Self-hosted alternatives to bigquery-pipeline-audit
5 self-hosted AI Skills apps to use instead, best rated first.
Top picks
- C

claude-to-deerflow
Launchclaude-to-deerflow is an agent skill that lets an assistant send messages and questions to a running DeerFlow instance through its HTTP API. DeerFlow is an AI agent platform built on LangGraph that orchestrates sub-agents for research, code
Self-hosted
- O

open-notebook
Launchopen-notebook is an agent skill for organising research with Open Notebook, a self-hosted alternative to NotebookLM. It arranges sources, notes and AI conversations into research notebooks. Sources can be PDFs, web pages, audio, video and O
Self-hosted
- R

Reactive Resume
LaunchReactive Resume is a free and open-source resume builder for writing resumes and cover letters, checking the work, and tracking job applications. You create a free account, import an existing resume or start from scratch, and see the finish
Open sourceSelf-hosted
- S

self-hosted-funnel-launch
LaunchSelf-hosted funnel launch is an agent skill that takes a funnel from an empty install to published on infrastructure you control, using the Autonnel funnel builder, which is licensed Apache-2.0. The result covers a landing page, checkout, a
Self-hosted
- G

get-convex/convex-backend
LaunchConvex is an open-source reactive database for web app developers. It combines a database, a place to write server functions in pure TypeScript, and client libraries that keep the app's data live, so screens update as the data changes. Beca
Self-hosted
About bigquery-pipeline-audit

bigquery-pipeline-audit
Audits Python + BigQuery pipelines for cost safety, idempotency
bigquery-pipeline-audit is an agent skill from the github/awesome-copilot collection that audits a Python and BigQuery data pipeline for cost safety, idempotency and production readiness. The agent acts as a senior data engineer reviewing the script. It locates every BigQuery job trigger, such as client.query, load_table_from_*, extract_table and copy_table, along with DDL and DML statements, and every external call to APIs, LLM services or storage, to show what will actually be billed. It then checks for loop-driven query multiplication, where a query runs once per item in a loop and the cost grows with the data, and for missing maximum_bytes_billed limits that would let a query scan more data than intended. The audit also checks whether a rerun would corrupt data, and whether failures are visible rather than silently swallowed. The response follows a fixed structure, sections A to F and a final summary, and it references exact function names and line locations with minimal suggested fixes rather than rewrites. This makes the audit practical to act on in a code review. The findings should be verified against the pipeline's real workload, since the cost exposure depends on data volumes that the code alone does not show. The skill is installed with the skills CLI from the github/awesome-copilot repository. Its skills.sh page showed about 8.8K installs and passing results from three security audits at the time of the scan.
- Price
- Free
- Made by
- github
- Category
- AI Skills
- Website
- github.com/github/awesome-copilot/bigquery-pipeline-audit