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Write a SQL query

Turn a plain-language question into SQL against your schema.

Use Write a SQL query

What it asks you for

What you want to knowrequired
In plain language.
Your schemarequired
Tables and columns it can use.
Dialect
Which SQL.

What it tells the AI to do

Write {{ dialect | default("postgres") }} SQL for this question:

{{ question }}

Schema:
{{ schema }}

Use only tables and columns present in the schema above. When the question needs
something that is not there, say what is missing and stop. An invented column
name produces a query that runs on a different database than the one you were
given, and the error surfaces hours later.

Return the query, then in two lines: what it assumes, and what it excludes.
Assumptions are where these go wrong (which rows count as active, whether
cancelled orders are revenue, what timezone a date is in).

Prefer a readable query over a clever one. Someone will edit this in six months
and it will not be you.

Why this works

Most SQL that comes back wrong is not wrong syntax, it is a wrong assumption about the data: which rows count as active, whether cancelled orders are revenue, what timezone a date column is in. The schema field exists to close that gap, and the query comes back with its assumptions stated so you can correct the assumption instead of debugging the SQL.

Questions

Why does it ask for my schema?
So it cannot invent a column. A query written against guessed table names runs against a different database than yours, and the error shows up long after you have stopped watching.
Which SQL dialects does it handle?
PostgreSQL, MySQL, SQLite, BigQuery and Snowflake. The dialect changes date functions and window syntax, which is where most portable-looking queries break.
  • sql
  • query
  • database
  • data

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  • Home
  • Pricing
  • AI Models
  • Image models
  • Voice models
  • Video models
  • Rankings
  • New models
  • Model status
  • Multi-Model Chat
  • Voice Mode
  • Voice HUD
  • Web Search
  • Image Generation
  • Video Generation
  • Audio Generation
  • Transcription
  • Drive
  • Credentials
  • Sharing
  • Workspaces
  • Tasks
  • Memory
  • Agents
  • Subagents
  • Automations
  • Skills
  • idapt Code
  • Code Execution
  • Computers
  • Computer Use
  • Computer Assist · Soon
  • Cloud Computers
  • Local AI
  • AI Gateway
  • API & SDK
  • CLI
  • MCP
  • Tunnels
  • All features →
  • LLM cost calculator
  • Token counter
  • Context window checker
  • Can I run it
  • Model picker quiz
  • Savings finder
  • Video cost estimator
  • Text to speech cost
  • Transcription cost
  • API endpoint tester
  • All free tools →
  • Blog
  • Use cases
  • Comparisons
  • Best of
  • Skills
  • Learn
  • Changelog
  • Help center
  • FAQ
  • Privacy
  • Compare all models
  • Support
  • idapt Code
  • Developers
  • Quickstarts
  • API reference
  • API pricing
  • CLI
  • MCP
  • Downloads
  • Desktop
  • Badges and embeds
© idapt[email protected]TermsPrivacy PolicyLegal noticeReport content
X (Twitter)