Cursor Snowflake 编码规范：来自 PatrickJS/awesome-cursorrules (40k stars) 的 sno，适用于各类文档与内容的智能化处理。
Cursor Snowflake 编码规范：来自 PatrickJS/awesome-cursorrules (40k stars) 的 sno，适用于各类文档与内容的智能化处理。
**文件来源:** PatrickJS/awesome-cursorrules → `rules/snowflake-cortex-ai-cursorrules-prompt-file.mdc`
**原仓库:** https://github.com/PatrickJS/awesome-cursorrules
**评分:** ⭐ 仓库 40k stars (社区最权威 Cursor rules 合集)
把 `snowflake-cortex-ai-cursorrules-prompt-file.mdc` 这条 Cursor 编码规则打包成可调用的 AI skill,帮你把代码生成统一到一致的标准上。
> 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
...(完整内容在原仓库)...有问题或建议,在本 skill 下留言。
把 `snowflake-cortex-ai-cursorrules-prompt-file.mdc` 这条 Cursor 编码规则打包成可调用的 AI skill,帮你把代码生成统一到一致的标准上。
> Cursor rules for Snowflake Cortex AI Functions (AI_COMPLETE, AI_CLASSIFY, AI_EXTRACT, etc.) and Cortex Search for RAG applications.