en un clic
data-gcp
data-gcp contient 5 skills collectées depuis pass-culture, avec une couverture métier par dépôt et des pages de détail sur le site.
Skills dans ce dépôt
Generate YAML schema and documentation for dbt models, ensuring alignment with best practices and automated testing.
Review a pull request and rate it /10 on bugs, security, improvements, technical quality, and consistency with adjacent code.
Migrate Airflow DAGs from GCE (SSHGCEOperator) to GKE (CustomKubernetesPodOperator). Use when the user wants to migrate a DAG from VM-based to Kubernetes-based execution, replace SSHGCEOperator with CustomKubernetesPodOperator, convert GCE tasks to KPO tasks, or mentions GCE-to-GKE migration. Also trigger when they mention removing StartGCEOperator, DeleteGCEOperator, InstallDependenciesOperator in favor of pod-based execution.
Create pull requests that follow data team standards with proper naming conventions, commit validation, and squash-and-merge workflow. Use this skill when the user wants to create a PR, mentions pull requests, needs help with commit naming, wants to clean up commits before review, or talks about submitting work for review. Also trigger when they mention tickets like DE-XXX, HF-XXX, or BSR, or when they're working with dbt, bq_jobs, ml_jobs, or analytics code and need to get their changes reviewed.
Fix Python package vulnerabilities for a single uv.lock file by updating pyproject.toml and tool.uv constraint-dependencies, then regenerating the lockfile.