Lathika-laa
Community@Lathika-laa
Google-published skill registry for building, orchestrating, securing, and optimizing data pipelines across BigQuery, Dataflow, Dataproc Spark, Cloud Composer, and Cloud Storage.
Agent Skills by Lathika-laa
Showing 29 vetted skills indexed across 1 GitHub repositories.
Lathika-laagcp-data-pipelines
Routes data pipeline requests to the appropriate Google Cloud tool skill.
Lathika-laadiscovering-gcp-data-assets
Discovers and inspects Google Cloud data assets using Dataplex search and context lookup.
Lathika-laagcp-spark
Generates and executes PySpark notebooks on Dataproc clusters and Serverless with BigQuery, Iceberg, and Spanner.
Lathika-laamanaging-python-dependencies
Detects project dependency managers and installs Python packages with the correct tooling.
Lathika-laadata-autocleaning
Profiles and cleans BigQuery and GCS data using Dataplex scans and SQL transformations.
Lathika-laagcp-dataflow
Guides authoring, packaging, launching, and diagnosing Apache Beam pipelines on Google Cloud Dataflow.
Lathika-laabigquery-data-transfer-service
Discovers and inspects BigQuery Data Transfer Service configurations for ingestion pipelines.
Lathika-laaenforcing-resource-attribution
Applies attribution labels to bq and gcloud CLI commands for resource tracking.
Lathika-laabigquery-bigframes
Generates Python code using BigQuery DataFrames for pandas-style analysis and ML on BigQuery.
Lathika-laadbt-bigquery
Generates, modifies, and validates dbt models and pipelines targeting Google BigQuery.
Lathika-laagcp-composer-troubleshooting
Diagnose Cloud Composer and Airflow DAG failures using gcloud logs and remote code analysis.
Lathika-laabigquery-graph
Generates GQL queries and property graph DDL for BigQuery graph analytics.
Lathika-laafederate-lakehouse-catalog
Configures Google Cloud Lakehouse federated catalogs connecting BigQuery to Databricks Unity and AWS Glue.
Lathika-laaaccidental-data-loss-prevention
Blocks irreversible deletion commands until explicit user consent is obtained.
Lathika-laabuilding-data-apps
Build data dashboards and interactive reports with React, Vite, or Streamlit connected to BigQuery.
Lathika-laadataform-bigquery
Generates and validates Dataform SQLX pipeline code for BigQuery ELT workflows.
Lathika-laagcp-managed-airflow-recommendations
Diagnose Cloud Composer environments and generate evidence-based Airflow tuning recommendations.
Lathika-laaskill-repair
Fixes failed agent skill installations and updates manifest.json status entries.
Lathika-laagcp-managed-airflow-dag-authoring
Author and validate Apache Airflow DAGs for Google Cloud Managed Service for Apache Airflow environments.
Lathika-laagoogle-cloud-storage-basics
Manages Google Cloud Storage buckets and objects via gcloud CLI, JSON API, and client libraries.
Lathika-laabigquery-ai-ml
Write BigQuery SQL queries using built-in AI and ML functions for forecasting, anomaly detection, and generative analysis.
Lathika-laagcp-pipeline-orchestration
Generate, validate, deploy, and trigger Google Cloud Composer orchestration pipeline YAML definitions.
Lathika-laagcloud-auth-verification
Diagnose and resolve missing Google Cloud authentication and Application Default Credentials errors.
Lathika-laanotebook-guidance
Guides creation and execution of Jupyter notebooks for BigQuery data analysis and visualization.
Frequently Asked Questions About Lathika-laa
FAQPage SchemaWhat tasks can I accomplish with Lathika-laa's Google Cloud data skills?▼
You can build and orchestrate data pipelines using dbt, Dataform, Dataflow (Apache Beam), Dataproc Spark, and Cloud Composer; optimize BigQuery SQL; run BigFrames pandas-style analysis; clean data from BigQuery or GCS; provision pipeline resources via deployment.yaml; and assess GCS security posture against SAIF compliance.
Who are these skills designed for?▼
Data engineers, analytics engineers, and ML practitioners working on Google Cloud. They suit teams building ELT pipelines in BigQuery, authoring Airflow DAGs for Managed Service for Apache Airflow, running Spark ETL on Dataproc Serverless, or performing notebook-based analysis with %%bqsql magics.
How do I run and authenticate these skills in practice?▼
Skills execute through gcloud, bq, and dataform commands with verified Application Default Credentials via the gcloud-auth-verification skill. Python work requires project-specific virtual environments rather than global pip installs, and bq operations enforce mandatory resource labeling for attribution.
What license and cost apply to these skills?▼
All 29 skills are published by Google under the Apache-2.0 open-source license, permitting free use, modification, and redistribution. Usage of underlying Google Cloud services such as BigQuery, Dataflow, and Cloud Composer is billed separately under standard GCP pricing.
What safety guardrails are included before destructive operations?▼
The accidental-data-loss-prevention skill mandates explicit user consent before irreversible actions: DROP, TRUNCATE, or unbounded DELETE statements; gsutil or gcloud storage rm on production buckets; project deletion; and KMS key destruction. Confirmation is required whenever destructive intent is ambiguous.