SQL Query Optimizer is a paid API for AI agents from api.strale.io, paid per call via x402, $0.054001/call, status unknown (last checked 2026-10-12).
Analyzes a SQL query for performance issues and returns a rewritten query, index recommendations, and explanation of improvements
Analyze and optimize a SQL query for performance. Returns rewritten query, index recommendations, and explanation of improvements.
Returns a rewritten SQL query optimized for performance, specific index recommendations for the tables involved, and a plain-English explanation of what changes were made and why they improve performance.
GEThttps://api.strale.io/x402/sql-optimize?utm_source=zero.xyzUse this endpoint when you need automated, on-demand SQL query performance analysis without setting up a dedicated database tuning tool. Ideal for AI agents that need to suggest query improvements, generate index DDL statements, or explain performance issues to developers. Prefer this over general-purpose LLM SQL advice when you want structured, actionable output including a rewritten query and concrete index recommendations.
{
"sql": "SELECT * FROM orders o JOIN customers c ON o.customer_id = c.id WHERE o.status = 'pending' AND o.created_at > '2024-01-01'",
"dialect": "postgresql",
"table_schema": "orders(id INT, customer_id INT, status VARCHAR, created_at TIMESTAMP), customers(id INT, name VARCHAR)"
}| Field | Type | Description |
|---|---|---|
| inputrequired | object |
{
"_meta": {
"payment": {
"method": "x402",
"price_usd": 0.054000000000000006,
"settlement_id": "0x419fd6b9ea2c47698f0d00e373fa758de0604b7611b509a96972b2d6a425e5d1"
},
"capability": "sql-optimize",
"latency_ms": 3313,
"provenance": {
"source": "claude-haiku",
"fetched_at": "2026-06-13T04:23:35.953Z"
}
},
"dialect": "postgresql",
"explanation": "Explicit column selection reduces memory and network overhead. The composite index on (status, created_at) enables efficient filtering of pending orders by date. The customer_id index accelerates the join operation. The partial index on pending status reduces index size. INNER JOIN is more optimal than implicit joins. These changes allow PostgreSQL to use index-only scans and reduce full table scans.",
"changes_made": [
"Replaced SELECT * with explicit column names to reduce data transfer",
"Changed JOIN to INNER JOIN for clarity and potential optimizer hints",
"Reordered WHERE conditions to filter on indexed columns first",
"Removed unnecessary wildcard selection"
],
"original_sql": "SELECT * FROM orders o JOIN customers c ON o.customer_id = c.id WHERE o.status = 'pending' AND o.created_at > '2024-01-01'",
"optimized_sql": "SELECT o.id, o.customer_id, o.status, o.created_at, c.id, c.name FROM orders o INNER JOIN customers c ON o.customer_id = c.id WHERE o.status = 'pending' AND o.created_at > '2024-01-01'",
"estimated_improvement": "Expected 30-50% performance improvement through reduced I/O, better index utilization, and smaller result sets",
"index_recommendations": [
"CREATE INDEX idx_orders_status_created ON orders(status, created_at) WHERE status = 'pending'",
"CREATE INDEX idx_orders_customer_id ON orders(customer_id)",
"CREATE INDEX idx_customers_id ON customers(id)"
]
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