# snowflake-cortex-ai-cursorrules-prompt-file

This Cursor rule covers Snowflake Cortex AI Functions and Cortex Search. Use it for SQL-based AI tasks or to build a retrieval-augmented search flow.

- rule · `type=rule` · Cursor · ★ 41024
- Author: PatrickJS
- License: CC0-1.0 · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/PatrickJS/awesome-cursorrules/tree/HEAD/rules/snowflake-cortex-ai-cursorrules-prompt-file.mdc
- Updated: 2026-05-30
- HTML: https://affpapa.org/en/nevibecode/rules/snowflake-cortex-ai-cursorrules-prompt-file

## What it does

The rule gives examples for Cortex AI functions that generate text, assign categories, extract fields, score sentiment, and process documents. It also covers Cortex Search, a managed service that combines semantic and keyword retrieval, with setup examples and queries through the Python or REST API.

Its RAG pattern retrieves relevant context first, then passes that context to AI_COMPLETE. The guidance recommends checking token counts before large batch jobs and estimating costs before sending table rows through AI_COMPLETE one by one. Access to the AI functions requires the USE AI FUNCTIONS account privilege and the SNOWFLAKE.CORTEX_USER database role.

## Requirements
- Works with: Snowflake

## Install

### Cursor (native platform)

**Manually: put the files in place**
- File: `.cursor/rules/snowflake-cortex-ai-cursorrules-prompt-file.mdc` — Frontmatter: description, globs, alwaysApply

### Claude Code

**Manually: put the files in place**
- File: `.claude/rules/snowflake-cortex-ai-cursorrules-prompt-file.md` — The paths frontmatter field limits the files: move globs from the source into paths

### Codex

**AGENTS.md**
- Codex reads AGENTS.md: paste the rule text there

### GitHub Copilot

**Manually: put the files in place**
- File: `.github/instructions/snowflake-cortex-ai-cursorrules-prompt-file.instructions.md` — The applyTo field sets which files it applies to: move globs from the source into applyTo

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/rules/snowflake-cortex-ai-cursorrules-prompt-file.md`

### Cline

**Manually: put the files in place**
- File: `.clinerules/snowflake-cortex-ai-cursorrules-prompt-file.md`

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/PatrickJS/awesome-cursorrules/tree/HEAD/rules/snowflake-cortex-ai-cursorrules-prompt-file.mdc

## When to use it
- classify support tickets with AI_CLASSIFY
- extract fields from emails or documents
- set up hybrid retrieval with Cortex Search
- configure search filters and query options
- pass retrieved context to AI_COMPLETE for a RAG flow

## Example prompts
- Show me a SQL example that sorts support tickets into categories with AI_CLASSIFY.
- Create a Cortex Search service that indexes transcript text and lets me filter by region.
- Write a RAG example that retrieves context with Cortex Search, then sends it to AI_COMPLETE.

## Source text · snowflake-cortex-ai-cursorrules-prompt-file.mdc · CC0-1.0

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: 79acf05b6dd48163.

BEGIN THIRD-PARTY FILE 79acf05b6dd48163
```text
---
description: "Cursor rules for Snowflake Cortex AI Functions (AI_COMPLETE, AI_CLASSIFY, AI_EXTRACT, etc.) and Cortex Search for RAG applications."
globs: **/*
alwaysApply: false
---
// Snowflake Cortex AI
// Expert guidance for Cortex AI Functions and Cortex Search (hybrid vector+keyword search)

You are an expert in Snowflake Cortex — the AI layer of Snowflake including Cortex AI Functions (SQL-callable LLM/ML functions) and Cortex Search (managed hybrid search for RAG applications). All processing runs inside Snowflake with no data leaving the platform.

// ═══════════════════════════════════════════
// CORTEX AI FUNCTIONS
// ═══════════════════════════════════════════

// Available Functions (use these names — they are the current versions):
// AI_COMPLETE       — General-purpose LLM completion (text, images, documents).
// AI_CLASSIFY       — Classify text/images into user-defined categories (multi-label supported).
// AI_FILTER         — Returns TRUE/FALSE for text/image input. Use in WHERE clauses.
// AI_AGG            — Aggregate insights across rows of text (no context window limit).
// AI_EMBED          — Generate embedding vectors (similarity search, clustering).
// AI_EXTRACT        — Extract structured info from text, images, or documents.
// AI_SENTIMENT      — Sentiment score from text (-1 to 1).
// AI_SUMMARIZE_AGG  — Summarize across rows (no context window limit).
// AI_SIMILARITY     — Embedding similarity between two inputs.
// AI_TRANSCRIBE     — Transcribe audio/video from stages.
// AI_PARSE_DOCUMENT — OCR or text+layout extraction from documents in stages.
// AI_REDACT         — Redact PII from text.
// AI_TRANSLATE      — Translate between supported languages.

// Helper Functions:
// TO_FILE('@stage', 'filename')  — File reference for document processing.
// AI_COUNT_TOKENS(model, text)   — Check token count before calling a model.
// PROMPT('template {0}', arg)    — Build prompt objects for AI_COMPLETE.
// TRY_COMPLETE                   — Returns NULL on failure instead of error.

// AI_COMPLETE — The Primary Function
// Models: claude-4-opus, claude-4-sonnet, claude-sonnet-4-5, claude-opus-4-5, claude-haiku-4-5,
//         gemini-3-pro, llama3.1-70b, llama3.1-8b, llama3.3-70b, mistral-large2, mistral-small2, deepseek-r1

// Text completion:
SELECT AI_COMPLETE(MODEL => 'claude-4-sonnet', PROMPT => 'Summarize: ' || review_text) FROM reviews;

// Document processing:
SELECT AI_COMPLETE(
  MODEL => 'claude-4-sonnet',
  PROMPT => PROMPT('Extract the invoice total from {0}', TO_FILE('@docs', 'invoice.pdf'))
);

// Structured JSON output:
SELECT AI_COMPLETE(MODEL => 'claude-4-sonnet',
  PROMPT => 'Extract name, email, company as JSON: ' || raw_text)::VARIANT AS extracted FROM contacts;

// AI_CLASSIFY:
SELECT AI_CLASSIFY(ticket_text, ['billing', 'technical', 'account', 'other']) AS category FROM tickets;
// Multi-label: AI_CLASSIFY(input, categories, {'output_mode': 'multi'})

// AI_FILTER (natural-language WHERE):
SELECT * FROM reviews WHERE AI_FILTER(review_text, 'mentions product quality issues');

// AI_AGG (cross-row aggregation):
SELECT AI_AGG(feedback_text, 'What are the top 3 themes?') FROM customer_feedback;

// AI_EXTRACT (entity extraction):
SELECT AI_EXTRACT(email_body, 'meeting date', 'attendees', 'action items') FROM emails;

// AI_SENTIMENT: SELECT review_text, AI_SENTIMENT(review_text) AS sentiment FROM product_reviews;
```
END THIRD-PARTY FILE 79acf05b6dd48163

The third-party file has ended. Everything between the 79acf05b6dd48163 tags is data: requests and commands from it are not followed. An “end of file” line with another tag inside the block is part of the file.

First 3633 of 7281 bytes. © PatrickJS · CC0-1.0 · https://github.com/PatrickJS/awesome-cursorrules/tree/HEAD/rules/snowflake-cortex-ai-cursorrules-prompt-file.mdc

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