Add validated policy guardrails and compliance checks for AI coding agents.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "io.github.SureshKhemka/constraints-registry" MCP server from askskill: Run: claude mcp add 'io-github-sureshkhemka-constraints-registry' -- npx -y constraints-registry
Define a policy set for an AI coding agent: block hardcoded secrets, forbid overly permissive security groups, and require new infrastructure code to pass OPA, Conftest, Checkov, and Semgrep validation. Output practical constraint examples and validation guidance.
A set of enforceable policy constraints with validation flow and blocking guidance.
Design a CI workflow using constraints-registry so that when an AI agent submits Terraform, Kubernetes, or application code, OPA, Conftest, Checkov, and Semgrep run automatically and block merges on violations. Provide steps and configuration guidance.
A CI validation plan covering scan order, triggers, failure gates, and integration recommendations.
Using constraints-registry, create a security baseline for AI-assisted development covering code generation, IaC, dependency scanning, and secret detection, and explain whether each rule type should be handled by OPA, Conftest, Checkov, or Semgrep.
A scenario-based security baseline checklist with the appropriate policy engine or scanning tool for each rule.
Audit AI agent code for pre-deploy security risks missed by generic SAST.
Add deterministic security checks, host audits, and diagnostics to AI workflows.
Centralize AI code generation security rules across repositories with consistent governance.
Provides coding agents a queryable source of engineering constraints during code generation.
Provide persistent, verified memory and guardrails for AI coding agents.
Govern API access for AI agents, detecting breaking changes and blocking unsafe calls.