query-builder

Original：🇺🇸 English
Translated

Convert natural language questions into SQL queries. Activates when users ask data questions in plain English like "show me users who signed up last week" or "find orders over $100".

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Sourceclidey/whodb
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NPX Install

npx skill4agent add clidey/whodb query-builder

Tags

Translated version includes tags in frontmatter
sql-generationnatural-language-to-sqldatabase-queriesquery-builderdata-safety

SKILL.md Content

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Query Builder

Convert natural language questions into SQL queries using the database schema.

When to Use

Activate when user asks questions like:
  • "Show me all users who signed up last month"
  • "Find orders greater than $100"
  • "Which products have low inventory?"
  • "Get the top 10 customers by total spend"

Workflow

1. Understand the Schema

Before generating SQL, always check the table structure:
whodb_tables(connection="...") → Get available tables
whodb_columns(table="relevant_table") → Get column names and types

2. Identify Intent

Parse the natural language request:
  • Subject: What entity? (users, orders, products)
  • Filter: What conditions? (last month, > $100, active)
  • Aggregation: Count, sum, average, max, min?
  • Grouping: By what dimension?
  • Ordering: Sort by what? Ascending/descending?
  • Limit: How many results?

3. Map to Schema

  • Match entities to table names
  • Match attributes to column names
  • Identify foreign key joins needed

4. Generate SQL

Build the query following SQL best practices:
sql
SELECT columns
FROM table
[JOIN other_table ON condition]
WHERE filters
[GROUP BY columns]
[HAVING aggregate_condition]
ORDER BY column [ASC|DESC]
LIMIT n;

5. Execute and Present

whodb_query(query="generated SQL")

Translation Patterns

Natural LanguageSQL Pattern
"last week/month/year"
WHERE date_col >= DATE_SUB(NOW(), INTERVAL 1 WEEK)
"more than X" / "greater than X"
WHERE col > X
"top N"
ORDER BY col DESC LIMIT N
"how many"
SELECT COUNT(*)
"total" / "sum of"
SELECT SUM(col)
"average"
SELECT AVG(col)
"for each" / "by"
GROUP BY col
"between X and Y"
WHERE col BETWEEN X AND Y
"contains" / "like"
WHERE col LIKE '%term%'
"starts with"
WHERE col LIKE 'term%'
"is empty" / "is null"
WHERE col IS NULL
"is not empty"
WHERE col IS NOT NULL

Date Handling by Database

PostgreSQL

sql
WHERE created_at >= NOW() - INTERVAL '7 days'
WHERE created_at >= DATE_TRUNC('month', CURRENT_DATE)

MySQL

sql
WHERE created_at >= DATE_SUB(NOW(), INTERVAL 7 DAY)
WHERE created_at >= DATE_FORMAT(NOW(), '%Y-%m-01')

SQLite

sql
WHERE created_at >= DATE('now', '-7 days')
WHERE created_at >= DATE('now', 'start of month')

Examples

"Show me users who signed up this month"

sql
SELECT * FROM users
WHERE created_at >= DATE_TRUNC('month', CURRENT_DATE)
ORDER BY created_at DESC;

"Find the top 5 products by sales"

sql
SELECT p.name, SUM(oi.quantity) as total_sold
FROM products p
JOIN order_items oi ON p.id = oi.product_id
GROUP BY p.id, p.name
ORDER BY total_sold DESC
LIMIT 5;

"How many orders per customer?"

sql
SELECT customer_id, COUNT(*) as order_count
FROM orders
GROUP BY customer_id
ORDER BY order_count DESC;

Safety Rules

  • Always use LIMIT for exploratory queries (default: 100)
  • Never generate DELETE, UPDATE, or DROP unless explicitly requested
  • Warn if query might return large result sets
  • Use table aliases for readability in JOINs