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BigQuery Pipeline Audit

Audits Python and BigQuery pipelines for cost, safe reruns, and production readiness.

Source Download skill
Repository
github/awesome-copilot
Stars
40,703
Licence
MIT
Files
1 file

What it does

This is a set of instructions that makes an AI agent act like a senior data engineer reviewing a Python script that runs BigQuery jobs. When you point the agent at your pipeline code, it checks for runaway query costs, missing dry-run and prod safeguards, backfill loops that run one query per date, risky SQL scans, writes that could create duplicate rows on rerun, and weak logging. It returns a graded A to F report with references to specific functions and suggested minimal fixes.

Great for

  • Data engineers reviewing a Python + BigQuery pipeline before it goes to production
  • Teams wanting a checklist-style review of query cost and rerun safety
  • Developers who inherited a pipeline and need to understand its billing exposure

Skip it if

  • Non-BigQuery warehouses or pipelines (the checks are BigQuery-specific, so results would be unreliable)
  • Anyone expecting the skill to actually measure costs; it reads code and does not run queries itself, so estimates are rough reasoning from the code
  • Replacing a formal security or compliance review, since it focuses on cost and data-correctness rather than access control

Try asking

  • “Audit my pipeline script for BigQuery cost risks and tell me the worst-case job count”
  • “Review this ETL script for idempotency: will a rerun create duplicate rows?”
  • “Check whether my backfill loop runs one query per date and suggest a set-based rewrite”
  • “Add a dry_run and execute mode to this script with safe defaults”
Step-by-step guide: how to use BigQuery Pipeline AuditInstall, first run, examples, tips and FAQs

Install in 3 steps

  1. 1

    Download the skill

    The ZIP contains the 1 original files, the MIT licence and an attribution note.

    bigquery-pipeline-audit.zip
  2. 2

    Add it to your agent

    Claude Code (all projects)

    mkdir -p ~/.claude/skills && unzip bigquery-pipeline-audit.zip -d ~/.claude/skills/

    Claude Code / Agent SDK (this project only)

    mkdir -p .claude/skills && unzip bigquery-pipeline-audit.zip -d .claude/skills/

    Claude apps (web/desktop): Settings → Capabilities → Skills → Upload skill, and choose the ZIP.

  3. 3

    Ask for the task

    No special command needed — the agent reads the skill's description and loads it when your request matches. Try one of the prompts above.

Get better results

  • Give the agent the full pipeline entry point plus any modules it calls, so it can trace loops and retries across files
  • Ask for the Final section explicitly if you only want the PASS/FAIL verdict and patch list
  • Treat the worst-case job estimates as hypotheses and confirm them with BigQuery dry-run output or job history

What's inside

  • SKILL.md

Redistributed unmodified from github/awesome-copilot under the MIT licence. The assessment was drafted with AI from the skill's files on 2026-10-29. Skills can instruct your agent to run code — read SKILL.md and any scripts before installing.