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demos
Interactive demos for custom AI functions. Use when: demo, example, walkthrough, show me, how does this work, try it, hands-on, tutorial.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
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Interactive demos for custom AI functions. Use when: demo, example, walkthrough, show me, how does this work, try it, hands-on, tutorial.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
| name | demos |
| description | Interactive demos for custom AI functions. Use when: demo, example, walkthrough, show me, how does this work, try it, hands-on, tutorial. |
| parent_skill | cortex-ai-function-studio |
Interactive walkthroughs organized by feature — each demo highlights specific studio capabilities so you can jump straight to what interests you. Not every demo runs the full create → evaluate → optimize pipeline; some focus on a single capability.
Load from main skill when user intent matches DEMO: "demo", "example", "walkthrough", "show me", "how does this work".
Prerequisites: Before routing to a demo, ensure the user has a database and schema with CREATE TABLE/FUNCTION privileges. If not already established, the demo sub-skill will prompt for location.
If environment == snowsight, ask user:
Which demo would you like to try?
1. **Pseudo-Labeling & Teacher-Student Distillation** (~10 min)
Start with unlabeled insurance claims, generate ground truth labels
with a strong teacher model (Claude Opus), then build a cheap student
model and measure how closely it reproduces teacher decisions.
Features: Synthetic Data (pseudo-label), Create, Evaluate
2. **Prompt Optimization** (~10 min)
Take a policy-conditioned ticket router where cheap models fail badly
on unfamiliar company vocabulary, then watch prompt optimization close
the accuracy gap through prompt evolution and Pareto cost/quality analysis.
Features: Create, Optimize, Pareto Analysis
---
The following demos are currently available in the CLI only.
They may be supported in Snowsight in a future update.
3. **Quick Start: Create & Evaluate** (~5 min)
Build a toxicity classifier and measure its accuracy — the fastest
way to experience the core workflow. Uses built-in exact_match metric.
Features: Create (direct mode), Evaluate
4. **Custom Evaluation Metrics** (~5 min)
Build a legal contract field extractor and create a weighted composite
metric that scores 4 fields independently — governing law, parties,
effective date, expiration date. See how custom metrics give richer
signal than simple exact_match.
Features: Create, Custom Composite Metrics, Evaluate
5. **Multimodal: Document Extraction** (~10 min)
Extract structured fields from SEC 10-K filing PDFs, build a custom
composite metric for multi-field scoring, and evaluate extraction
accuracy with per-field analysis.
Features: Multimodal (PDFs), Custom Metrics, Evaluate
6. **Agent Research: Pre/Post-Processing** (~10 min) [Experimental]
Build a PII redaction function using Agent Research mode — the agent
searches the web for state-of-the-art techniques, proposes multiple
SQL UDF architectures with pre- and post-processing around AI_COMPLETE,
and you pick the approach. Then optimize the entire function body —
prompts, model, and SQL logic.
Features: Create (Agent Research mode, web search, SQL pre/post-processing), Optimize (body mode)
If environment == cli (or not set), ask user:
Which demo would you like to try?
1. **Quick Start: Create & Evaluate** (~5 min)
Build a toxicity classifier and measure its accuracy — the fastest
way to experience the core workflow. Uses built-in exact_match metric.
Features: Create (direct mode), Evaluate
2. **Pseudo-Labeling & Teacher-Student Distillation** (~10 min)
Start with unlabeled insurance claims, generate ground truth labels
with a strong teacher model (Claude Opus), then build a cheap student
model and measure how closely it reproduces teacher decisions.
Features: Synthetic Data (pseudo-label), Create, Evaluate
3. **Custom Evaluation Metrics** (~5 min)
Build a legal contract field extractor and create a weighted composite
metric that scores 4 fields independently — governing law, parties,
effective date, expiration date. See how custom metrics give richer
signal than simple exact_match.
Features: Create, Custom Composite Metrics, Evaluate
4. **Prompt Optimization** (~10 min)
Take a policy-conditioned ticket router where cheap models fail badly
on unfamiliar company vocabulary, then watch prompt optimization close
the accuracy gap through prompt evolution and Pareto cost/quality analysis.
Features: Create, Optimize, Pareto Analysis
5. **Multimodal: Document Extraction** (~10 min)
Extract structured fields from SEC 10-K filing PDFs, build a custom
composite metric for multi-field scoring, and evaluate extraction
accuracy with per-field analysis.
Features: Multimodal (PDFs), Custom Metrics, Evaluate
6. **Agent Research: Pre/Post-Processing** (~10 min) [Experimental]
Build a PII redaction function using Agent Research mode — the agent
searches the web for state-of-the-art techniques, proposes multiple
SQL UDF architectures with pre- and post-processing around AI_COMPLETE,
and you pick the approach. Then optimize the entire function body —
prompts, model, and SQL logic.
Features: Create (Agent Research mode, web search, SQL pre/post-processing), Optimize (body mode)
⚠️ STOP: Wait for user selection before proceeding.
Route based on the demo name the user selected (numbering differs between Snowsight and CLI menus):
If Quick Start: Load classification/SKILL.md
If Pseudo-Labeling: Load insurance-claim-routing/SKILL.md
If Custom Metrics: Load legal-doc-extraction/SKILL.md
If Prompt Optimization: Load policy-conditioned-routing/SKILL.md
If Multimodal Documents: Load pdf-field-extraction/SKILL.md
If Agent Research: Load redaction/SKILL.md
Each demo will:
DEMO_ prefix)Not every demo runs every step of the create → evaluate → optimize pipeline. Demos are designed to be fast and focused on the feature they showcase.
Note: Demos execute real SQL and create real objects in your Snowflake account. All demo objects use the DEMO_ prefix for easy identification and cleanup.
Routed to specific demo sub-skill (e.g., classification/SKILL.md, insurance-claim-routing/SKILL.md)
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 job status. Triggers: ai function builder, custom ai function, user defined ai function, build my own llm function, evaluate ai function, tune ai function, optimize ai function, demo ai function, resume ai function job, image classification, document analysis, multimodal 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.
Quick Start demo: Build a toxicity classifier and evaluate it — the fastest way to experience the core create → evaluate workflow.
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.
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.
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.