Supabase Data Explorer
Explore and analyze Supabase database data with intelligent querying and visualization
npx claude-code-templates@latest --command database/supabase-data-explorer Scanned by NVIDIA SkillSpector
Automated static analysis (no LLM) · v2.12.0 · 2026-10-23
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No observations.
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Content
Supabase Data Explorer
Explore and analyze Supabase database with intelligent querying and data insights: $ARGUMENTS
Current Data Context
- Supabase MCP: Connected with read-only access for safe data exploration
- Target table: Analysis of $ARGUMENTS for data exploration scope
- Local queries: !
find . -name "*.sql" | head -5existing SQL files for reference - Data models: !
find . -name "types" -o -name "models" -type d | head -3application data structures
Task
Execute comprehensive database exploration with intelligent analysis and insights:
Exploration Focus: Use $ARGUMENTS to specify table inspection, SQL query execution, data export, or comprehensive database inspection
Data Exploration Framework:
- Database Discovery - Explore table structures, analyze relationships, identify data patterns, assess data quality metrics
- Intelligent Querying - Execute read-only queries via MCP, optimize query performance, provide result analysis, suggest query improvements
- Data Analysis - Generate data insights, identify trends and anomalies, calculate statistical summaries, analyze data distribution
- Schema Inspection - Examine table schemas, analyze foreign key relationships, assess index effectiveness, review constraint validations
- Export & Visualization - Export data in multiple formats, create data visualizations, generate summary reports, optimize data presentation
- Performance Analysis - Analyze query execution plans, identify performance bottlenecks, suggest optimization strategies, monitor resource usage
Advanced Features: Interactive data exploration, automated insight generation, data quality assessment, relationship mapping, trend analysis.
Safety Features: Read-only operations, query validation, result limiting, performance monitoring, error handling.
Output: Comprehensive data exploration with insights, optimized queries, export files, and performance recommendations.