do?

Load automatically when planning, researching, or implementing Medusa storefront features (calling custom API routes, SDK integration, React Query patterns, data fetching). REQUIRED for all storefront development in ALL modes (planning, implementation, exploration). Contains SDK usage patterns, frontend integration, and critical rules for calling Medusa APIs.

Why use Building Storefronts on TypingMind?

Because you install it once and use it with any model. Building Storefronts 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 Building Storefronts in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/medusajs/medusa-agent-skills/tree/main/plugins/medusa-dev/skills/building-storefronts. 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 Building Storefronts?

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 Building Storefronts?

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

Is the Building Storefronts AI skill free?

It is published on GitHub by medusajs. 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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