bigarrow: A Mac Visual Clicking Tool That Points the Way for AI Agents

AI Agents can see your screen, but they struggle to tell you exactly where to click. bigarrow tries to fill that gap in the simplest way possible—by drawing a big arrow on the screen that points directly to where you need to click.

The developer spent a week using bigarrow alongside AI coding agents like Claude Code and Codex. Here is the complete set of hands-on findings and observations.

What bigarrow Is

bigarrow is a Mac app whose core function does exactly one thing: it turns coordinates output by an AI Agent into a visible arrow on the screen. The arrow appears, you click where it points, and the arrow disappears.

Its positioning is as a "visual feedback layer." It doesn't do the Agent's job for it, and it doesn't take over your clicks. The AI Agent decides "where to click," while bigarrow makes "where" visually obvious.

From a product design perspective, it shifts the collaboration interface between AI and humans from textual descriptions to spatial indicators. In multi-step UI operation scenarios, this can significantly reduce comprehension overhead.

How AI Agents output coordinates: Before tools like bigarrow existed, AI Agents typically had two paths for interacting with the screen. The first was for the Agent to directly call the system's accessibility API (such as macOS's Accessibility API) and perform clicks itself, entirely invisibly to the human. The second was for the Agent to describe the location in natural language—for example, "click the save button in the top right"—leaving the human to find and click it. The former is a black box that's hard to intervene in; the latter is highly error-prone when the interface is complex or elements are densely packed. bigarrow takes a third path: the Agent outputs an absolute screen coordinate (usually x and y pixel values in the screen coordinate system), and bigarrow reads that coordinate and overlays a visual marker at the corresponding position, after which a human performs the actual click. The benefit is that it preserves the human's control as the final executor, while turning the "find the element" step from semantic understanding into pixel-level positioning.

Core Features at a Glance

bigarrow's feature list isn't long, but each item revolves around "making visual guidance reliably land":

• Visual pointing: Displays a large arrow at precise screen coordinates rather than a text description
• Agent integration: Supports Claude Code, Codex, and any AI Agent that can output coordinates
• Arrow customization: Size, color, and style are all adjustable
• Keyboard shortcuts: Trigger arrow display with a single keystroke
• Multi-monitor support: Can work across multiple screens
• Lightweight design: Extremely low CPU and memory usage

From the feature design, it's clear that bigarrow doesn't try to replace existing toolchains. Instead, it lets different Agents share a single visual output standard. This "pluggable" positioning is relatively rare among similar tools.

Screen overlay layers and coordinate tracking APIs: The reason bigarrow can draw arrows on a Mac comes down to macOS's window layering capabilities. Above normal application windows, there exists a special class of window that can be set to be borderless, have a transparent background, and not receive mouse events (click-through), effectively acting like a transparent canvas floating above the top of the desktop. bigarrow uses this type of window to draw arrows, so the arrow doesn't block your normal clicking when it appears, and leaves no trace when it disappears. Coordinate tracking relies on macOS's independent coordinate system management for multiple monitors: each screen has its own origin and resolution, and the system provides interfaces to convert global coordinates into local coordinates on a given screen. When arrows land on the wrong screen under multi-monitor setups, this is essentially a misjudgment in this coordinate conversion process when stitching together the monitor layout.

What Actually Works Well in Practice

The developer used bigarrow with Claude Code to automate a complex UI workflow. The process was: have Claude output click coordinates, have bigarrow display an arrow on screen, then click according to the arrow. Compared to descriptive instructions, this approach eliminates a lot of guessing and trial and error.

Agent integration was the most stable part of the experience. bigarrow remains open about Agent choice; users can freely switch between different Agents without being locked into any one vendor. The developer tested multiple Agents with the same workflow and found that coordinate accuracy varied noticeably between them—but the choice always remained with the user, rather than being constrained by bigarrow.

The lightweight design is also a plus. After running continuously in the background for a week, there was no lag, abnormal battery drain, or conflicts with other applications. For a always-on tool, this kind of "non-intrusiveness" is itself part of the core experience.

Issues Exposed in Real-World Use

bigarrow isn't perfect, and several issues came up repeatedly during testing.

On coordinate accuracy, the auto-detection feature locates elements based on the Agent's description, but it isn't always accurate—sometimes the arrow points to the wrong location. Manually selecting coordinates is more reliable, but then you lose the point of auto-detection.

In multi-monitor scenarios, bigarrow occasionally puts the arrow on the wrong screen, causing directional confusion. Manually specifying the monitor can solve this, but again it goes against the original intent of "automatic multi-screen support."

Keyboard shortcut conflicts with other applications are also a frequent problem. When conflicts occur, bigarrow's triggering becomes unreliable. Manual configuration can work around this, but the operational cost goes up.

These issues share a common pattern: there is tension between the convenience and the reliability of automation. Once auto-recognition fails, users are forced back into manual mode.

Why AI Agent output coordinates are inaccurate: Getting an AI Agent to give precise coordinates is itself a hard problem. When most current multimodal models look at a screenshot, their perception of pixel positions is relatively fuzzy—they can roughly tell that "this button is in the lower-right part of the image," but when converting that to absolute screen pixels, the error is often in the tens to hundreds of pixels. The denser the interface elements and the higher the resolution, the more pronounced the deviation. In addition, screenshot scaling, the conversion between physical and logical pixels on Retina displays, and differences in coordinate origins between browsers and native apps all introduce error. This is why bigarrow's auto-detection works on simple interfaces but easily points wrong on complex ones: the error mainly comes from the Agent's localization capability, not from bigarrow's drawing layer.

Pricing and Platform Constraints

bigarrow is free for personal use, with Pro features available for a one-time purchase of $9.99—no subscription.

As for platform, bigarrow only supports Mac. It relies on macOS-specific screen overlay and coordinate tracking APIs, and there is currently no Windows or Linux version. If you're not in the Mac ecosystem, this tool isn't an option for now.

Compared with other visual feedback tools, bigarrow's strengths lie in AI Agent integration and visual pointing capabilities, while its weakness is that its UX polish in general scenarios isn't as good as mature products. In other words, it may not feel smooth enough for ordinary users, but it's actually more appealing to advanced users who want to control their automation workflows.

Who It's For

bigarrow's target user profile is fairly focused:

• Developers who use AI coding agents daily and want more intuitive visual feedback
• Teams that need to automate complex UI workflows
• Users who care about privacy and want all processing to stay local
• Developers using multiple monitors who want a unified interaction interface
• Teams that need to audit AI decisions and want to retain visual evidence

From these scenarios, it's clear that bigarrow is better suited to users who treat AI Agents as production tools, rather than casual users just trying things out.

Expectations to Adjust Before Getting Started

The most common misconception is expecting bigarrow to be "perfect." Giving up after a single arrow points to the wrong place and then reverting to text descriptions is the most typical path to failure.

bigarrow is a tool, not magic. It performs excellently on some tasks and isn't suitable for others. The right way to use it is to apply it to scenarios where visual pointing genuinely adds value—such as complex UI workflows, multi-step operation processes, and situations where text descriptions themselves are unclear.

Don't use it for every task, and don't dismiss it because of one failure. There's really only one criterion for judgment: does it help you get the work done? The best development environment is the one you truly understand.