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Orbi takes a GitHub Issue from label to release. When an Issue is marked ai-ready, Orbi builds the change in a dedicated worktree and opens a pull request. A reviewer agent, separate from the one that wrote the code, compares the PR with the Issue's acceptance criteria and repairs it. Orbi then merges only that reviewed head and publishes a tagged GitHub release. It is installed from the GitHub repo, with the CLI on PyPI as orbi-cli and Docker images on GHCR and Docker Hub, and can also be...

...Covers the IAM family (KSI-IAM-MFA, KSI-IAM-APM, KSI-IAM-SNU, KSI-IAM-JIT, KSI-IAM-ELP, KSI-IAM-SUS, KSI-IAM-AAM) and MLA family (KSI-MLA-OSM, KSI-MLA-RVL, KSI-MLA-EVC, KSI-MLA-LET, KSI-MLA-ALA) in depth, with machine-readable YAML mappings, real AWS Config rule references, NIST 800-53 control crosswalks, and per-indicator evidence shapes that compliance engineers can use directly during 3PAO preparation. Includes the full FedRAMP machine-readable documentation (FRMR v0.9.43-beta) and a Python ksi-validator CLI for OSCAL package validation. Maintained by Boundera (https://boundera.io) as a community resource alongside the Boundera commercial product, which automates evidence collection across all 60 KSI indicators and 11 families on AWS, Azure, and GCP. MIT licensed.