skill-kilo-org-kilo-marketplace-bigquery-basics · by Install
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Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
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Links to your public security report.[](https://agentstack.voostack.com/security/report/skill-kilo-org-kilo-marketplace-bigquery-basics) Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
BigQuery Basics
BigQuery is a serverless, AI-ready data platform that enables high-speed analysis of large datasets using SQL and Python. Its disaggregated architecture separates compute and storage, allowing them to scale independently while providing built-in machine learning, geospatial analysis, and business intelligence capabilities.
Setup and Basic Usage
- Enable the BigQuery API:
``bash gcloud services enable bigquery.googleapis.com --quiet ``
- Create a Dataset:
``bash bq mk --dataset --location=US my_dataset ``
- Create a Table:
Create a file named schema.json with your table schema:
``json [ { "name": "name", "type": "STRING", "mode": "REQUIRED" }, { "name": "post_abbr", "type": "STRING", "mode": "NULLABLE" } ] ``
Then create the table with the bq tool:
``bash bq mk --table my_dataset.mytable schema.json ``
- Run a Query:
``bash bq query --use_legacy_sql=false \ 'SELECT name FROM bigquery-public-data.usanames.usa1910_2013 \ WHERE state = "TX" LIMIT 10' ``
Reference Directory
- [Core Concepts](references/core-concepts.md): Storage types, analytics
workflows, and BigQuery Studio features.
- [CLI Usage](references/cli-usage.md): Essential
bqcommand-line tool
operations for managing data and jobs.
- [Client Libraries](references/client-library-usage.md): Using Google Cloud
client libraries for Python, Java, Node.js, and Go.
- [MCP Usage](references/mcp-usage.md): Using the BigQuery remote MCP server and
related client integrations.
- [Infrastructure as Code](references/iac-usage.md): Terraform examples for
datasets, tables, and reservations.
- [IAM & Security](references/iam-security.md): Roles, permissions, and data
governance best practices.
If you need product information not found in these references, use the Developer Knowledge MCP server search_documents tool.
Related Skills
- [BigQuery AI & ML Skill](../bigquery-ai-ml):
SKILL.md file for BigQuery AI and ML capabilities (forecast, anomaly detection, text generation).
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: Kilo-Org
- Source: Kilo-Org/kilo-marketplace
- License: Apache-2.0
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.