sql-queries
Expert SQL query generation for DBX Studio. Use when writing, optimizing, or debugging SQL queries against user database connections.
Best use case
sql-queries is best used when you need a repeatable AI agent workflow instead of a one-off prompt. It is especially useful for teams working in multi. Expert SQL query generation for DBX Studio. Use when writing, optimizing, or debugging SQL queries against user database connections.
Expert SQL query generation for DBX Studio. Use when writing, optimizing, or debugging SQL queries against user database connections.
Users should expect a more consistent workflow output, faster repeated execution, and less time spent rewriting prompts from scratch.
Practical example
Example input
Use the "sql-queries" skill to help with this workflow task. Context: Expert SQL query generation for DBX Studio. Use when writing, optimizing, or debugging SQL queries against user database connections.
Example output
A structured workflow result with clearer steps, more consistent formatting, and an output that is easier to reuse in the next run.
When to use this skill
- Use this skill when you want a reusable workflow rather than writing the same prompt again and again.
When not to use this skill
- Do not use this when you only need a one-off answer and do not need a reusable workflow.
- Do not use it if you cannot install or maintain the related files, repository context, or supporting tools.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/sql-queries/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How sql-queries Compares
| Feature / Agent | sql-queries | 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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