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Claude plugin reportedly recovers Kindle highlights blocked by Amazon export limits
A third-party Claude Code skill extracts full Kindle highlights, including those truncated or hidden by Amazon’s undocumented export restrictions.
Engineers working with personal data extraction or AI-assisted tooling may find this approach useful for bypassing platform-imposed limits. However, the solution is macOS-specific and relies on undocumented Kindle internals, which could break with future updates. The method also raises questions about data ownership and platform control.
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The plugin recovers highlights Amazon truncates or hides entirely from its notebook export feature.
It combines browser automation, OCR, and Kindle app data files to reconstruct blocked text locally.
The tool is macOS-only and requires specific software dependencies, including Claude Desktop and Xcode tools.
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This Claude Code skill addresses a long-standing frustration for Kindle users: Amazon’s undocumented export limits on highlights. The tool recovers text that Amazon truncates or hides entirely from its notebook page exports, using a combination of browser automation, OCR, and Kindle app data files. The approach is notable for its precision, with recovered text aligning closely to the Kindle app’s own position ruler. However, the solution is tightly coupled to macOS, relying on AppleScript, Vision framework, and the Mac Kindle app’s SQLite database.
The technical implementation is multi-stage. First, it scrapes visible highlights from the notebook page DOM. For blocked text, it captures rendered pages from the Cloud Reader via canvas, then uses Apple’s Vision framework for local OCR. The Kindle app’s annotation database provides exact character positions, which the tool uses to trim OCR output to the correct extents. The result is a Markdown file with location-cited, blockquoted text, including flags for recovered or approximate content. This method avoids cloud-based OCR, keeping data local and token-free.
Adopting this tool requires significant setup. Users must install Claude Desktop with its browser-control extension, enable JavaScript from Apple Events in Chrome, and have the Mac Kindle app with the target book downloaded. Xcode Command Line Tools and Python 3 are also prerequisites. The macOS-only dependency is a hard limit, Windows or Linux users are excluded. Additionally, the tool’s reliance on undocumented Kindle internals means it could break if Amazon changes its app or web interface. The license is MIT, but the scope is explicitly personal use, as extracted book text remains copyrighted.
The skill’s existence highlights broader tensions around data ownership and platform restrictions. Amazon’s export limits are undocumented and unadjustable, forcing users to accept truncated or missing highlights. This tool bypasses those limits but does so by reverse-engineering Kindle’s internals, a fragile approach. For engineers, it demonstrates how AI-assisted tooling can bridge gaps left by platform policies, but also underscores the risks of building on undocumented or unstable foundations. The tool’s precision is impressive, but its narrow compatibility and potential fragility limit its broader applicability.
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