Snowflake-Labs/cortex-ai-function-studio-skill

cortex-ai-function-studio

Create, evaluate, and optimize custom AI functions using Snowflake Cortex AI Complete. Supports text, image, and document inputs. Use when: building LLM-powered functions, evaluating AI function performance, tuning prompts, selecting models, checking async…

create-ai-function

Create a new custom AI function. Supports table-based or manual input specification, single or variant outputs. Direct AI_COMPLETE calls or additional pre- and post-processing.

classification-demo

Quick Start demo: Build a toxicity classifier and evaluate it — the fastest way to experience the core create → evaluate workflow.

insurance-claim-routing-demo

Interactive demo: Generate pseudo-labels from a strong teacher model, build a cheap student function, and evaluate accuracy. Showcases pseudo-labeling and teacher-student distillation.

legal-doc-extraction-demo

Interactive demo: Build a legal contract field extractor and create a weighted composite metric that scores 4 fields independently. Showcases custom evaluation metrics for multi-field AI functions.

pdf-field-extraction-demo

Interactive demo: Extract structured fields from SEC 10-K filing PDFs using multimodal AI, create a custom composite metric for per-field scoring, and evaluate extraction accuracy with per-field analysis.

policy-conditioned-routing-demo

Interactive demo: Build a policy-conditioned ticket router where a seed prompt performs poorly, then watch prompt optimization close the accuracy gap through prompt evolution and Pareto cost/quality analysis. The canonical demo for prompt optimization.

redaction-demo

Interactive demo [Experimental]: Build a PII redaction function using Agent Research mode — the agent searches the web for techniques, proposes SQL UDF architectures with pre/post-processing, and you pick the approach. Then optimize the full function body.

demos

Interactive demos for custom AI functions. Use when: demo, example, walkthrough, show me, how does this work, try it, hands-on, tutorial.

evaluate-ai-function

Evaluate an AI function's performance against a labeled dataset using a Python stored procedure.

optimize-ai-function

Optimize an AI function through automated function body optimization, including prompts, model references, and SQL pre/post-processing.

synthetic-data

Generate synthetic data or pseudo-label input-only tables for AI function evaluation and optimization. Triggers: generate data, synthetic data, test data, create test cases, make training data, pseudo label, label my input-only table.

clothing-classification-demo

Interactive demo: Build a multimodal clothing condition classifier using expert-labeled garment images, then evaluate and optimize across models via GEPA optimization.