Dbt Bigquery
作者 gemini-cli-extensions2df10e25bbf7Apache-2.0215 个星标收录于 2026年10月8日更新于 2026年10月8日仓库今天更新
Expert guidance for creating, modifying, and optimizing dbt pipelines for BigQuery. Use this skill whenever user asks for generating or modifying a dbt model or project. Activate this skill when the user - Creates, modifies, or troubleshoots **dbt models or pipelines** - Needs to **optimize SQL** within a dbt project - Is **setting up a new dbt project** or configuring existing one
仅公开文件列表。将技能安装到工作区后即可查看文件内容。
| 路径 | 大小 | 类型 |
|---|---|---|
| SKILL.md | 11.6 KB | text/markdown |
来源与署名
来源：gemini-cli-extensions/data-agent-kit-starter-pack位于skills/dbt-bigquery提交2df10e2
许可证： Apache-2.0
内容归原作者所有。SourceWeft 从公开仓库中收录这些内容。
更多来自 gemini-cli-extensions/data-agent-kit-starter-pack 的技能
Schema Mapping
gemini-cli-extensions
为 ETL、ELT 或数据集成任务规划源到目标的模式映射，产出文档化的映射宣言。
Resolving Mcp Region Configs
gemini-cli-extensions
修复区域级 Google Cloud MCP 服务器配置中未替换的区域占位符，使缺失的 MCP 工具得以注册。
Notebook Guidance
gemini-cli-extensions
This skill guides the use of Jupyter notebooks for data analysis, exploration, and visualization, particularly with BigQuery. It outlines best practices for notebook execution and validation (supporting both cell-by-cell execution and full notebook generation depending on tool availability), library installation, and structuring notebooks for clarity. It also covers specific rules for data cleaning, plotting, and integrating with BigQuery SQL and machine learning workflows. Relevant when any of the following conditions are true: 1. The user request involves a data analysis, data exploration, data visualization, or data insights task that requires multiple steps, queries, or visualizations to answer. 2. The user explicitly requests a notebook (.ipynb). 3. You are creating, editing, or executing cells in a Jupyter notebook. 4. You need to query BigQuery from within a notebook. DO NOT use the Python BigQuery client library; instead, you MUST use the `%%bqsql` magics explained in this skill.
Ml Best Practices
gemini-cli-extensions
为机器学习笔记本提供分步方案，涵盖聚类、预测、分类、回归和模型比较。
Managing Python Dependencies
gemini-cli-extensions
指导代理检测 Python 项目的依赖管理器并正确安装依赖，而不是使用全局 pip。
Google Cloud Storage Fuse
gemini-cli-extensions
Mounts Cloud Storage buckets as a POSIX file system with Cloud Storage FUSE (gcsfuse). Use when you need to interact with gcsfuse — decide whether FUSE, native gs:// reads, or Filestore/Managed Lustre fits a workload, deploy tuned mounts on GKE, Compute Engine, or Cloud Run, enable and size the file, stat, and list caches, tune mount flags or config-file settings, apply workload profiles, keep ML checkpointing safe (rename atomicity, hierarchical namespace, close-time finalization, concurrent writers), or diagnose slow training, low throughput, or GCS bill spikes on existing mounts with gcsfuse metrics. Covers mount semantics, the gcsfuse CLI and config file, the GKE gcsfuse CSI driver (Workload Identity principal:// bindings, profile StorageClasses, sidecar sizing), and Cloud Run volume mounts. Don't use for bucket administration or data management without a mount (google-cloud-storage-basics) or for fully POSIX-compliant shared file systems (Filestore, Managed Lustre).
更多Data & Analytics技能
Content Strategy
anthropics
将 PayPal、QuickBooks 或 Square 的销售数据转化为按优先级排序的 30 天内容简报。
Cash Flow Snapshot
anthropics
根据账簿、支付平台或 CSV 数据生成 30/60/90 天现金流预测，含置信区间和具名风险提示。
Pipeline Review
anthropics
按阶段审查 CRM 销售管道健康状况，标记老化、停滞和高风险商机并检查覆盖率。
Metrics Review
anthropics
审阅产品指标，分析趋势并与目标对比，输出带建议行动的指标记分卡。
Performance Report
anthropics
生成营销表现报告，包含关键指标、趋势分析、成败总结以及按优先级排序的优化建议。
People Report
anthropics
根据人力数据生成人员编制、流失率、多元化和组织健康度等人才分析报告。