Claude-skill-registry bi-builder
Build BI dashboards from databases. Use when creating dashboards, charts, or analytics pages with Next.js + shadcn/ui + Recharts + Prisma.
git clone https://github.com/majiayu000/claude-skill-registry
T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/bi-builder" ~/.claude/skills/majiayu000-claude-skill-registry-bi-builder && rm -rf "$T"
skills/data/bi-builder/SKILL.mdBI Builder
Build BI dashboards from existing databases, from data exploration to full implementation.
Tech Stack
| Layer | Technology |
|---|---|
| Frontend Framework | Next.js 16 (App Router) |
| UI Components | shadcn/ui + Tailwind CSS |
| Charts | Recharts |
| ORM | Prisma |
| Database | MySQL / PostgreSQL / Supabase / SQLite |
Core Workflow
Database Connection → Schema Exploration → Requirements Dialog → Metrics Design → Chart Planning → Page Implementation
Workflow Flexibility
Skip phases based on project state and user needs:
| Scenario | Skip Phases | Starting Point |
|---|---|---|
Project has | Phase 1 | Go directly to Phase 2 schema analysis |
| User has clear requirements and metrics | Phase 3 | Go directly to Phase 4 metrics design |
| Only need a single chart component | Phases 1-5 | Read recharts-guide.md and implement |
| Only need data query logic | Phases 5-6 | End after metrics design |
Decision criteria:
- Check if
exists in projectprisma/schema.prisma - Ask user "Do you have specific metrics requirements?"
- Ask user "Do you need a full dashboard or just a single chart?"
Phase 1: Database Connection
1.1 Check and Install Prisma
First, check if Prisma is already installed in the project:
# Check if prisma is in package.json dependencies grep -q '"prisma"' package.json && echo "Prisma installed" || echo "Prisma not installed"
If Prisma is not installed, install it:
# Install Prisma as dev dependency npm install prisma --save-dev # Install Prisma Client npm install @prisma/client
1.2 Initialize Prisma
# Initialize Prisma (creates prisma/schema.prisma and .env) npx prisma init
Note: If
prisma/schema.prisma already exists, skip this step.
1.3 Create .env with Placeholders
⚠️ Security Note: Never ask users to share database credentials directly.
First, ask user which database type they use, then create
.env file with placeholders:
Which database are you using? 1. MySQL 2. PostgreSQL 3. Supabase 4. SQLite
For MySQL:
# Database Connection # Please fill in your database credentials below DATABASE_URL="mysql://YOUR_USERNAME:YOUR_PASSWORD@YOUR_HOST:3306/YOUR_DATABASE" # Example: # DATABASE_URL="mysql://root:password123@localhost:3306/myapp_db"
For PostgreSQL:
# Database Connection # Please fill in your database credentials below DATABASE_URL="postgresql://YOUR_USERNAME:YOUR_PASSWORD@YOUR_HOST:5432/YOUR_DATABASE" # Example: # DATABASE_URL="postgresql://postgres:password123@localhost:5432/myapp_db"
For Supabase:
# Supabase Database Connection # Find your connection string in: Supabase Dashboard → Project Settings → Database → Connection string → URI DATABASE_URL="postgresql://postgres.YOUR_PROJECT_REF:YOUR_PASSWORD@aws-0-YOUR_REGION.pooler.supabase.com:6543/postgres?pgbouncer=true" # Direct connection (for migrations) DIRECT_URL="postgresql://postgres.YOUR_PROJECT_REF:YOUR_PASSWORD@aws-0-YOUR_REGION.pooler.supabase.com:5432/postgres" # Example: # DATABASE_URL="postgresql://postgres.abcdefghijkl:MyPassword123@aws-0-us-east-1.pooler.supabase.com:6543/postgres?pgbouncer=true"
For SQLite:
# Database Connection DATABASE_URL="file:./dev.db"
After creating the file, tell the user:
For MySQL/PostgreSQL:
I've created .env file with placeholders. Please fill in your actual database credentials: - YOUR_USERNAME → your database username - YOUR_PASSWORD → your database password - YOUR_HOST → database host (e.g., localhost or IP address) - YOUR_DATABASE → database name Tip: Use a read-only account for safety. Let me know when you've filled in the credentials.
For Supabase:
I've created .env file with Supabase placeholders. To get your connection string: 1. Go to Supabase Dashboard → Your Project 2. Click "Project Settings" (gear icon) 3. Go to "Database" section 4. Copy the "Connection string" → "URI" format 5. Replace [YOUR-PASSWORD] with your database password Let me know when you've filled in the credentials.
