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sql-query

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Generate, explain, and optimize SQL queries. Use when user asks to write SQL, optimize a query, or explain what a query does.

التثبيت

التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.

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المصدر

deskwand

deskwand/agent

فتح مستودع GitHub عرض مستودعات المنشئ

تنزيل

تشغيل في Manus

المهن ذات الصلةSOC

استنادا إلى تصنيف SOC المهني

مصممو قواعد البياناتمهن الحاسوب والرياضيات·SOC 15-1243

SKILL.md

readonly

name	sql-query
description	Generate, explain, and optimize SQL queries. Use when user asks to write SQL, optimize a query, or explain what a query does.
version	1.0.0
author	deskwand
license	MIT
metadata	{"tags":["SQL","Database","Queries","MySQL","PostgreSQL","SQLite"]}
allowed-tools	read,shell

SQL Query Tools

Write, review, and optimize SQL queries.

When to use

User asks to "write a SQL query to..."
User has an existing query and wants optimization
User needs to explain or debug a SQL query
User wants to design a schema or add indexes

Query Generation Guidelines

1. Always ask for schema context first

Before writing a query, identify:

Database engine: PostgreSQL, MySQL, SQLite, etc.
Table structure: columns, types, relationships
Data volume: approximate row counts

2. Write safe queries

-- ✅ Parameterized
SELECT * FROM users WHERE id = ?;

-- ❌ String interpolation (SQL injection risk)
SELECT * FROM users WHERE id = '${userId}';

3. Include EXPLAIN for performance

EXPLAIN ANALYZE SELECT ...

4. Common patterns

-- Join with aggregation
SELECT u.name, COUNT(o.id) as order_count
FROM users u
LEFT JOIN orders o ON u.id = o.user_id
GROUP BY u.id, u.name
HAVING COUNT(o.id) > 5
ORDER BY order_count DESC;

-- Window functions
SELECT
  department,
  employee,
  salary,
  RANK() OVER (PARTITION BY department ORDER BY salary DESC) as rank
FROM employees;

-- CTE (Common Table Expression)
WITH monthly_sales AS (
  SELECT DATE_TRUNC('month', created_at) as month, SUM(amount) as total
  FROM orders
  GROUP BY 1
)
SELECT month, total, LAG(total) OVER (ORDER BY month) as prev_month
FROM monthly_sales;

-- Upsert (PostgreSQL)
INSERT INTO users (id, email, name)
VALUES (1, 'a@b.com', 'Alice')
ON CONFLICT (id) DO UPDATE
SET email = EXCLUDED.email, name = EXCLUDED.name;

Query Review Checklist

When reviewing an existing query:

Correctness: Does it return the expected results? Check JOIN conditions, WHERE filters, NULL handling.
Performance: Are there missing indexes? Can subqueries be rewritten as JOINs? Is LIMIT used where appropriate?
Safety: No SQL injection vectors. No SELECT * in production code.
Readability: Proper formatting, meaningful aliases, comments for complex logic.

Engine-Specific Notes

Feature	PostgreSQL	MySQL	SQLite
String concat	`\|\|`	`CONCAT()`	`\|\|`
Limit + offset	`LIMIT n OFFSET m`	`LIMIT m, n`	`LIMIT n OFFSET m`
Current timestamp	`NOW()`	`NOW()`	`datetime('now')`
Boolean type	`BOOLEAN`	`TINYINT(1)`	`INTEGER` (0/1)
JSON support	`JSONB`	`JSON`	`TEXT` + json functions

Constraints

Never execute DROP, TRUNCATE, or DELETE without explicit user confirmation
Always show estimated row impact before UPDATE/DELETE
Generate queries with parameterized placeholders, not literal values

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name	sql-query
description	Generate, explain, and optimize SQL queries. Use when user asks to write SQL, optimize a query, or explain what a query does.
version	1.0.0
author	deskwand
license	MIT
metadata	{"tags":["SQL","Database","Queries","MySQL","PostgreSQL","SQLite"]}
allowed-tools	read,shell

SQL Query Tools

Write, review, and optimize SQL queries.

When to use

User asks to "write a SQL query to..."
User has an existing query and wants optimization
User needs to explain or debug a SQL query
User wants to design a schema or add indexes

Query Generation Guidelines

1. Always ask for schema context first

Before writing a query, identify:

Database engine: PostgreSQL, MySQL, SQLite, etc.
Table structure: columns, types, relationships
Data volume: approximate row counts

2. Write safe queries

-- ✅ Parameterized
SELECT * FROM users WHERE id = ?;

-- ❌ String interpolation (SQL injection risk)
SELECT * FROM users WHERE id = '${userId}';

3. Include EXPLAIN for performance

EXPLAIN ANALYZE SELECT ...

4. Common patterns

-- Join with aggregation
SELECT u.name, COUNT(o.id) as order_count
FROM users u
LEFT JOIN orders o ON u.id = o.user_id
GROUP BY u.id, u.name
HAVING COUNT(o.id) > 5
ORDER BY order_count DESC;

-- Window functions
SELECT
  department,
  employee,
  salary,
  RANK() OVER (PARTITION BY department ORDER BY salary DESC) as rank
FROM employees;

-- CTE (Common Table Expression)
WITH monthly_sales AS (
  SELECT DATE_TRUNC('month', created_at) as month, SUM(amount) as total
  FROM orders
  GROUP BY 1
)
SELECT month, total, LAG(total) OVER (ORDER BY month) as prev_month
FROM monthly_sales;

-- Upsert (PostgreSQL)
INSERT INTO users (id, email, name)
VALUES (1, 'a@b.com', 'Alice')
ON CONFLICT (id) DO UPDATE
SET email = EXCLUDED.email, name = EXCLUDED.name;

Query Review Checklist

When reviewing an existing query:

Correctness: Does it return the expected results? Check JOIN conditions, WHERE filters, NULL handling.
Performance: Are there missing indexes? Can subqueries be rewritten as JOINs? Is LIMIT used where appropriate?
Safety: No SQL injection vectors. No SELECT * in production code.
Readability: Proper formatting, meaningful aliases, comments for complex logic.

Engine-Specific Notes

Feature	PostgreSQL	MySQL	SQLite
String concat	`\|\|`	`CONCAT()`	`\|\|`
Limit + offset	`LIMIT n OFFSET m`	`LIMIT m, n`	`LIMIT n OFFSET m`
Current timestamp	`NOW()`	`NOW()`	`datetime('now')`
Boolean type	`BOOLEAN`	`TINYINT(1)`	`INTEGER` (0/1)
JSON support	`JSONB`	`JSON`	`TEXT` + json functions

Constraints

Never execute DROP, TRUNCATE, or DELETE without explicit user confirmation
Always show estimated row impact before UPDATE/DELETE
Generate queries with parameterized placeholders, not literal values