Incident Investigate vs QA Loop vs GStack Investigate
Side-by-side comparison· 把候选放在一起看更容易选
| Editor's Pick· 编辑首选 Incident Investigate | QA Loop | GStack Investigate | |
|---|---|---|---|
| Rank· 排名 | #1Editor's Pick · 编辑首选 | #1 | #2 |
| In a sentence· 一句话 | No fixes until the cause is real. 原因还没坐实之前，不急着修。 | Open the product, try the flow, fix what breaks, repeat. 打开产品走一遍流程，发现问题就修，然后再验证。 | No fixes until the root cause is real. 根因没坐实之前，不急着动手修。 |
| Editor rating· 编辑评分 | |||
| Stars· 星标数 | 10k | 15k | 123k |
| Platforms· 运行平台 | CodexClaude Codelocal terminals | CodexBrowser automation | CodexClaude CodeLocal terminals |
| Risk· 风险 | Low risk · 低风险 | Medium risk · 中风险 | Low risk · 低风险 |
| Author· 作者 | |||
| Updated· 最近更新 | 2026-04-19 | 2026-04-17 | 2026-04-22 |
| Why pick this· 为什么选它 | Best for incidents where the fastest reflex would be the wrong fix. Forces an evidence-before-action loop: collect logs, list candidate hypotheses, verify each, only then propose a change. Pays for itself the moment it catches the kind of incident where "just restart it" would have masked a real data-integrity problem. Skip it for obviously cosmetic regressions — the cost of slowing down outweighs the cost of a re-deploy there. 在那种「第一反应反而是错的」事故里它最有用。强制走「证据—假设—验证—再动手」的顺序：先收集日志，列出候选假设，逐个验证，最后才提修复方案。只要救下一次本该用「重启就好」掩盖掉的真实数据完整性问题，回报就够了。但纯样式回归就别用它了，等回滚比慢思考更划算。 | Best browser QA pick when you need evidence to leave a paper trail. Each run produces screenshots, console diffs, and a reproducible action log — much harder for stakeholders to wave off than "I tested it locally." Works well as a pre-merge gate and for filing bugs with repro steps attached. Not for unit tests, and not for authenticated production sessions where the screenshot itself becomes a data risk. 做需要留证据链的浏览器 QA，它是最佳选择。每次跑都会产出截图、控制台 diff 和可重放的动作日志——比一句「我在本地测过了」更难被挡回去。适合做合并前关卡，也适合带证据提 bug。别用在单元测试场景，也别在敏感的登录态生产会话里用——截图本身就是数据风险。 | Best when the bug lives inside the code itself, not in operational state. Same "no fixes until the root cause is real" discipline as incident-investigate, but biased toward static code investigation: reads suspect modules, builds a hypothesis tree, asks for a failing test or repro before proposing a change. Strongest on flaky tests and intermittent failures where shallow patches make things worse. For ops-side incidents (logs, traffic, infra), incident-investigate fits better. bug 是在代码里而不是在运行态时，它最合适。和 incident-investigate 一样有「根因没明确前不修复」的纪律，但更偏静态代码调查：读可疑模块、建假设树、要求先有失败测试或复现，才允许改代码。在 flaky test 和间歇性故障这种「浅修反而更糟」的场景里最强。运维侧事故（日志、流量、基础设施）用 incident-investigate 更合适。 |
| Why skip· 为什么不选 | Quick cosmetic fixes 快速样式修补 | Pure unit testing 纯单元测试 | Workflows that require stronger human review than this catalog entry documents. 快速文案改动 |
| Install· 安装命令 | $codex /investigate | $codex /qa | $codex /investigate |
If you can only install one如果你只能装一个
Best for incidents where the fastest reflex would be the wrong fix. Forces an evidence-before-action loop: collect logs, list candidate hypotheses, verify each, only then propose a change. Pays for itself the moment it catches the kind of incident where "just restart it" would have masked a real data-integrity problem. Skip it for obviously cosmetic regressions — the cost of slowing down outweighs the cost of a re-deploy there.
在那种「第一反应反而是错的」事故里它最有用。强制走「证据—假设—验证—再动手」的顺序：先收集日志，列出候选假设，逐个验证，最后才提修复方案。只要救下一次本该用「重启就好」掩盖掉的真实数据完整性问题，回报就够了。但纯样式回归就别用它了，等回滚比慢思考更划算。
Larger teams with stricter security: combine the picks above; their coverage complements rather than overlaps.团队大、安全要求高？把首选和其它候选搭配使用——它们覆盖互补而不是替代。