Query remote databases via natural language to SQL over SSH.
npx skills add https://github.com/zrt-ai-lab/opencode-skills --skill smart-query
Please help me install this Agent Skill. Skill: smart-query Source: https://github.com/zrt-ai-lab/opencode-skills/tree/main/smart-query Command: npx skills add https://github.com/zrt-ai-lab/opencode-skills --skill smart-query
Remote data access often requires manual, insecure, or brittle steps to run queries against production databases. This skill enables secure, SSH-tunneled connections and a natural language to SQL workflow to speed up data retrieval and analysis.
Run a basic test to connect to the configured database and perform a sample query.
High-intent search queries and answers about installing and using this skill.
Querying a remote database securely through an SSH tunnel involves establishing an encrypted connection using paramiko and sshtunnel, then executing data retrieval operations without directly exposing your database credentials.
Translating natural language to SQL for ad-hoc data queries involves converting user intent into executable database syntax, allowing you to fetch specific rows and verify data quality without writing manual SQL statements.
Yes, you can use PyMySQL to explore table structure on a production database by executing schema discovery operations through a secure SSH-tunneled connection to safely inspect remote table definitions.
You need SSH tunneling to run NL-to-SQL queries securely when accessing remote production databases, as it provides the encrypted connectivity required to safely execute natural language translated SQL statements.
The best way to fetch the latest rows from a production table without exposing credentials is to use SSH-tunneled connectivity combined with a natural language to SQL workflow to speed up secure data retrieval.
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