When you activate Invisly, the first thing that happens is a capture — a precise, instant snapshot of your coding environment. The capture system is designed to be fast, lightweight, and accurate, giving the AI analysis engine exactly what it needs to understand your problem without slowing you down or drawing attention.Documentation Index
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Smart screenshot technology
Invisly captures high-fidelity screenshots of your coding environment using optimized system APIs that minimize resource consumption. The capture happens the moment you trigger Invisly, with no perceptible lag and no interruption to your workflow. You never have to stop what you’re doing to wait for the system to catch up. The underlying APIs are chosen specifically to avoid heavy CPU or memory usage, so Invisly stays quiet in the background until you need it.Selective area capture
You can define a specific region of your screen rather than capturing everything. This is useful when your screen contains multiple windows, browser tabs, or unrelated content alongside your code editor. By drawing a selection around just the relevant area — a single function, an error message, a specific file — you direct the AI’s attention exactly where it matters. Selective area capture is especially effective when:- You’re working in a split-screen layout and only one panel is relevant
- You want to isolate a single error message or stack trace
- You’re focused on a specific algorithm and don’t want surrounding boilerplate included
Multi-monitor awareness
Active display detection
Invisly identifies which monitor you’re actively working on and captures from that display automatically. You don’t need to configure anything when switching between screens.
Focused capture
Rather than capturing all displays at once, Invisly targets the screen where your input focus is, keeping the captured content relevant and the file size small.
Format optimization
Raw screenshots contain more data than the AI needs and can slow down analysis. Invisly processes each capture before sending it for analysis, optimizing the image format to preserve code readability while reducing file size. The optimization pipeline:- Sharpens text rendering to maintain character-level accuracy for code
- Removes visual artifacts that could confuse the analysis engine
- Normalizes contrast so syntax elements remain clearly distinguishable
- Compresses the image efficiently without degrading the legibility of identifiers, operators, or punctuation