1.4 Configure Prisma Schema
After user confirms .env is configured, update
prisma/schema.prisma:
For MySQL/PostgreSQL/SQLite:
generator client { provider = "prisma-client-js" } datasource db { provider = "mysql" // or postgresql, sqlite url = env("DATABASE_URL") }
For Supabase (requires directUrl for migrations):
generator client { provider = "prisma-client-js" } datasource db { provider = "postgresql" url = env("DATABASE_URL") directUrl = env("DIRECT_URL") }
1.5 Pull Database Schema
# Pull schema from existing database npx prisma db pull # Generate Prisma Client npx prisma generate
1.6 Error Handling
When connection fails:
| Error Message | Possible Cause | Solution |
|---|---|---|
| Network/Firewall | Check host address and port accessibility |
| Insufficient permissions | Verify username, password, and user privileges |
| Database doesn't exist | Confirm database name spelling |
| SSL configuration | Add to DATABASE_URL |
Post-schema pull checks:
- If few tables (< 3) → Confirm connection to correct database
- If no relationships → May be legacy database, need manual relationship analysis
Phase 2: Schema Exploration & Analysis
2.1 Read Generated Schema
After
prisma db pull, read prisma/schema.prisma and analyze:
- Table structure: What tables exist, what fields each has
- Data types: Numeric, datetime, categorical fields
- Relationships: Table associations (one-to-many, many-to-many)
- Indexes: Which fields are indexed, indicating common query dimensions
2.2 Identify Metric Potential
Identify buildable metrics by field type:
| Field Type | Metric Potential |
|---|---|
// (amounts, quantities) | Sum, average, max/min |
| Time series analysis, YoY/MoM comparisons |
/ (status, category) | Group statistics, distribution analysis |
| Join aggregations, multi-dimensional analysis |
| Conversion rates, completion rates |
2.3 Generate Data Overview Report
Present database overview to user:
## Database Overview ### Core Tables - **orders** (Orders table): 12 fields, related to users, products - **users** (Users table): 8 fields - **products** (Products table): 10 fields, related to categories ### Available Metrics **Transaction Metrics** - Total revenue (orders.total) - Order count (orders.count) - Average order value (orders.total / orders.count) **User Metrics** - Total users (users.count) - New users (users.created_at) **Product Metrics** - Sales ranking (order_items.quantity) - Category distribution (categories) ### Time Dimensions - orders.created_at → Supports daily/weekly/monthly analysis - users.created_at → Supports user growth analysis
Phase 3: Requirements Dialog
3.1 Questioning Strategy
Principle: Ask one question at a time, prefer multiple choice, ask in rounds.
Round 1: Industry Identification (Highest Priority)
Question 0: What industry is your business in? Options: E-commerce/Retail / SaaS Software / Financial Services / Content/Media / Education / Healthcare / Logistics/Supply Chain / Other
Industry determines metric direction:
| Industry | Core Focus | Typical Metrics |
|---|---|---|
| E-commerce/Retail | Transaction conversion | GMV, AOV, Repeat purchase rate, Return rate, Inventory turnover |
| SaaS Software | User retention | MRR/ARR, Churn Rate, LTV, CAC, DAU/MAU |
| Financial Services | Risk & return | AUM, Bad debt rate, Delinquency rate, Approval rate |
| Content/Media | Traffic monetization | PV/UV, Session duration, Bounce rate, Ad revenue, Paid conversion |
| Education | Learning outcomes | Course completion rate, Renewal rate, Referral rate, Study time |
| Healthcare | Service efficiency | Visit volume, Bed turnover, Return visit rate, Satisfaction |
| Logistics/Supply Chain | Operational efficiency | Order fulfillment rate, Delivery time, Warehouse cost, Turnover rate |
Round 2: Core Metrics Confirmation (Use AskUserQuestion tool)
Based on industry + schema analysis, generate metric options:
Question 1: Based on [industry] context and database analysis, which core metrics matter most to you? (Multiple select) Options: [Combine industry typical metrics + schema-supported metrics]
Question 2: What's your primary time granularity for analysis? Options: Daily / Weekly / Monthly / Quarterly
Round 3: Conditional Follow-ups
Only ask when conditions are met:
| Condition | Follow-up |
|---|---|
| Schema has category tables | "Do you need category filtering?" |
| User selected multiple metrics | "Do you need metric comparisons (YoY/MoM)?" |
| Data volume may be large | "Do you need export functionality?" |
Round 4: Confirmation
Show requirements confirmation template, ask "Is the above understanding correct?"
