CodexQA Jev Browser

简体中文 · How it works · Known limitations

Jev Browser is one skill in CodexQA: local Agent Skills that check whether code is actually good after it is written. This repository is the standalone project. The same skill is also installed from the CodexQA catalog.

GUI-model browser automation sends a screenshot to a vision model on every step. Recognition spends vision tokens, the loop waits for the model to read the image, and the click lands on coordinates.

CodexQA Jev Browser finds controls from an index built inside the page and treats visible page evidence as the result. Replay, goal runs, case generation, and site exploration share that index. The browser is Playwright Chromium. This repository has no benchmark against vision GUI models. The rows below are the structural answers to those costs.

On TypeSafe’s published System One comparison, a Jev decision is 40×–200× faster than a frontier LLM on the same kind of question (70–500 ms, against multi-second LLM calls). Their workflow demo is 193.6× faster and 444.6× cheaper: $0.000081 in 0.114 s versus $0.013880 in 8.566 s. TypeSafe calls that pair the high end of real-world gains. Jev lists input at $0.042 per million tokens, 238× lower than Claude Fable 5.1, and does not bill output tokens. These figures are for the decision call, not for loading the page or saving the report. Source: TypeSafe and the launch post.

What raises the pass rate

The knowledge base is the main lever. Jev only chooses an indexed control, and the characters it can type are phrases already in the goal. It does not know that a Baidu cite is an ad, that the left city box is the departure city, or that a login dialog means stop. Those facts belong in knowledge//*.md.

A failed live run is usually a missing or wrong note, not a missing selector. Read the report, name the control the model should have used or avoided, and add that sentence to the matching note. hosts matches the site. keywords match the goal. general: true is attached on every run, such as the login-dialog stop. Notes are reference. The model still has to pick an index that was observed. Do not put that site’s fill rules into src/policy.ts.

Where traditional automation gets stuck