Cheqpoint
Stop your AI agent before it f*cks something up
Cheqpoint launched on September 4, 2026.
What it does
Most AI safety tools check what an AI agent says. Cheqpoint checks what it does: it pauses risky actions (refunds, deletions, deploys) and routes them to the right reviewer before they run. It takes one line of code, works with any agent framework, and notifies reviewers who can approve from the platform or Slack with full context: the risk, the agent's reasoning, and the exact request. Rules auto-approve safe actions; humans handle the rest.
Does a similar job
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Continue – Source-controlled AI checks, enforceable in CIFeb 2026 · docs.continue.dev · ▲44We now write most of our code with agents. For a while, PRs piled up, causing review fatigue, and we had this sinking feeling that standards were slipping. Consistency is tough at this volume. I’m sharing the solution we found, which has become our main product. Continue (https://docs.continue.dev) runs AI checks on every PR. Each check is a source-controlled markdown file in `.continue/checks/` that shows up as a GitHub status check. They run as full agents, not just reading the diff, but able to read/write files, run bash commands, and use a browser. If it finds…
- IBI built a tool to assist AI agents to know when a PR is good to goJan 2026 · dsifry.github.io · ▲45
I've been using Claude Code heavily, and kept hitting the same issue: the agent would push changes, respond to reviews, wait for CI... but never really know when it was done. It would poll CI in loops. Miss actionable comments buried among 15 CodeRabbit suggestions. Or declare victory while threads were still unresolved. The core problem: no deterministic way for an agent to know a PR is ready to merge. So I built gtg (Good To Go). One command, one answer: $ gtg 123 OK PR #123: READY CI: success (5/5 passed) Threads: 3/3 resolved It aggregates CI status, classifies review comments…
Scan your AI agents for dangerous capabilitiesJul 2026 · github.com · ▲44Open-source security gateway & static scanner for AI agents. Enforce role-based access control (RBAC), human-in-the-loop approvals, segregation of duties, and cryptographically signed, offline-verifiable audit logs. - makerchecker/MakerChecker
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