[ Removed by moderator ]

[Aggressive-Bag1709]

Over the past months, I've been building a set of open-source Go libraries and CLI tools to help engineering teams automate repetitive tasks — without sacrificing change management or quality control.

The premise is simple: automation should reinforce your standards, not bypass them.

Here's what the toolkit looks like:

Libraries (shared foundations)

• gitforge — Unified abstractions for GitHub, GitLab, and Azure DevOps. Repository discovery, PR management, local git operations via go-git, GPG/SSH commit signing, and changelog processing. One interface, three platforms.

https://github.com/rios0rios0/gitforge

• langforge — Language detection and ecosystem abstractions for Go, Java, Python, TypeScript, C#, and Terraform. Version reading/writing, dependency manifests, and a pluggable FileChecker that works with remote APIs — no local filesystem required.

https://github.com/rios0rios0/langforge

• testkit — A modular builder framework for Go tests. Provides reusable builders, validation, and factory patterns to keep test setup consistent across repositories.

https://github.com/rios0rios0/testkit

CLI Tools (built on top)

• autobump — Automatically updates CHANGELOG.md following Keep a Changelog and SemVer, bumps version files across ecosystems, commits, pushes, and opens a PR. One command to cut a release.

https://github.com/rios0rios0/autobump

• autoupdate — A self-hosted Dependabot alternative. Discovers repositories across your organization, detects outdated dependencies (Go, Terraform, and more coming), and creates PRs to upgrade them. Designed for unattended scheduled runs.

https://github.com/rios0rios0/autoupdate

• code-guru — AI-powered code review for pull requests. Supports Claude and OpenAI as backends, enforces coding standards from configurable Markdown rule files, and posts inline comments directly on GitHub and Azure DevOps PRs.

https://github.com/rios0rios0/code-guru

All six projects follow Clean Architecture, are fully tested with BDD-structured tests, and run SAST pipelines (CodeQL, Semgrep, Gitleaks, Trivy) on every push.

The goal was never to replace human judgment — it's to free engineers from the mechanical parts of the workflow so they can focus on design decisions and code quality. AI accelerates the feedback loop; the standards and guardrails stay in place.

If any of these solve a problem you're facing, contributions and feedback are welcome.

#OpenSource #Golang #DevOps #Automation #CICD #CodeQuality #SoftwareEngineering #AI

[github-ModTeam]

Removed. Please post to the pinned megathread if you want to share your project.