sql-helper

# SQL Helper ## Quick Start Write, explain, optimize, and debug SQL queries. Support MySQL, PostgreSQL, SQL Server, and SQLite syntax. Always clarify the database engine when syntax differs. Prioritize readable, performant queries. ## Workflow 1. Understand the goal: data retrieval, aggregation, join, update, or schema design 2. Confirm the database engine if syntax-sensitive (MySQL vs PostgreSQL vs SQL Server) 3. Gather table structure: column names, types, relationships 4. Write the query with proper formatting and aliases 5. Explain each part of the query 6. Suggest indexes or optimizations if applicable ## Examples **Example 1: Aggregation Query** Input: "Write a query to calculate total revenue by month from the orders table, for 2026 only" Output: ``` SQL QUERY ========= Task: Monthly revenue for 2026 Engine: MySQL (compatible with PostgreSQL) SELECT YEAR(order_date) AS year, MONTH(order_date) AS month, COUNT(*) AS total_orders, SUM(total_amount) AS revenue, AVG(total_amount) AS avg_order_value FROM orders WHERE order_date >= '2026-01-01' AND order_date < '2027-01-01' GROUP BY YEAR(order_date), MONTH(order_date) ORDER BY year, month; EXPLANATION ----------- - WHERE: Filters to 2026 using range comparison (index-friendly, avoids YEAR() on column) - GROUP BY: Groups rows by year and month - SUM/COUNT/AVG: Calculates revenue, order count, and average order value - ORDER BY: Sorts chronologically PERFORMANCE TIP: - Ensure index on: orders(order_date) - Range filter (>= and <) is more efficient than YEAR(order_date) = 2026 ``` **Example 2: Debug a Query** Input: "This query is slow, can you optimize it?" ```sql SELECT * FROM orders o JOIN customers c ON c.id = o.customer_id WHERE YEAR(o.created_at) = 2026 ``` Output: ``` OPTIMIZATION ============ Issues Found: 1. SELECT * — fetching all columns when likely only a few are needed 2. YEAR(o.created_at) — function on column prevents index usage 3. Missing index hint Optimized Query: SELECT o.id, o.total_amount, o.created_at, c.name, c.email FROM orders o JOIN customers c ON c.id = o.customer_id WHERE o.created_at >= '2026-01-01' AND o.created_at < '2027-01-01'; Recommended Indexes: - CREATE INDEX idx_orders_created_at ON orders(created_at); - CREATE INDEX idx_orders_customer_id ON orders(customer_id); Expected Improvement: 5-10x faster on large tables (>100K rows) ``` ## Tools - Use `Read` to load SQL files or schema definitions - Use `Write` to save queries to .sql files - Use `Grep` to search for table or column references in the codebase ## Error Handling - If table structure is unknown → ask for schema or column names - If database engine not specified → default to MySQL and note syntax differences - If query has syntax errors → identify and fix with explanation - If query logic seems wrong → flag potential issues before executing ## Connectors (Optional) This skill works standalone. When connected to external tools, it unlocks additional capabilities: | Connector | What it enables | |-----------|----------------| | ~~database | Run queries directly against live databases and return real results | | ~~BI tool | Export query output into dashboards and scheduled reports | | ~~spreadsheet | Pull table schemas from linked spreadsheets or push query results to sheets | | ~~data warehouse | Access warehouse catalog, table metadata, and execution plans for optimization | ## Rules - Always format queries with proper indentation and uppercase keywords - Use explicit column names — never SELECT * in production queries - Prefer JOIN syntax over subqueries where possible for readability - Always suggest relevant indexes for WHERE and JOIN columns - Use parameterized queries (placeholders) when values come from user input — never concatenate - Explain the query logic in plain language - Note engine-specific syntax differences when relevant (e.g., LIMIT vs TOP) - For UPDATE/DELETE queries, always suggest testing with SELECT first ## Output Template ``` SQL QUERY ========= Task: [What the query does] Engine: [MySQL / PostgreSQL / SQL Server / SQLite] [Formatted SQL query] EXPLANATION ----------- - [Line-by-line or section explanation] PERFORMANCE TIP: - [Index suggestions or optimization notes] ``` ## Related Skills - **data-summarizer** -- after querying data, summarize and analyze the results for insights - **data-cleaner** -- clean and standardize messy data before or after SQL operations - **chart-generator** -- visualize query results with charts and graphs