dangjin/bi-builder-skills/bi-builder
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Build BI dashboards from databases. Use when creating dashboards, charts, or analytics pages with Next.js + shadcn/ui + Recharts + Prisma.
Install
npx vskill@latest install dangjin/bi-builder-skills/bi-builderSKILL.md
BI 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
Workflow Flexibility
Skip phases based on project state and user needs:
| Scenario | Skip Phases | Starting Point | |
|---|---|---|---|
Project has prisma/schema.prisma | 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
prisma/schema.prismaexists in project - 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:
If Prisma is not installed, install it:
1.2 Initialize Prisma
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:
For MySQL:
For PostgreSQL:
For Supabase:
For SQLite:
After creating the file, tell the user:
For MySQL/PostgreSQL:
For Supabase:
1.4 Configure Prisma Schema
After user confirms .env is configured, update prisma/schema.prisma:
For MySQL/PostgreSQL/SQLite:
For Supabase (requires directUrl for migrations):
1.5 Pull Database Schema
1.6 Error Handling
When connection fails:
| Error Message | Possible Cause | Solution | |
|---|---|---|---|
Can't reach database server | Network/Firewall | Check host address and port accessibility | |
Access denied | Insufficient permissions | Verify username, password, and user privileges | |
Unknown database | Database doesn't exist | Confirm database name spelling | |
SSL connection error | SSL configuration | Add ?sslmode=require 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 | |
|---|---|---|
Decimal/Float/Int (amounts, quantities) | Sum, average, max/min | |
DateTime | Time series analysis, YoY/MoM comparisons | |
Enum/String (status, category) | Group statistics, distribution analysis | |
@relation | Join aggregations, multi-dimensional analysis | |
Boolean | Conversion rates, completion rates |
2.3 Generate Data Overview Report
Present database overview to user:
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)
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:
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:
Phase 4: Metrics Design
4.1 Define Metric Calculation Logic
Based on confirmed requirements, define calculation for each metric:
4.2 Time Series Metrics
This is the start of the file. Read the full SKILL.md on GitHub.
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