aiskillstore/data-exploration
skills/dbxstudio/data-exploration/SKILL.md
Systematic database and table profiling for DBX Studio. Use when a user wants to understand their data, explore schema structure, or profile a dataset.
$ install --global
skillsauthnpx skillsauth add aiskillstore/marketplace data-explorationInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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TrivyContainer and dependency vulnerability scanner
95%
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SemgrepStatic code analysis for vulnerabilities
95%
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95%
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Snyk (dep)Open source security scanning
50%
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50%
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OWASP Dep-Check
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Last scanned: Apr 1, 2026, 9:41 AM58.3s2 files scanned
SKILL.md
- name:
- data-exploration
- description:
- Systematic database and table profiling for DBX Studio. Use when a user wants to understand their data, explore schema structure, or profile a dataset.
Data Exploration — DBX Studio
Exploration Workflow
Phase 1: Schema Discovery
Start with read_schema to list all tables, then describe_table for each table of interest.
1. read_schema(schema_name: "public")
2. describe_table(table_name: "<each table>")
3. get_table_stats(table_name: "<table>")
Phase 2: Table Profiling
For each table, gather:
- Row count
- Column names and types
- Sample data via
get_table_data - Null counts and distributions
Phase 3: Relationship Discovery
Look for foreign key patterns:
- Columns named
*_idlinking to other tables - Common join patterns:
users.id → orders.user_id
Quality Scoring
| Score | Completeness | |-------|-------------| | Green | > 95% populated | | Yellow | 80–95% populated | | Orange | 50–80% populated | | Red | < 50% populated |
Common Exploration Queries
Row count
SELECT COUNT(*) AS row_count FROM "public"."table_name";
Column null rates
SELECT
COUNT(*) AS total,
COUNT(column_name) AS non_null,
ROUND(100.0 * COUNT(column_name) / COUNT(*), 2) AS pct_filled
FROM "public"."table_name";
Distinct values
SELECT column_name, COUNT(*) AS frequency
FROM "public"."table_name"
GROUP BY 1
ORDER BY 2 DESC
LIMIT 20;
Date range
SELECT MIN(created_at), MAX(created_at) FROM "public"."table_name";
Output Format
After exploration, present a structured summary:
- Tables: list with row counts
- Key relationships: how tables connect
- Data quality flags: any columns with high null rates
- Suggested next queries: what the user might want to know next
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