Engineering Guardrails for the AI Era.
Turn
AI prompts, standards, AGENTS.md files, eng wikis, cursor rules,
checklists, compliance
into deterministic PR and AI-level enforcement
in minutes,
not quarters
Developer behavior
is fundamentally difficult to change at scale.
Standards Are Scattered
AGENTS.md, wikis, Slack threads nobody follows
Checklists Get Rubber-Stamped
By humans and AI alike — no way to verify compliance
Human Review Is the Bottleneck
It's hard to keep up with AI-generated code volume
Fragmented Tooling
Every repo configured differently, no central enforcement
Issues Surface Too Late
Non-compliant code caught at deploy time, not authoring time
❌ The Broadcast Problem
Standards communicated
out-of-context
through mass channels
Any Guardrail, One Prompt Away
Describe any standard, process, or incident response. Lunar turns it into an enforced guardrail across every repo, in minutes.
claude
Earthly Lunar skill
-
1
Describe
Postmortem finding, compliance mandate, or zero-day. In plain language.
-
2
AI Creates the Guardrail
Data collection and enforcement. The platform handles both.
-
3
Enforced Everywhere
Every PR, every repo. Minutes, not quarters.
Incident Response
- Pin GitHub Actions to commit SHAs after the Trivy supply chain compromise
- Block npm package versions published during the Axios attack window
- Audit all workflows using tj-actions/changed-files after the March breach
- Flag Docker images built with compromised Trivy scanner versions
- Detect Log4j usage in transitive dependencies across all Java services
Internal Standards
- Flag repos still importing our deprecated internal auth library
- Ensure every service has a catalog-info.yaml with a valid team owner
- Verify all Terraform modules reference our internal module registry
- Ensure Helm charts inherit from our approved base chart
- Require the team's standard .editorconfig in every repo
- Enforce our naming convention for Kubernetes namespaces
Compliance & Audit
- Require valid Jira ticket references on every PR for SOC 2
- Verify SBOMs are generated and uploaded for every release artifact
- Block packages with GPL or AGPL licenses in proprietary codebases
- Ensure license headers are present in all source files
- Validate that every container image is signed before deployment
Migrations
- Block Python 3.9 Lambda functions now that it has reached end of life
- Flag repos still using AWS SDK v1 instead of v2
- Detect services still on the deprecated logging framework
- Flag repos pulling images from Docker Hub instead of our private ECR
- Block creation of new Jenkins pipelines — all new projects use GitHub Actions
Operational Readiness
- Require a linked runbook in every production service README
- Require OpenTelemetry tracing in all Go services before production
- Ensure every Kubernetes deployment has liveness and readiness probes
- Verify all services define an on-call rotation in PagerDuty
- Require resource limits on all Kubernetes workloads to prevent cost overruns
AI Generates Code Fast.
Guardrails Ensure It Ships Right.
Deterministic enforcement for developers and AI agents. Centrally instrumented, gradually rolled out, audit-ready by default.
Deterministic,
Not Stochastic
Prompts are suggestions, not constraints. Same input, same output, every time. Trustworthy enough to actually block a PR or a deploy.
Same Guardrails,
Human and AI
One set of standards, uniformly enforced. No separate AI governance track. Works with Claude Code, Cursor, Codex, and every pull request.
Central
Instrumentation
Deploy once, cover every repo and pipeline. No per-team opt-in, no template drift, no repo-by-repo rollout.
Evidence as
a Byproduct
Real-time adherence dashboards and a continuous audit trail fall out of enforcement. Not a separate quarterly exercise.
Gradual
Enforcement
Start with visibility, add PR comments, escalate to blocking. Adjust centrally, without repo-by-repo opt-in.
Learn more
Works With
Your Stack
GitHub, GitLab, any CI/CD. Complements OPA, Rego, and existing policy tools with the structured SDLC data they need.
Write Once, Enforce Everywhere
Same policies. Same evaluation engine.
Every stage of your development lifecycle.
Code Authoring
Pull Request
Deploy
- Fires on every file edit during authoring
- Agent self-corrects in real-time
- Automated checks on every pull request
- Block or report per guardrail
- Checks repo + SHA against policy results
- Blocks deploy on failure
Your top priorities, enforced.
Whatever's driving your adoption of Lunar, we've built the path for it.
-
For Teams Shipping with AI
AI writes at machine speed. Your guardrails don't have to fall behind.
AI Code Governance -
For Platform Engineering
You can't enforce what you can't see.
Managing Engineering at Scale -
For SRE Leaders
"This will never happen again." Finally true.
Reliability & Incident Prevention -
For Defense Contractors
Stop the pre-release compliance scramble.
Compliance for Defense & Government -
For Fintech & Banking
Passing the audit isn't the same as protecting your brand.
SDLC Governance for Finance
200+ Guardrails Included
Enforce standards across reliability, quality, security, and compliance — for human-written and AI-generated code alike.
Ready to Automate Your Standards?
See how Lunar can turn your AGENTS.md, engineering wiki, compliance docs, or postmortem action items into automated guardrails with our 200+ built-in guardrails.
AI agent rules & prompt files
Post-mortem action items
Security & compliance policies
Testing & quality requirements
