Intent
What the team meant the AI change to do.
AI pull request control
Control AI pull requests before merge.
Abizor is a control layer for AI pull requests. It preserves AI change state from intent to merge: intent, scope, facts, receipts, readiness, and delivery boundary.
Agents can write the patch. They should not become the authority for what the change means.
Live todayCI proof
Canonical truthevent log
ProjectionChange Record
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This page is for
Teams defining the control model for AI PR change state.
Use this page when the question is organizational: how intent, scope, facts, receipts, readiness, and delivery boundary stay attached to AI-made pull requests across tools and retries.
Search intent
For teams asking how to control AI pull requests.
AI coding tools move quickly, but the merge decision still needs independent state. Abizor checks whether the pull request is still the intended change, whether the evidence supports it, and whether the next delivery step is allowed.
Required checks tell you whether CI passed. Abizor tells you whether the AI change is still the change you meant to ship.
What Abizor keeps attached to the PR
State that survives chat resets, retries, and repair branches.
Scope
Which paths and surfaces the change is allowed to touch.
Facts
Observed repository, pull request, CI, and authority state from the run.
Receipts
What each allowed action returned after execution.
Readiness
Whether fresh facts and receipts support the next step.
Delivery boundary
Where Abizor stops, blocks, or moves toward merge.
Boundary
Control layer, not another coding agent.
Abizor does not write the code for you. It checks whether the AI change is still bounded, evidenced, replayable, and ready to move forward.
The event log remains canonical truth. The Change Record, GitHub Check, PR comment, summary, and proof report are projections or evidence over that log.
Run Abizor on one AI pull request.
Start with the PyPI package and GitHub Actions CI proof. No hosted app or GitHub App install is required.
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