What is bigquery-basics?

Instructions for working with BigQuery, Google's service for storing and querying large datasets with SQL. A dataset is a collection of related tables, and a job is a task such as running a query.

Use it to enable the BigQuery service, create datasets and tables, run SQL queries, and work with BigQuery ML or Gemini for data analysis.

It provides the basic commands and setup steps needed to create BigQuery resources and query data.

How tutur3u/platform configures Claude Code and Codex

Reuse

Borrowing it

Nothing to install: this file belongs to tutur3u/platform. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file

curl -O https://raw.githubusercontent.com/tutur3u/platform/main/.agents/skills/bigquery-basics/SKILL.md

Clone the repo

git clone --depth 1 https://github.com/tutur3u/platform

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

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Your own site · 80×15

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Per session 21 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,136 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin 91% copy Near-identical to another mod in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00021	$0.01136
Opus 5.5	$0.00008	$0.00454
Sonnet 5.5	$0.00004	$0.00227
Haiku 4.5	$0.00002	$0.00114

Measured 1mo ago against content hash ce209e571618, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

bigquery-basics scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

91% identical to bigquery-basics — 38 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.agents/skills/bigquery-basics/SKILL.md · 98 lines

How it starts

The opening of the file, as written. The whole thing — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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:

gcloud services enable bigquery.googleapis.com --quiet

Create a Dataset:

bq mk --dataset --location=US my_dataset

Create a Table:

Create a file named schema.json with your table schema:

[
  {
    "name": "name",
    "type": "STRING",
    "mode": "REQUIRED"
  },
  {
    "name": "post_abbr",
    "type": "STRING",
    "mode": "NULLABLE"
  }
]

Then create the table with the bq tool:

bq mk --table my_dataset.mytable schema.json

Run a Query:

bq query --use_legacy_sql=false \
'SELECT name FROM `bigquery-public-data.usa_names.usa_1910_2013` \
WHERE state = "TX" LIMIT 10'

Reference Directory

Core Concepts: Storage types, analytics workflows, and BigQuery Studio features.
CLI Usage: Essential bq command-line tool operations for managing data and jobs.
Client Libraries: Using Google Cloud client libraries for Python, Java, Node.js, and Go.
MCP Usage: Using the BigQuery remote MCP server and Gemini CLI extension.
Infrastructure as Code: Terraform examples for datasets, tables, and reservations.
IAM & Security: 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.

Read the full file on GitHub · 98 lines

Files

What ships with it

6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

1mo ago Changed · -6 lines · -64 tokens per session ce209e571618
1mo ago First seen · 104 lines · 85 tokens per session scan A 1b6908fc0934

Subscribe to this mod's changes

bigquery-basics is a skill published in the GitHub repository tutur3u/platform (55 stars, last pushed today), licensed Apache-2.0. It adds 21 tokens to every session and 1,136 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 91% identical to bigquery-basics, differing in 38 lines, and is treated as a copy.

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