Your team built it with AI. Make sure it’s ready to run.
VibeGuard is a free and open source AI code review tool that runs as a set of AI-powered subagents, auditing AI-built codebases against 50 production-readiness checks and delivering a full remediation plan in under 30 minutes.
AI-built applications are reaching production before anyone has governed them
Although tools like Cursor, Copilot, and Claude let engineering teams ship internal applications in days, that speed creates a blind spot. The business logic works, but the surrounding operational layer often doesn’t exist: no audit trail, no defined ownership, no access controls, no rollback path. By the time an organisation notices, the application is already handling live workflows. The rise of vibe coding has accelerated this dynamic, and with it, the security and governance risks that come from shipping AI-generated code without a structured review process.
What’s typically missing
| No audit trail or change history | No record of what changed, when, or why |
| No clear ownership | Nobody accountable when something breaks |
| No access controls or security boundaries | APIs, secrets, and prompts left exposed |
| No test coverage or rollback mechanism | No safe way to recover when things go wrong |
| No governance review | Business-critical workflows with zero oversight |
| No runtime visibility | No observability into how the system behaves in production |
| Without operational governance, AI-built applications create invisible production and compliance risk inside the organisation. |
How VibeGuard works
A systematic automated code review your team can act on the same day
VibeGuard works through your existing codebase – no rebuilding, no parallel project. A scout agent maps the repository first, then up to 19 specialised subagents run in parallel, each focused on a single operational domain before aggregating into a single production readiness report.
It’s free, open source, and ready to run or extend.
Scout first
The scout runs alone to detect your exact stack: frameworks, containers, cloud dependencies, so only the relevant skills are activated. No wasted analysis.
Parallel execution
Once the scout completes, up to 19 domain agents fire simultaneously. Agents that don’t apply to your stack are skipped automatically. This is what makes VibeGuard an agentic code review system, and not a static analyser.
Configurable per stack
Opinionated best-practice files let you define stack-specific rules and exclusions per language and framework, eliminating false positives and matching your team’s conventions.
Six domains. One consistent standard across every audit.
How the application handles data across prompts, APIs, logs, and connected systems. Covers exposure risks, retention boundaries, input/output flows, and prompt content governance.
Whether the application can be operated and supported in production. Covers deployment ownership, change management, rollback readiness, incident response, and runbook availability.
How the system behaves under real workload conditions. Covers latency, throughput, resource usage, LLM efficiency, and cost per operation.
Whether outputs remain reliable across normal usage, edge cases, and failure scenarios. Covers validation logic, evaluation coverage, error handling, and testing around critical workflows.
Whether the application can sustain production usage over time. Covers uptime posture, dependency resilience, provider fallback strategies, circuit breakers, and recovery behaviour.
How access, secrets, APIs, and prompts are protected across the application. Covers authentication, authorisation, API boundaries, sensitive data exposure, and prompt injection risks.
| Findings are delivered as a severity-ranked report with production blockers, a risk heatmap, and remediation recommendations, plus an executive summary for non-technical stakeholders. |
Built for people responsible for ensuring that nothing breaks.
VibeGuard produces two layers of output: a detailed technical report for the team doing the work, and an executive summary for the people making the go/no-go call. Both readable without translating between them.
Engineering teams
Developers, tech leads, architects
What they use it for
- Accelerating code review on AI-generated repositories
- Identifying production blockers before go-live
- Getting a structured entry point into an unfamiliar codebase
- Applying and enforcing team-specific coding standards
What they get
Severity-ranked findings with error IDs, descriptions, risk level, and recommended fixes, including which issues an agent can patch automatically.
CTOs & technical managers
Decision-makers, project owners
What they use it for
- Tracking remediation progress across the risk heatmap
- Making an informed production go/no-go decision
- Understanding risk exposure without reading technical detail
- Communicating readiness to non-technical stakeholders
What they get
An executive summary with a production readiness verdict, a six-domain risk map, and a prioritised list of what must be fixed before rollout.
| VibeGuard produces the report, but interpreting it and deciding on next steps still requires a technical person on your side. The tool accelerates the review process, it does not replace engineering judgement. |
Cost & efficiency
A full audit for less than the cost of an hour of senior engineering time
Running VibeGuard against a repository costs $8-10 in LLM token usage and completes in around 30 minutes. The same review done manually by a senior developer typically takes a full day at a cost an order of magnitude higher.
| VibeGuard | Manual senior review | |
|---|---|---|
| Cost per audit | $8–10 | 1–2 days of senior time |
| Time to report | ~30 minutes | Full day or more |
| Coverage | 50 checks, 6 domains | Depends on reviewer’s focus |
| Consistency | Same standard every run | Varies by person and time |
| Output | Ranked report + remediation plan | Notes, often undocumented |
Token costs depend on repository size and the LLM provider used. The $8-10 figure reflects typical mid-sized repositories. |
Your team built it fast. VibeGuard makes sure it runs safely.
Teams understand how the application behaves, what requires remediation, and how the system should be maintained over time.
