supabase-data-explorer — Claude Code command: Supabase analysis
This command explores Supabase data and schema, runs read-only SQL queries, and prepares exports or visualizations. Use it when database checks belong in the project workflow.
npx claude-code-templates@latest --command database/supabase-data-explorerWhat supabase-data-explorer does
The command accepts a table name, a SQL query, or the --export and --inspect flags. It can inspect table structures, relationships, indexes, and constraints, then analyze data distribution, trends, and anomalies. It also looks for a few local SQL files and types or models directories to add project context.
Queries run through a connected Supabase MCP with read-only access. The workflow includes query validation, result limits, execution-plan analysis, and optimization suggestions. Its output can include data insights, exported files, visualizations, summary reports, and performance recommendations.
Without a connected Supabase MCP, the command cannot read the database: its Supabase access is provided through MCP and is restricted to read-only operations.
What it helps with
- inspect a Supabase table structure
- run a read-only SQL query
- trace relationships, indexes, and constraints
- export database data for analysis
- review a query execution plan
Example prompts for the agent
- Inspect the
[table-name]table with/supabase-data-explorer [table-name]. - Run a read-only query and explain the results with
/supabase-data-explorer --query [sql]. - Inspect the database and prepare an export with
/supabase-data-explorer --inspect --export.
How to install supabase-data-explorer
1claude-code-templates
npx claude-code-templates@latest --command database/supabase-data-explorer2Manually: put the files in place
.claude/commands/supabase-data-explorer.mdCall it with /supabase-data-explorer. For all projects use ~/.claude/commands/
Manually: put the files in place
~/.codex/prompts/supabase-data-explorer.mdCall it with /prompts:supabase-data-explorer. Codex marks this format deprecated in favour of skills
Manually: put the files in place
.github/prompts/supabase-data-explorer.prompt.mdManually: put the files in place
.gemini/commands/supabase-data-explorer.tomlGemini stores commands as TOML: the prompt text goes into the prompt field
Questions about supabase-data-explorer
How do I install supabase-data-explorer in Claude Code?
Run npx claude-code-templates@latest --command database/supabase-data-explorer. The command file is placed at .claude/commands/supabase-data-explorer.md. Connect Supabase MCP before using it with database data.
What does supabase-data-explorer do?
It explores Supabase tables, runs read-only SQL queries, and analyzes schema relationships and data quality. It can also prepare exports, visualizations, reports, and performance suggestions.
Can this command change Supabase data?
Supabase access is read-only, so the command is built for database inspection and analysis rather than data changes.
Source text
supabase-data-explorer.md · MIT
--- allowed-tools: Read, Write, Edit, Bash argument-hint: "[table-name] | --query [sql] | --export | --inspect" description: Explore and analyze Supabase database data with intelligent querying and visualization --- # 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 -5` existing SQL files for reference - Data models: !`find . -name "types" -o -name "models" -type d | head -3` application 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**: 1. **Database Discovery** - Explore table structures, analyze relationships, identify data patterns, assess data quality metrics 2. **Intelligent Querying** - Execute read-only queries via MCP, optimize query performance, provide result analysis, suggest query improvements 3. **Data Analysis** - Generate data insights, identify trends and anomalies, calculate statistical summaries, analyze data distribution 4. **Schema Inspection** - Examine table schemas, analyze foreign key relationships, assess index effectiveness, review constraint validations 5. **Export & Visualization** - Export data in multiple formats, create data visualizations, generate summary reports, optimize data presentation 6. **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.
© davila7 · MIT · davila7/claude-code-templates
