Commit Comprehension Gate
Block merges until devs prove they read their own diff
What it does
CCG is a GitHub Action that blocks PR merges until the author correctly answers comprehension questions generated from their own diff using Claude. Built for teams where AI-generated code gets merged faster than anyone reads it. Completely stateless — the answer key lives in a hidden HTML comment in the PR itself. No database, no infrastructure. Just 3 files and an API key. Open source, MIT licensed, patent pending.
Does the same job
all alternatives →- 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…
- CCContinuous Claude – run Claude Code in a loopNov 2025 · github.com · ▲170
Continuous Claude is a CLI wrapper I made that runs Claude Code in an iterative loop with persistent context, automatically driving a PR-based workflow. Each iteration creates a branch, applies a focused code change, generates a commit, opens a PR via GitHub's CLI, waits for required checks and reviews, merges if green, and records state into a shared notes file. This avoids the typical stateless one-shot pattern of current coding agents and enables multi-step changes without losing intermediate reasoning, test failures, or partial progress. The tool is useful for tasks that require many…
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A little idea I got from playing with AI SWE Agents. Can AI help make sure we understand the code that our AIs write? PR Quiz uses AI to generate a quiz from a pull request and blocks you from merging until the quiz is passed. You can configure various options like the LLM model to use, max number of attempts to pass the quiz or min diff size to generate a quiz for. I found that the reasoning models, while more expensive, generated better questions from my limited testing. Privacy: This GitHub Action runs a local webserver and uses ngrok to serve the quiz through a temporary url. Your code…
- CSContinue – Source-controlled AI checks, enforceable in CIFeb 2026 · docs.continue.dev · ▲44
We 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…
- WBWe built an AI to review your pull requests2025 · infinitcode.ai · ▲53
Hey HN, We’re two developers (co-founders) with a team of 20 who got tired of spending hours reviewing PRs, so we built Infinitcode.ai, an AI-powered code reviewer that: - *Summarizes PRs in plain English*: No more deciphering 1,000-line diff jungles - *Catches more than bugs*: Security holes, performance pitfalls, code smells, even typos (yes, we’ll flag “vurnerabilities” and vulnerabilities) - *Zero onboarding*: Works instantly—no “let me learn your codebase for weeks” nonsense. Why we’re posting: We’re in alpha and need brutal honesty. Roast our tool, mock our UI, or tell us why AI will…
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