Move your AI-built application into production with deployment controls, runtime visibility, and security boundaries already defined.
Access controls, API boundaries, secrets handling, and prompt injection risks reviewed and addressed before the application touches real data.
Production blockers identified early, remediation work prioritised before operational issues appear in production environments.
Reduce dependency on fragile prototypes. Create a foundation teams can safely extend, monitor, and support as adoption grows.
Clearer oversight around deployments, access boundaries, runtime behaviour, and operational responsibility as AI-built workflows become business-critical.
Apache 2.0 licence. Use it as-is, adapt it to your stack, or contribute new skills back to the community.
Not sure where to start, or don’t have the capacity to act on the findings?
Running VibeGuard gives you the full picture, but turning a remediation plan into a production-ready system takes engineering time and AI architecture experience most teams don’t have in-house.
That’s what our Vibe Code to Pro Code service is for. We start with a structured assessment of your existing prototype, then add the production infrastructure layer by layer: evaluation pipelines, observability, security hardening, cost controls, CI/CD, and deployment. No rewrites from scratch. No black box. The business logic you’ve already built stays intact.
Phase 1 takes one to two weeks and gives you an honest go/no-go recommendation and a concrete technical plan. No commitment to anything beyond that.
FAQ
Answers to the questions that come up most often from engineering teams, CTOs, and potential partners. Missing something? Get in touch.
Primarily the latter. VibeGuard identifies issues, ranks them by severity, and produces a remediation plan. Some straightforward fixes can be applied automatically by a coding agent acting on the report, but the tool is designed to surface problems and guide action, not to rewrite your codebase.
VibeGuard checks for production-readiness gaps across six domains: data handling, operations, performance, quality, reliability, and security. This includes things like missing access controls, exposed secrets, absent rollback mechanisms, no audit trail, prompt injection risks, and lack of test coverage around critical workflows, ie. patterns that frequently appear in vibe coded applications and AI-generated code but are rarely caught by static analysis or informal reviews, making VibeGuard an effective AI code review tool for teams moving fast with coding agents.
Both. VibeGuard is designed to work against any existing repository. It doesn’t require the project to be set up in a particular way. It’s been used as a sanity check on projects already in use, as an entry point for teams inheriting an unfamiliar codebase, and as an extension of existing review practices.
Yes. While VibeGuard was built specifically in response to governance gaps in AI-assisted development, the checks it applies are relevant to any codebase going to production. The framework doesn’t distinguish between AI-generated and hand-written code.
VibeGuard is language-agnostic and fully extensible. The scout agent detects your stack automatically and selects only the relevant skills – checks that don’t apply to your technology are skipped. Beyond language support, the framework lets you add your own company-specific best practices, which may differ from, or even contradict, general conventions. Those custom rules are treated as the standard for your project, so what another team might flag as a flaw won’t surface as one in your audit.
VibeGuard is agent-agnostic. It works as a rule engine that delivers instructions in markdown. Any coding agent that can execute markdown-based tasks can run it. It has been used alongside tools like Cursor, Copilot, and Claude, but is not tied to any specific platform.
Install the VibeGuard plugin from the official repository, navigate to your project folder, and run /vibeguard from within it. The scout agent takes it from there, detecting your stack, selecting the relevant skills, and running the full audit automatically.
Yes. VibeGuard supports opinionated best-practice files per-language, per-framework configuration files where you can define custom rules, anti-patterns, and exclusions. This eliminates false positives and lets you align the audit with your team’s specific conventions and standards.
A technically fluent person needs to review the findings and decide on next steps. VibeGuard produces the report, but it does not replace engineering judgement. The executive summary is designed for non-technical stakeholders, but the detailed findings require someone who can evaluate the context and prioritise remediation appropriately.
The report contains two layers. The detailed report lists findings by domain, each with an error ID, description, risk level (critical, high, medium, low), and a recommended fix. The executive summary provides a production readiness verdict, a six-domain risk heatmap, and a prioritised list of blockers designed for a CTO or project owner to read without needing to go through the technical detail.
All outputs are markdown files – the detailed findings report, the remediation plan, and the executive summary. Markdown makes them easy to commit to a repository, share with stakeholders, drop into documentation, or pipe into other tools in your workflow.
VibeGuard itself is free and open source. The cost comes from LLM token usage, typically $8-10 per full repository analysis, depending on the size and complexity of your codebase and the model provider you use. Larger or more complex projects will use more tokens. There is no subscription, no platform fee, and no sign-up required.
Contact us!
Send us an email: [email protected]
VibeGuard was created after repeatedly seeing the same pattern inside organisations adopting AI quickly: internal teams built useful LLM-powered applications in days, but once those systems started handling real workflows, the surrounding operational gaps became impossible to ignore.
I may have built the framework, but what’s inside it is 10+ years of collective knowledge from our entire DAC team – every pattern we’ve seen break in production, every gap we’ve had to close after the fact. VibeGuard is that experience, made repeatable.