3.2 Data Structure Limitation Handling
When user requirements don't match data, clearly inform:
| User Request | Missing Data | Response |
|---|---|---|
| Regional distribution analysis | No region field | "Database has no region information, cannot implement. Should we analyze by [available dimension] instead?" |
| Trend analysis | No datetime field | "Missing datetime field, can only do static statistics, cannot show trends." |
| User profiling | Limited user fields | "User data is limited, can only track basic metrics (count, new users)." |
3.3 Requirements Confirmation Template
Organize user requirements:
## Requirements Confirmation ### Dashboard Name Sales Analytics Dashboard ### Core Metrics (KPI Cards) 1. Total Revenue - orders.total sum 2. Order Count - orders count 3. AOV - Total Revenue / Order Count 4. New Users - users count (this month) ### Chart Requirements | Chart | Type | Data Source | Dimension | |-------|------|-------------|-----------| | Revenue Trend | Line Chart | orders.total | By day/month | | Category Sales | Pie Chart | categories | Category distribution | | Top 10 Products | Bar Chart | products | Sales ranking | | Order Status | Pie Chart | orders.status | Status distribution | ### Filters - Date range picker - Product category dropdown - Order status multi-select ### Other Requirements - CSV export support - Responsive layout
Phase 4: Metrics Design
4.1 Define Metric Calculation Logic
Based on confirmed requirements, define calculation for each metric:
// lib/metrics.ts // KPI Metrics export async function getKPIs(startDate: Date, endDate: Date) { const [revenue, orders, users] = await Promise.all([ // Total revenue prisma.order.aggregate({ where: { createdAt: { gte: startDate, lte: endDate }, status: { not: 'CANCELLED' } }, _sum: { total: true }, }), // Order count prisma.order.count({ where: { createdAt: { gte: startDate, lte: endDate }, status: { not: 'CANCELLED' } }, }), // New users prisma.user.count({ where: { createdAt: { gte: startDate, lte: endDate } }, }), ]); return { revenue: Number(revenue._sum.total) || 0, orders, avgOrderValue: orders > 0 ? Number(revenue._sum.total) / orders : 0, newUsers: users, }; }
4.2 Time Series Metrics
// Aggregate by time granularity export async function getRevenueTrend( startDate: Date, endDate: Date, granularity: 'day' | 'week' | 'month' ) { const format = { day: '%Y-%m-%d', week: '%Y-%u', month: '%Y-%m', }[granularity]; return prisma.$queryRaw` SELECT DATE_FORMAT(created_at, ${format}) as period, SUM(total) as revenue, COUNT(*) as orders FROM orders WHERE created_at BETWEEN ${startDate} AND ${endDate} AND status != 'CANCELLED' GROUP BY period ORDER BY period `; }
4.3 Grouped Metrics
// Category distribution export async function getCategoryDistribution(startDate: Date, endDate: Date) { return prisma.$queryRaw` SELECT c.name as category, SUM(oi.quantity * oi.price) as revenue, SUM(oi.quantity) as quantity FROM order_items oi JOIN products p ON oi.product_id = p.id JOIN categories c ON p.category_id = c.id JOIN orders o ON oi.order_id = o.id WHERE o.created_at BETWEEN ${startDate} AND ${endDate} AND o.status != 'CANCELLED' GROUP BY c.id, c.name ORDER BY revenue DESC `; }
Before writing complex queries → Must read data-layer.md#data-aggregation-queries
Phase 5: Chart Planning
5.1 Visualization Type Selection
| Data Type | Recommended Component | Reason |
|---|---|---|
| Time trends | LineChart / AreaChart | Show change over time |
| Distribution | PieChart | Intuitive proportion display |
| Rankings | BarChart (horizontal) | Easy comparison and reading |
| Multi-metric comparison | ComposedChart | Combine bar and line charts |
| Status distribution | PieChart / BarChart | Show counts per status |
| Detailed records | DataTable | Sortable, filterable, paginated list |
| Transaction logs | DataTable | Search, filter, export capabilities |
| Item listings | DataTable | With actions (view, edit, delete) |
5.2 Layout Type Selection
Ask user about their dashboard purpose to recommend a layout:
What is the primary purpose of this dashboard? 1. Executive Overview - High-level KPIs for quick decision-making 2. Operations Monitoring - Real-time data and alerts 3. Deep Analysis - Multi-dimensional filtering and exploration 4. Period Comparison - YoY/MoM comparison and benchmarking
| Layout Type | Best For | Key Features |
|---|---|---|
| Executive Dashboard | C-level, managers | KPI cards + main trend + distribution |
