This release has been yanked by its maintainers, and will be ignored by installers, except when explicitly specified.
Consider using release 1.3.1 instead.
Reason given by maintainers: Broken release.
AI engineering workstation guardrails
Give AI coding agents a seatbelt, not a committee meeting. This is a local, vendor-neutral guardrails kit for OpenAI Codex, Claude Code, Cursor, GitHub Copilot in VS Code and Visual Studio, and JetBrains AI Assistant/Copilot.
It turns one canonical policy into product-appropriate guidance, skills, hooks, and optional agent roles. The goal is boringly useful: inspect first, preserve user work, avoid secrets and destructive operations, verify changes, and say what happened.
The short version
- One canonical policy, rendered for six product surfaces rather than copied six times.
- Narrow deterministic checks for high-confidence risks: destructive Git operations, publication, credential exposure, and dangerous infrastructure actions.
- Portable, on-demand skills and capability packs for application, delivery, and infrastructure work.
- A local installer that preserves unrelated configuration, creates backups, and uses an immutable runtime independent of the source clone.
- Optional routing and terminal UX—both off unless you explicitly enable them.
This is defence in depth, not a replacement for product approvals, sandboxing, operating-system permissions, branch protection, cloud IAM, Kubernetes RBAC, or a human release decision.
Start here
Python 3.11+ is required. Install the published package with pipx and preview before writing anything. Do not use sudo, Administrator, or an elevated shell.
pipx install ai-engineering-guardrails
ai-guardrails install --dry-run
ai-guardrails install
ai-guardrails status
For contributor work or a reviewed local checkout instead:
git clone https://github.com/ZarrenSpryXplor/ai-engineering-guardrails.git
cd ai-engineering-guardrails
pipx install .
The default install detects local supported products, uses no cloud login, and changes no main model, approval setting, sandbox, network setting, routing profile, or terminal decoration. If no product is detected, it makes no change and prints the explicit command to use.
For a direct Git install, pin a reviewed tag or full commit rather than a moving branch:
pipx install 'git+https://github.com/ZarrenSpryXplor/ai-engineering-guardrails.git@<reviewed-tag-or-full-commit>'
The package is published on PyPI through Trusted Publishing. Maintainers should follow the release guide for protected approvals, version/tag checks, and provenance.
Optional extras
Terminal visibility is opt-in. Claude Code can use a managed local status line; Codex uses its native /statusline fields; Cursor CLI keeps its documented /status-indicators control.
ai-guardrails statusline preview --product all --profile standard
ai-guardrails statusline install --product all --profile standard --dry-run
ai-guardrails statusline install --product all --profile standard
ai-guardrails activity --since 24h
ai-guardrails receipt --compact
Routing is also opt-in. It installs static, bounded roles; it does not classify prompts, choose a model at runtime, or grant authority.
ai-guardrails routing show --profile balanced --product codex
ai-guardrails routing set balanced --product codex --dry-run
ai-guardrails routing set balanced --product codex
Find the right detail
The operator documentation hub is the durable entry point. It gives each audience one place to start instead of making this README do every job.
| If you need to… | Read… |
|---|---|
| Install, update, recover, inspect state, or use waivers | Quick user guide and operations |
| Understand product versions, paths, and limitations | Compatibility |
| Enable terminal UX, activity, complexity, receipts, or demo mode | Terminal UX |
| Audit policy evidence, use a task contract, or inspect an external skill/instruction | Evidence and assurance |
| Delegate bounded work safely | Routing and cost |
| Use or extend language and infrastructure support | Capability packs and skills catalogue |
| Change canonical policy or understand the design | Policy authoring and architecture |
| Review threat boundaries and enterprise examples | Threat model, enterprise output, and Spacelift |
Contribute and report safely
- Read CONTRIBUTING.md before changing canonical policy, generated output, or product integration.
- Report vulnerabilities privately using SECURITY.md; do not put exploit details or secrets in a public issue.
- See CHANGELOG.md for release-facing changes and CODE_OF_CONDUCT.md for community expectations.
The project is MIT licensed. It makes no claim to be a universal security boundary or to save a particular amount of money, time, or tokens.
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