What problem does it solve? Cloud resources created or modified by AI agents often lack attribution, making it impossible to track which environment or client created them. This Skill ensures every relevant bq and gcloud command carries proper attribution labels so resource usage can be traced back to its origin. ## Core Features & Use Cases - BigQuery Labeling: Automatically adds --label datacloud:<ide> to label-supporting bq subcommands (query, load, extract, mk, update, cp) while omitting it from read-only commands like bq show or bq ls that reject the flag. - gcloud Environment Tagging: Prepends CLOUDSDK_METRICS_ENVIRONMENT=datacloud.<ide> to every gcloud command, covering both read-only and mutation operations. - Environment Detection: Deduces the correct IDE/client identifier (e.g., vscode, cursor, gemini-cli, cloud-shell) with an ai-agent fallback. - Use Case: When an AI agent runs a BigQuery query to deduplicate a dataset in VS Code, the command becomes bq query --use_legacy_sql=false --label datacloud:vscode ..., ensuring the job is attributed correctly. ## Quick Start Ask the agent to run a BigQuery query or any gcloud command and it will automatically attach the correct attribution label or environment variable for your current IDE.
