Query PolarDB (MySQL) databases using natural language instead of writing SQL.
npx skills add https://github.com/liutao96/skill --skill polardb-query-assistant
Please help me install this Agent Skill. Skill: PolarDB Query Assistant Source: https://github.com/liutao96/skill/tree/main/PolarDB_Query Command: npx skills add https://github.com/liutao96/skill --skill polardb-query-assistant
Natural-language querying of PolarDB databases replaces manual SQL writing, making data access faster and less error-prone.
Use a natural-language prompt like 'Show me today's total orders' to fetch results.
High-intent search queries and answers about installing and using this skill.
The assistant translates your plain text prompts into SQL queries, executes them against your PolarDB MySQL instance using a Python bridge, and returns the data. This enables instant ad-hoc data exploration without manual SQL syntax.
Yes, natural language querying on PolarDB is designed for ad-hoc data exploration and reporting. You can ask questions like 'Show me today's total orders' to instantly fetch aggregated results without writing manual SQL queries.
Yes, you need to configure a db_config.json file containing your host, user, and password to connect. The assistant uses this configuration alongside a Python bridge script to establish a connection and execute SQL queries on your PolarDB MySQL instance.
Yes, natural language querying supports smart aggregations including SUM, COUNT, MAX, and MIN on PolarDB. This allows you to quickly generate insights and calculate totals or counts directly from your plain text questions without writing manual SQL.
Natural language querying automatically handles multiple schemas in PolarDB MySQL instances, such as those matching the sry_2025sz_yh_* pattern. This allows you to perform multi-schema analysis seamlessly by asking questions across different schemas without specifying them manually in SQL.
The best way to run ad-hoc queries on PolarDB without writing SQL syntax is using a natural language query assistant. It converts your plain text questions into SQL, executes them via a Python bridge, and returns results instantly for quick data exploration.
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