An AI-powered SQL specialist for explaining execution plans, optimizing queries, and converting natural language into database commands.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install sql-explain-kay
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install sql-explain-kay using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is SQL Query Explain?
SQL Query Explain is a comprehensive AI coding agent skill designed to bridge the gap between complex database queries and developer productivity. As a core part of the Openclaw Skills ecosystem, it functions as a virtual SQL Expert that provides deep insights into query execution plans for PostgreSQL, MySQL, and SQLite. Whether you are troubleshooting slow performance or need to generate standard SQL from natural language descriptions, this skill streamlines the database development lifecycle.
By leveraging local parsing libraries such as sqlparse, the skill ensures data privacy while delivering highly technical and actionable feedback. It goes beyond simple formatting by identifying expensive operations like full table scans and nested loops, helping developers implement index-driven optimizations effectively within their Openclaw Skills enabled workflows.
SQL Query Explain Use Cases
- Analyzing slow-running queries to identify missing indexes or inefficient join types.
- Converting complex business requirements described in plain text into executable SQL statements.
- Formatting and beautifying messy legacy SQL code for better readability and maintenance.
- Debugging syntax errors in SQL scripts with actionable correction suggestions.
- Understanding the cost and estimated row impact of a query before executing it in production environments.
How SQL Query Explain Works
- The user provides a SQL query or a natural language description through a platform supporting Openclaw Skills.
- The skill identifies the specific intent: whether to explain, generate, format, or check syntax.
- For performance analysis, it utilizes sqlparse to build a syntax tree and applies built-in rule sets to interpret EXPLAIN output.
- It evaluates table scan methods, index usage, and join strategies to calculate query costs and performance bottlenecks.
- It generates a structured performance report including specific optimization suggestions and formatted code for the developer.
SQL Query Explain Setup
To integrate this skill into your environment, ensure you have Python installed and the necessary parsing libraries.
# Install the required dependencies
pip install sqlparse
# If using sqlean modules for extended analysis
pip install sqlean
After installation, add the SQL Query Explain trigger keywords to your agent configuration settings to enable the skill functionality.
SQL Query Explain Data Schema & Taxonomy
The skill processes SQL strings and returns structured reports categorized by execution metrics and optimization rules. Below is the metadata taxonomy used for reports:
| Attribute | Description |
|---|---|
| Total Cost | The estimated execution cost calculated from the database engine's plan. |
| Scan Type | Identifies Seq Scan, Index Scan, Index Only Scan, or Full Table Scan. |
| Row Estimation | The estimated vs. actual number of rows processed by the query. |
| Performance Issues | A list of identified bottlenecks such as expensive joins or missing indexes. |
| Optimization Tips | Actionable steps to improve the query performance and resource efficiency. |
SQL Query Explain Advanced Features
- Cross-dialect support for PostgreSQL, MySQL, and SQLite execution plan formats.
- Fully local execution with no external API dependencies, ensuring maximum data security and privacy for your Openclaw Skills.
- Tiered access levels (Pro/Team) for history tracking and collaborative team optimization.
- Intelligent intent recognition to distinguish between DQL (SELECT) and DML (INSERT/UPDATE) operations.
- Detailed breakdown of join types including Hash Join, Nested Loop, and Merge Join.
SKILL.md
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