by gemini-cli-extensions2df10e25bbf7Apache-2.0Listed Oct 8, 2026Updated Oct 8, 2026
**STOP AND VERIFY**: Before running any command or tool that results in irreversible data loss, you MUST obtain explicit user consent. When in doubt, ask. It is better to wait for confirmation than to accidentally delete production data or critical project assets. Use this for: - SQL: DROP TABLE/VIEW/SCHEMA/DATABASE, TRUNCATE, or broad DELETE (missing WHERE or using 1=1). - Cloud Storage: gsutil rm or gcloud storage rm targeting production data or critical buckets. - Infrastructure: gcloud projects delete, deleting Spanner/BigQuery/Dataproc resources, deleting secrets, or KMS key destruction.
Requires explicit user consent before running commands that could cause irreversible data loss.
[!CAUTION]
STOP AND VERIFY: Before running any command or tool that results in irreversible data loss, you MUST obtain explicit user consent.
Source:gemini-cli-extensions/data-agent-kit-starter-packinskills/accidental-data-loss-preventionat commit2df10e2
License: Apache-2.0
Content belongs to its original authors. SourceWeft indexes it from a public repository.
gemini-cli-extensions
Plans source-to-target schema mappings for ETL, ELT, or data integration work, producing a documented Mapping Manifesto.
gemini-cli-extensions
Fixes unreplaced region placeholders in regional Google Cloud MCP server configs so missing MCP tools register.
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.
gemini-cli-extensions
Guides machine learning notebooks with step-by-step plans for clustering, forecasting, classification, regression and model comparison.
gemini-cli-extensions
Guides agents to detect a Python project's dependency manager and install packages correctly instead of using global pip.
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).
Guides implementation of OAuth 2.0 DPoP (RFC 9449) sender-constrained refresh tokens for Google's OAuth platform.
Guides SOC analysts through triaging Google SecOps security alerts, from investigation to closure or escalation.
Guides SOC analysts through deep security incident and entity investigations in Google SecOps using UDM queries and timelines.
Guides proactive threat hunting in Google SecOps using UDM queries, IoC lookback, prevalence and outlier analysis.
Manages Google Security Operations SOAR cases across their lifecycle via MCP tools.
Guides Google Cloud Privileged Access Manager entitlement CRUD, temporary access requests, and grant approval workflows.