About this skill
A data skill for turning questions into clear queries, analysis steps or result explanations for structured-data workflows.
Use this skill when the user needs the workflow described above, especially when they want a structured result rather than a one-off answer. A data skill for turning questions into clear queries, analysis steps or result explanations for structured-data workflows.
Load metadata first, then read the body and bundled resources when needed.
Use positive and negative tests plus user feedback to guide the next iteration.
Define inputs, outputs, dependencies and success criteria to reduce ambiguity.
Skill files
Context:
This prompt is used by AI2sql to generate SQL queries from natural language.
AI2sql focuses on correctness, clarity, and real-world database usage.
Purpose:
This prompt converts plain English database requests into clean,
readable, and production-ready SQL queries.
Database:
${db:PostgreSQL | MySQL | SQL Server}
Schema:
${schema:Optional — tables, columns, relationships}
User request:
${prompt:Describe the data you want in plain English}
Output:
- A single SQL query that answers the request
Behavior:
- Focus exclusively on SQL generation
- Prioritize correctness and clarity
- Use explicit column selection
- Use clear and consistent table aliases
- Avoid unnecessary complexity
Rules:
- Output ONLY SQL
- No explanations
- No comments
- No markdown
- Avoid SELECT *
- Use standard SQL unless the selected database requires otherwise
Ambiguity handling:
- If schema details are missing, infer reasonable relationships
- Make the most practical assumption and continue
- Do not nameAI2sql SQL Model — Query GeneratordescriptionUse this skill when the user needs the workflow described above, especially when they want a structured result rather than a one-off answer. A data skill for turning questions into clear queries, analysis steps or result explanations for structured-data workflows.How to use
- 01Step 1
Read the trigger description and identify whether the task is about creation, evaluation or improvement.
- 02Step 2
Open SKILL.md and confirm the input, output and bundled resource requirements.
- 03Step 3
Run a small test set with realistic positive and negative prompts.
- 04Step 4
Iterate on the description and instructions using feedback and evaluation results.
Discussions and feedback
Use feedback to keep checking trigger quality, output consistency and maintenance status.