Marketplace sql-queries-tool

Expert SQL query generation for DBX Studio. Use when writing, optimizing, or debugging SQL queries against user database connections.

install
source · Clone the upstream repo
git clone https://github.com/aiskillstore/marketplace
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/aiskillstore/marketplace "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/dbxstudio/sql-queries-tool" ~/.claude/skills/aiskillstore-marketplace-sql-queries-tool && rm -rf "$T"
manifest: skills/dbxstudio/sql-queries-tool/SKILL.md
source content

SQL Query Expert — DBX Studio

This project supports multiple database backends via user connections. Always write dialect-appropriate SQL.

Supported Dialects

DialectProvider
PostgreSQLDefault / Railway
SnowflakeVia MCP connector
BigQueryVia MCP connector
DatabricksVia MCP connector
MySQLVia connection string
SQLiteVia connection string

Query Patterns

Safe SELECT with limit

Always add LIMIT unless the user explicitly wants all rows:

SELECT * FROM "schema"."table" LIMIT 100;

CTEs for complex queries

WITH ranked AS (
  SELECT *, ROW_NUMBER() OVER (PARTITION BY category ORDER BY created_at DESC) AS rn
  FROM orders
)
SELECT * FROM ranked WHERE rn = 1;

Aggregations

SELECT
  DATE_TRUNC('month', created_at) AS month,
  COUNT(*) AS total,
  SUM(amount) AS revenue
FROM orders
GROUP BY 1
ORDER BY 1 DESC;

Window Functions

SELECT
  user_id,
  amount,
  SUM(amount) OVER (PARTITION BY user_id ORDER BY created_at) AS running_total
FROM transactions;

Tool Usage in DBX Studio AI

The AI has access to these tools — always use them rather than guessing:

ToolWhen to Use
read_schema
First call — understand table structure
get_table_data
Preview rows before writing complex queries
execute_query
Run SELECT queries (SELECT/WITH only)
describe_table
Get column details, FK relationships
get_table_stats
Row counts, distributions
generate_chart
Visualize query results

Query Safety Rules

  • Only SELECT and WITH (CTEs) are permitted via
    execute_query
  • Always quote identifiers:
    "schema"."table"."column"
  • Add LIMIT automatically unless the user asks for all data
  • Validate table/column names exist via
    read_schema
    or
    describe_table
    first

Response Format

  1. Execute tool to get data
  2. Answer the user's question directly with the result
  3. Show SQL in ```sql blocks only if the user asks "how" or "show me the query"
  4. Present numbers clearly: "There are 1,247 orders this month"