무료GitHub에 공개

bigquery-ai-ml

Write SQL that uses BigQuery’s built-in machine learning and generative AI for forecasting, anomaly detection, identifying drivers of change, searching by meaning, and classifying or summarizing text stored in your data.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

원문원문 설명 보기

Leverages BigQuery's built-in machine learning and GenAI capabilities for advanced data analytics. Use when you need to write SQL queries that perform time-series forecasting, predict values, detect outliers or anomalies, find key drivers, perform semantic search or vector search, classify text, calculate similarity, summarize content, translate language, evaluate models, filter by semantic conditions, measure the causal effect of an intervention, compute correlations between columns, detect change points or structural breaks, extract trend or seasonality components, or leverage generative AI capabilities in BigQuery. Do not use for general BigQuery dataset, table, or job management requests.

google/skills

연동 도구Google Cloud

설치 방법 보기

이럴 때 유용합니다

Forecasting future values from time-series data
Detecting anomalies and investigating drivers of change
Searching documents by meaning
Classifying and summarizing text in tables
Measuring the impact of an intervention

포함된 파일(22)

SKILL.md3.8 KB
references/ai_agg.md3.5 KB
references/ai_causal_effect.md11.2 KB
references/ai_classify.md3.7 KB
references/ai_detect_anomalies.md3.7 KB
references/ai_evaluate.md2.2 KB
references/ai_forecast.md4.4 KB
references/ai_generate_embedding.md1.6 KB
references/ai_generate_table.md2.9 KB
references/ai_generate.md2.8 KB
references/ai_if.md2.0 KB
references/ai_key_drivers.md4.5 KB
references/ai_score.md1.9 KB
references/ai_search.md3.7 KB
references/ai_similarity.md2.7 KB
references/ml_contribution_analysis.md4.8 KB
references/ml_correlation.md8.9 KB
references/ml_detect_change_points.md5.5 KB
references/ml_seasonality.md6.6 KB
references/ml_trend.md4.1 KB
references/remote_models.md872 B
references/vector_search.md4.0 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

BigQuery AI & ML

BigQuery integrates with Vertex AI to provide powerful machine learning and generative AI capabilities directly within SQL queries using built-in functions like AI.FORECAST, AI.KEY_DRIVERS, AI.DETECT_ANOMALIES, and AI.GENERATE.

Reference Directory

Functions Reference:
- AI.AGG: ai_agg.md - Multi-row semantic aggregation and summarization.
- AI.CAUSAL_EFFECT: ai_causal_effect.md - Quantifies the impact of an intervention on a time series.
- AI.CLASSIFY: ai_classify.md - Classify text.
- AI.DETECT_ANOMALIES: ai_detect_anomalies.md - Detect anomalies.
- AI.EVALUATE: ai_evaluate.md - Evaluate models.
- AI.FORECAST: ai_forecast.md - Time-series forecasting.
- AI.GENERATE: ai_generate.md - Generate text using LLMs.
- AI.GENERATE_EMBEDDING: ai_generate_embedding.md - Generate embeddings.
- AI.GENERATE_TABLE: ai_generate_table.md - Table-valued AI generation.
- AI.IF: ai_if.md - Evaluate semantic conditions.
- AI.KEY_DRIVERS: ai_key_drivers.md - Identifies key drivers, this is a TVF.
- AI.SCORE: ai_score.md - Score data.
- AI.SEARCH: ai_search.md - Semantic search.
- AI.SIMILARITY: ai_similarity.md - Semantic similarity.
- Remote Models: remote_models.md - Working with remote models (Vertex AI).
- CONTRIBUTION_ANALYSIS: ml_contribution_analysis.md
  - Finds contributing factors, key drivers of change. Requires creating a MODEL entity.
- ML.CORRELATION: ml_correlation.md - Calculates correlation between columns, optionally sliced by dimensions.
- ML.DETECT_CHANGE_POINTS: ml_detect_change_points.md - Detects structural breaks or sustained shifts in a time series.
- ML.SEASONALITY: ml_seasonality.md - Extracts seasonal components from a time series.
- ML.TREND: ml_trend.md - Extracts the long-term trend component from a time series.
- VECTOR_SEARCH: vector_search.md - Vector search best practices.

