LetMeWatch: Python Plugin Adds Video Analysis to Claude via FFmpeg Scene Detection
A developer has created a Python plugin called LetMeWatch that enables Claude to analyze video content despite its lack of native video support. The tool addresses the specific use case of sending screen recordings of bugs to Claude for diagnosis.
How It Works
The plugin uses FFmpeg scene detection to extract only frames where the visuals actually change. It timestamps each extracted frame and feeds them to Claude in batches. This approach avoids using AI video models or complex infrastructure—it relies on frame extraction combined with Claude's existing multimodal vision capabilities.
Technical Implementation
- Written in Python (~200 lines of code)
- Uses FFmpeg for scene detection
- Extracts frames only when visual changes occur
- Adds timestamps to each frame
- Sends frames to Claude in batches
- Works on all platforms
- Open source (available on GitHub)
Practical Application
The developer tested the tool by recording a bug in a todo app and running the command /video-last. Claude successfully identified the exact line with the typo from watching the recording. This demonstrates how the tool can be used for debugging by having Claude analyze screen recordings of issues.
The project is available at github.com/BinyaminEden/letmewatch and represents a practical workaround for Claude's current video limitations using existing tools and Claude's vision capabilities.
📖 Read the full source: r/ClaudeAI
👀 See Also
Deblank: Tool to Strip Code Formatting for LLM Token Reduction
Deblank is an open-source tool that strips code formatting (indentation, whitespace, line breaks) before sending to LLMs, reducing tokens by ~30% for Java/C++ and ~9% for Python with ~76ms latency. It supports Python, Java, C/C++, C#, JS/TS, and Go.
ai-codex: Pre-index your codebase to save Claude tokens
ai-codex is a tool that generates compact markdown indexes of your codebase, allowing Claude Code to skip the initial exploration phase that typically consumes 30-50K tokens per conversation. It creates five files covering routes, pages, libraries, schemas, and components.
OpenClaw User Critiques Tool's Architecture and Safety Gaps
A Reddit user describes OpenClaw as the only tool making agent automation this accessible but criticizes its architecture for lacking a control layer for file operations, a protected kernel, proper context management, and built-in versioning or tests.
Session Siphon: Open Source Tool Consolidates AI Coding Agent Conversations
Session Siphon is a free, open source tool that consolidates and indexes conversation history from multiple AI coding agents across different providers and machines. The developer created it using Claude to solve the problem of tracking conversations across different platforms.