| Operational Dashboard | Operations team | Real-time status + live table + alerts |
| Analytical Dashboard | Analysts | Sidebar filters + drill-down + detailed table |
| Comparison Dashboard | Strategy, planning | Period selector + dual charts + change analysis |
Before implementing layout → Must read dashboard-patterns.md#common-bi-layout-patterns
5.3 Layout Structure
Default Executive Dashboard layout:
┌─────────────────────────────────────────────────────────┐ │ Filter Bar: [Date Range] [Category] [Status] [Apply] │ ├─────────┬─────────┬─────────┬───────────────────────────┤ │ KPI 1 │ KPI 2 │ KPI 3 │ KPI 4 │ │ Revenue │ Orders │ AOV │ New Users │ ├─────────────────────────────┬───────────────────────────┤ │ │ │ │ Revenue Trend (Line) │ Category Dist (Pie) │ │ lg:col-span-2 │ │ │ │ │ ├─────────────────────────────┴───────────────────────────┤ │ │ │ Top 10 Products (Bar Chart) │ │ │ ├─────────────────────────────────────────────────────────┤ │ Order Details (DataTable) │ └─────────────────────────────────────────────────────────┘
Phase 6: Page Implementation
6.1 Directory Structure
app/dashboard/ ├── page.tsx # Main page ├── loading.tsx # Loading skeleton └── components/ ├── kpi-cards.tsx # KPI cards ├── revenue-chart.tsx # Revenue trend chart ├── category-pie.tsx # Category pie chart ├── top-products.tsx # Product ranking ├── data-table.tsx # Reusable DataTable component ├── columns.tsx # Table column definitions ├── filters.tsx # Filters └── export-button.tsx # Export button lib/ ├── prisma.ts # Prisma client └── metrics.ts # Metric calculation functions app/api/dashboard/ ├── route.ts # Combined data API ├── kpi/route.ts # KPI API ├── revenue/route.ts # Revenue trend API └── categories/route.ts # Category data API
6.2 Implementation Order
- Prisma client →
lib/prisma.ts - Metric functions →
lib/metrics.ts - API routes →
app/api/dashboard/ - KPI cards → Simplest, verify data flow first
- Chart components → Implement one by one
- Filters → Add interactivity
- Export functionality → Complete last
6.3 Component Implementation
Chart components must use
"use client" and ResponsiveContainer:
"use client"; import { ResponsiveContainer, LineChart, Line, XAxis, YAxis, Tooltip } from "recharts"; export function RevenueChart({ data }: { data: { period: string; revenue: number }[] }) { return ( <ResponsiveContainer width="100%" height={300}> <LineChart data={data}> <XAxis dataKey="period" /> <YAxis /> <Tooltip /> <Line type="monotone" dataKey="revenue" stroke="hsl(var(--primary))" /> </LineChart> </ResponsiveContainer> ); }
Before creating chart components → Must read recharts-guide.md for the corresponding chart type
Before creating DataTable components → Must read table-patterns.md
Before implementing page layout → Must read dashboard-patterns.md
Before implementing export functionality → Must read export-patterns.md
Quick Reference
Prisma Commands
npx prisma db pull # Pull schema from database npx prisma generate # Generate Prisma Client npx prisma studio # Open database management UI
Chart Color Scheme
const CHART_COLORS = [ "hsl(221, 83%, 53%)", // blue "hsl(142, 71%, 45%)", // green "hsl(38, 92%, 50%)", // amber "hsl(0, 84%, 60%)", // red "hsl(262, 83%, 58%)", // purple ];
Responsive Breakpoints
// KPI row <div className="grid grid-cols-1 sm:grid-cols-2 lg:grid-cols-4 gap-4"> // Main chart area <div className="grid grid-cols-1 lg:grid-cols-3 gap-4"> <div className="lg:col-span-2">{/* Large chart */}</div> <div>{/* Small chart */}</div> </div>
Reference Document Usage Rules
⚠️ Do not read all documents upfront. Only load on-demand when entering the corresponding phase.
Required Reading Triggers
| Trigger Timing | Must Read | Section |
|---|---|---|
| Entering Phase 4 (before writing Prisma queries) | data-layer.md | |
| Entering Phase 5 (when selecting chart types) | recharts-guide.md | Corresponding chart type section |
| Entering Phase 6 (before implementing page layout) | dashboard-patterns.md | |
| When user needs DataTable | table-patterns.md | Full document |
| When user needs export functionality | export-patterns.md | Full document |
Document Index
- data-layer.md - Prisma queries, Schema analysis, API design
- recharts-guide.md - Chart code examples by type
- table-patterns.md - DataTable with sorting, filtering, pagination
- dashboard-patterns.md - Page layouts, KPI cards, filters
- export-patterns.md - CSV export, image export