Dynamic logo

Dynamic

Organization
ww-w-ai
dynamic

Fullstack development with bkend.ai BaaS — authentication, database, API integration. Triggers: fullstack, BaaS, login, signup, database, web app

Overview

Publisherww-w-ai
Repositorybkit-claude-code
Skill namedynamic
Stars
601
Forks
154
Bundled files
Instructions only
LicenseApache-2.0
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by ww-w-ai on GitHub. Read the source before you install it.

Installation

Install the Dynamic 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/ww-w-ai/bkit-claude-code.git /tmp/bkit-claude-code
mkdir -p .claude/skills
cp -r /tmp/bkit-claude-code/skills/dynamic .claude/skills/dynamic
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Dynamic 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 Dynamic 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 Dynamic 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.

Intermediate (Dynamic) Skill

Actions

ActionDescriptionExample
initProject initialization (/init-dynamic feature)/dynamic init my-saas
guideDisplay development guide/dynamic guide
helpBaaS integration help/dynamic help

init (Project Initialization)

  1. Create Next.js + Tailwind project structure
  2. Configure bkend.ai MCP (.mcp.json)
  3. Create CLAUDE.md (Level: Dynamic specified)
  4. Create docs/ folder structure
  5. src/lib/bkend.ts client template
  6. Initialize .bkit-memory.json

guide (Development Guide)

  • bkend.ai auth/data configuration guide
  • Phase 1-9 full Pipeline guide
  • API integration patterns

help (BaaS Help)

  • Explain bkend.ai basic concepts
  • Auth, database, file storage usage
  • MCP integration methods

Target Audience

  • Frontend developers
  • Solo entrepreneurs
  • Those who want to build fullstack services quickly

Tech Stack

Frontend:
- React / Next.js 14+
- TypeScript
- Tailwind CSS
- TanStack Query (data fetching)
- Zustand (state management)

Backend (BaaS):
- bkend.ai
  - Auto REST API
  - MongoDB database
  - Built-in authentication (JWT)
  - Real-time features (WebSocket)

Deployment:
- Vercel (frontend)
- bkend.ai (backend)

Language Tier Guidance (v1.3.0)

Recommended: Tier 1-2 languages

Dynamic level supports full-stack development with strong AI compatibility.

TierAllowedReason
Tier 1✅ PrimaryFull AI support
Tier 2✅ YesMobile (Flutter/RN), Modern web (Vue, Astro)
Tier 3⚠️ LimitedPlatform-specific needs only
Tier 4❌ NoMigration recommended

Mobile Development:

  • React Native (Tier 1 via TypeScript) - Recommended
  • Flutter (Tier 2 via Dart) - Supported

Project Structure

project/
├── src/
│   ├── app/                    # Next.js App Router
│   │   ├── (auth)/            # Auth-related routes
│   │   │   ├── login/
│   │   │   └── register/
│   │   ├── (main)/            # Main routes
│   │   │   ├── dashboard/
│   │   │   └── settings/
│   │   ├── layout.tsx
│   │   └── page.tsx
│   │
│   ├── components/             # UI components
│   │   ├── ui/                # Basic UI (Button, Input...)
│   │   └── features/          # Feature-specific components
│   │
│   ├── hooks/                  # Custom hooks
│   │   ├── useAuth.ts
│   │   └── useQuery.ts
│   │
│   ├── lib/                    # Utilities
│   │   ├── bkend.ts           # bkend.ai client
│   │   └── utils.ts
│   │
│   ├── stores/                 # State management (Zustand)
│   │   └── auth-store.ts
│   │
│   └── types/                  # TypeScript types
│       └── index.ts
├── docs/                       # PDCA documents
│   ├── 01-plan/
│   ├── 02-design/
│   │   ├── data-model.md      # Data model
│   │   └── api-spec.md        # API specification
│   ├── 03-analysis/
│   └── 04-report/
├── .mcp.json                   # bkend.ai MCP config (type: http)
├── .env.local                  # Environment variables
├── package.json
└── README.md

Core Patterns

bkend.ai Client Setup

typescript
// lib/bkend.ts - REST Service API Client
const API_BASE = process.env.NEXT_PUBLIC_BKEND_API_URL || 'https://api.bkend.ai/v1';
const PROJECT_ID = process.env.NEXT_PUBLIC_BKEND_PROJECT_ID!;
const ENVIRONMENT = process.env.NEXT_PUBLIC_BKEND_ENV || 'dev';

async function bkendFetch(path: string, options: RequestInit = {}) {
  const token = localStorage.getItem('bkend_access_token');
  const res = await fetch(`${API_BASE}${path}`, {
    ...options,
    headers: {
      'Content-Type': 'application/json',
      'x-project-id': PROJECT_ID,
      'x-environment': ENVIRONMENT,
      ...(token && { Authorization: `Bearer ${token}` }),
      ...options.headers,
    },
  });
  if (!res.ok) throw new Error(await res.text());
  return res.json();
}

export const bkend = {
  auth: {
    signup: (body: {email: string; password: string}) => bkendFetch('/auth/email/signup', {method: 'POST', body: JSON.stringify(body)}),
    signin: (body: {email: string; password: string}) => bkendFetch('/auth/email/signin', {method: 'POST', body: JSON.stringify(body)}),
    me: () => bkendFetch('/auth/me'),
    refresh: (refreshToken: string) => bkendFetch('/auth/refresh', {method: 'POST', body: JSON.stringify({refreshToken})}),
    signout: () => bkendFetch('/auth/signout', {method: 'POST'}),
  },
  data: {
    list: (table: string, params?: Record<string,string>) => bkendFetch(`/data/${table}?${new URLSearchParams(params)}`),
    get: (table: string, id: string) => bkendFetch(`/data/${table}/${id}`),
    create: (table: string, body: any) => bkendFetch(`/data/${table}`, {method: 'POST', body: JSON.stringify(body)}),
    update: (table: string, id: string, body: any) => bkendFetch(`/data/${table}/${id}`, {method: 'PATCH', body: JSON.stringify(body)}),
    delete: (table: string, id: string) => bkendFetch(`/data/${table}/${id}`, {method: 'DELETE'}),
  },
};

