A developer-focused agent skill that converts natural language requests into schema-accurate, dialect-specific SQL queries.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install text-to-sql-jipeng
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 text-to-sql-jipeng 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 Text to SQL?
The Text to SQL skill acts as an intelligent translator between plain English requirements and complex SQL statements. It addresses a common bottleneck for developers and data analysts who know what data they need but want to skip manual query drafting. As a key utility within Openclaw Skills, this asset helps autonomous agents and developers translate user intent into precise code quickly.
This skill is deliberately scoped for translation and formulation rather than execution. It requires a database schema alongside the natural language query to map fields accurately, completely avoiding the generation of hallucinated columns. It ensures robust outputs with clean formatting, explicit aliases, and compliance with specified database dialects.
Text to SQL Use Cases
- Creating optimized queries from business-level descriptions without writing boilerplate SQL.
- Explaining legacy or complex queries to team members with step-by-step inline annotations.
- Producing alternative query options, such as comparing subqueries to CTE structures, for educational or optimization purposes.
- Accelerating data analysis preparation by mapping requirements directly to known schemas.
How Text to SQL Works
- Schema Check: The skill reviews the input data for explicit table schemas, CREATE TABLE strings, or previous database outputs. It requests clarification if schema information is missing.
- Intent Parsing: It maps language indicators to appropriate SQL clauses (e.g., mapping 'how many' to COUNT or 'sorted by' to ORDER BY).
- Join Resolution: It maps foreign key relationships and joins tables accurately, choosing among INNER, LEFT, or RIGHT joins.
- SQL Generation & Validation: It writes the final query, validating that all columns match the schema, aliases are correctly declared, and syntax parameters match the database dialect.
Text to SQL Setup
To get started with this skill, configure it using your local agent runtime. This utility is accessible through the catalog of Openclaw Skills.
Install the skill with the CLI interface:
claw skill install text-to-sql
Ensure that database schema documentation or table structures are available in your query context to guarantee correct translations.
Text to SQL Data Schema & Taxonomy
The skill formats inputs and schemas into an organized representation before translation:
| Data Component | Description | Format |
|---|---|---|
| Schema Map | Physical table names mapped to columns | table_name -> {column_name: data_type} |
| SQL Dialect | The SQL format targeted by the engine | PostgreSQL, MySQL, SQLite, etc. |
| Query Mode | Output format and depth | Default, Explain, or Alternatives |
Outputs are organized using explicit table aliases (e.g., o.order_id) to avoid ambiguous column references.
Text to SQL Advanced Features
- Dialect Flexibility: Formats SQL natively for PostgreSQL, MySQL, SQLite, and other major engines.
- Schema Verification: Rigid compliance rules that halt query generation if table schemas are unknown, protecting against syntax errors.
- Explain Sub-mode: Provides inline annotations directly within the output code block to describe query operations.
- Query Alternatives: Offers multiple syntax strategies (CTEs vs. subqueries) for performance comparison.
SKILL.md
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