Related Skills

BigQuery Basics Skill: SKILL.md file for core BigQuery concepts, resource management, CLI, and client libraries.

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

같은 저장소의 스킬

agent-platform-alert-configuration

무료

Create Terraform files that define alerts for AI agent latency, errors, token use, safety, security, and response quality. Check telemetry and existing policies first, then validate the generated configuration. Quality alerts require Vertex AI.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

Configure alerts for agent latency and error rates
Monitor rapid increases in token usage
Monitor safety triggers and permission denials

google/skills2.1만2026년 10월 17일 업데이트

agent-platform-deploy

무료

Deploy Model Garden models to Agent Platform endpoints, the addresses used for model requests. Check supported hardware and estimated hourly costs, inspect deployment progress, test predictions, and remove deployed resources after use.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

Choose a deployable model and supported hardware
Estimate hourly deployment costs before approval
Check deployment progress and test predictions

google/skills2.1만2026년 10월 17일 업데이트

agent-platform-endpoint-management

무료

Manages Agent Platform endpoints, the stable URLs used to serve online model predictions. It supports listing, inspecting, creating, updating, and deleting endpoints, plus troubleshooting permission errors, quota limits, and resources that are busy.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

Listing endpoints and checking their configuration
Creating an endpoint before model deployment
Updating endpoint display names or labels

google/skills2.1만2026년 10월 17일 업데이트

agent-platform-eval-flywheel

무료

Evaluate AI models and agents on Google Cloud using test datasets and scoring criteria. Generate simulated user scenarios, analyze failures, and compare results across changes to guide improvements to prompts and code.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

Build evaluation datasets from conversation logs
Generate simulated user scenarios
Choose scoring criteria for responses and tool use

google/skills2.1만2026년 10월 17일 업데이트

agent-platform-inference

무료

Call Gemini and OpenMaaS models such as Llama, DeepSeek, and Qwen through Google Cloud Agent Platform. Prepare authentication and SDK code, run prompts, configure connection endpoints, and troubleshoot common request errors.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

Send a test prompt to Gemini
Call Llama or DeepSeek with the OpenAI SDK
Write code to call an existing custom endpoint

google/skills2.1만2026년 10월 17일 업데이트

agent-platform-migrate-from-ai-studio

무료

Guides migration from Google AI Studio’s Gemini API to Gemini Enterprise Agent Platform on Google Cloud, covering billing, access permissions, authentication, and connection settings for SDKs and supported agent tools.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

Moving a Gemini application to Google Cloud
Using Google Cloud credits for Gemini API calls
Unifying agent authentication and billing

google/skills2.1만2026년 10월 17일 업데이트

google의 스킬 모두 보기

이 스킬의 문제 신고

설치

명령으로 설치

npx skills add https://github.com/google/skills --skill bigquery-ai-ml

터미널에 붙여 넣고 실행합니다(Node.js 필요). Claude Code, Codex 등 설치할 에이전트를 고를 수 있습니다.

에이전트에게 부탁하기

다음 Agent Skill을 설치해 주세요.
https://github.com/google/skills/tree/main/skills/cloud/bigquery-ai-ml

먼저 SKILL.md와 첨부 파일의 내용을 확인해 수상한 처리(외부 전송, 인증 정보 읽기 등)가 없는지 확인한 뒤 Claude Code는 ~/.claude/skills/bigquery-ai-ml/, Codex는 ~/.agents/skills/bigquery-ai-ml/ 에 배치해 주세요.

이 문장을 그대로 Claude Code나 Codex에 보내면 내용을 확인한 뒤 설치해 줍니다.

GitHub에서 소스 보기

저장소: google/skills
스타: 21,408
포크: 1,805
카테고리: 데이터·AI
라이선스: Apache-2.0
원문 언어: 영어
최종 업데이트: 2026년 10월 17일

스킬은 에이전트를 위한 지시와 스크립트의 묶음입니다. cccskills는 내용의 안전성을 보증하지 않습니다. 설치하기 전에 내용을 확인하세요.