Authentication Hook

typescript
// hooks/useAuth.ts
import { create } from 'zustand';
import { persist } from 'zustand/middleware';
import { bkend } from '@/lib/bkend';

interface AuthState {
  user: User | null;
  isLoading: boolean;
  login: (email: string, password: string) => Promise<void>;
  logout: () => void;
}

export const useAuth = create<AuthState>()(
  persist(
    (set) => ({
      user: null,
      isLoading: false,

      login: async (email, password) => {
        set({ isLoading: true });
        const { user, token } = await bkend.auth.login({ email, password });
        set({ user, isLoading: false });
      },

      logout: () => {
        bkend.auth.logout();
        set({ user: null });
      },
    }),
    { name: 'auth-storage' }
  )
);

Data Fetching (TanStack Query)

typescript
// List query
const { data, isLoading, error } = useQuery({
  queryKey: ['items', filters],
  queryFn: () => bkend.collection('items').find(filters),
});

// Single item query
const { data: item } = useQuery({
  queryKey: ['items', id],
  queryFn: () => bkend.collection('items').findById(id),
  enabled: !!id,
});

// Create/Update (Mutation)
const mutation = useMutation({
  mutationFn: (newItem) => bkend.collection('items').create(newItem),
  onSuccess: () => {
    queryClient.invalidateQueries(['items']);
  },
});

Protected Route

typescript
// components/ProtectedRoute.tsx
'use client';

import { useAuth } from '@/hooks/useAuth';
import { redirect } from 'next/navigation';

export function ProtectedRoute({ children }: { children: React.ReactNode }) {
  const { user, isLoading } = useAuth();

  if (isLoading) return <LoadingSpinner />;
  if (!user) redirect('/login');

  return <>{children}</>;
}

Data Model Design Principles

typescript
// Base fields (auto-generated)
interface BaseDocument {
  _id: string;
  createdAt: Date;
  updatedAt: Date;
}

// User reference
interface Post extends BaseDocument {
  userId: string;        // Author ID (reference)
  title: string;
  content: string;
  tags: string[];        // Array field
  metadata: {            // Embedded object
    viewCount: number;
    likeCount: number;
  };
}

MCP Integration

Claude Code CLI (Recommended)

bash
claude mcp add bkend --transport http https://api.bkend.ai/mcp

.mcp.json (Per Project)

json
{
  "mcpServers": {
    "bkend": {
      "type": "http",
      "url": "https://api.bkend.ai/mcp"
    }
  }
}

Authentication

  • OAuth 2.1 + PKCE (browser auto-auth)
  • No API Key/env vars needed
  • First MCP request opens browser -> login to bkend console -> select Organization -> approve permissions
  • Verify: "Show my bkend projects"

## Environment Variables (.env.local)

NEXT_PUBLIC_BKEND_API_URL=https://api.bkend.ai/v1 NEXT_PUBLIC_BKEND_PROJECT_ID=your-project-id NEXT_PUBLIC_BKEND_ENV=dev


Note: Project ID is found in bkend console (console.bkend.ai).
Via MCP: "Show my project list" -> backend_project_list

## Limitations

❌ Complex backend logic (serverless function limits) ❌ Large-scale traffic (within BaaS limits) ❌ Custom infrastructure control ❌ Microservices architecture


## When to Upgrade

Move to **Enterprise Level** if you need:

→ "Traffic will increase significantly" → "I want to split into microservices" → "I need my own server/infrastructure" → "I need complex backend logic"


## bkit Features for Dynamic Level (v1.5.1)

### Output Style: bkit-pdca-guide (Recommended)

For optimal PDCA workflow experience, activate the PDCA guide style:

/output-style bkit-pdca-guide


This provides:
- PDCA status badges showing current phase progress
- Gap analysis suggestions after code changes
- Automatic next-phase guidance with checklists

### Agent Teams (2 Teammates)

Dynamic projects support Agent Teams for parallel PDCA execution:

| Role | Agents | PDCA Phases |
|------|--------|-------------|
| developer | bkend-expert | Do, Act |
| qa | qa-monitor, gap-detector | Check |

**To enable:**
1. Set environment: `CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1`
2. Start team mode: `/pdca team {feature}`
3. Monitor progress: `/pdca team status`

### Agent Memory (Auto-Active)

All bkit agents automatically remember project context across sessions.
No setup needed — agents use `project` scope memory for this codebase.

---

## Common Mistakes

| Mistake | Solution |
|---------|----------|
| CORS error | Register domain in bkend.ai console |
| 401 Unauthorized | Token expired, re-login or refresh token |
| Data not showing | Check collection name, query conditions |
| Type error | Sync TypeScript type definitions with schema |

Frequently asked questions

What does the Dynamic AI skill do?

Fullstack development with bkend.ai BaaS — authentication, database, API integration. Triggers: fullstack, BaaS, login, signup, database, web app

Why use Dynamic on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ww-w-ai/bkit-claude-code/tree/main/skills/dynamic. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Dynamic?

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 Dynamic?

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

Is the Dynamic AI skill free?

Yes. It is published on GitHub by ww-w-ai under the Apache-2.0 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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