sql-queries-tool
Expert SQL query generation for DBX Studio. Use when writing, optimizing, or debugging SQL queries against user database connections.
Best use case
sql-queries-tool is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Expert SQL query generation for DBX Studio. Use when writing, optimizing, or debugging SQL queries against user database connections.
Teams using sql-queries-tool should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/sql-queries-tool/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How sql-queries-tool Compares
| Feature / Agent | sql-queries-tool | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Expert SQL query generation for DBX Studio. Use when writing, optimizing, or debugging SQL queries against user database connections.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# SQL Query Expert — DBX Studio
This project supports multiple database backends via user connections. Always write dialect-appropriate SQL.
## Supported Dialects
| Dialect | Provider |
|---------|----------|
| PostgreSQL | Default / Railway |
| Snowflake | Via MCP connector |
| BigQuery | Via MCP connector |
| Databricks | Via MCP connector |
| MySQL | Via connection string |
| SQLite | Via connection string |
## Query Patterns
### Safe SELECT with limit
Always add LIMIT unless the user explicitly wants all rows:
```sql
SELECT * FROM "schema"."table" LIMIT 100;
```
### CTEs for complex queries
```sql
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
```sql
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
```sql
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:
| Tool | When 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"
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