Documentation
Impact Gate starts with deterministic diff analysis.
Then turns that evidence into a release-ready E2E plan for pull requests, release branches, hotfixes, and shipped tags before you layer in optional AI generation or healing.
Impact → Plan → Gate
Start with impact, plan, and gate to make pull-request and release-readiness coverage decisions from a git diff.
How the evidence layer works
Learn route families, confidence scoring, plan artifacts, and where AI fits into the workflow without becoming the workflow.
See where it fits against commercial platforms
Compare Impact Gate honestly against hosted optimization, AI-first E2E, no-code automation, and monitoring-oriented tools.
Ship with confidence from one diff
Compare the current candidate to the last shipped tag and turn that delta into a focused test plan before you ship.
Ground generation against what your repo already knows
AI-generated specs are grounded against your local API surface and
suspicious methods are quarantined into
generated-needs-review/.
Use /qa from Codex or Claude as the front door
Give the agent a running app URL and a goal like “test this branch” or
“hunt checkout regressions,” then let the skill translate that into the
right impact-gate-qa run.
Layer generation and healing on after the plan is useful
Configure providers, inspect artifacts, and add autonomous workflows only after the deterministic path is already trustworthy.
CI, troubleshooting, and cost control
Use focused playbooks for PR gating, release diffs, AI safety, budget controls, and rollout troubleshooting.