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video-bug-prompt

Extract frames from bug videos and generate PDF and Markdown bug reports.

Updated Feb 28, 2026
Search Tags:#debugging#ai#report generation#video processing#code insights#bug analysis
One-click install
npx skills add https://github.com/ramirlm/skillshare-ramir --skill video-bug-prompt
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: video-bug-prompt
Source: https://github.com/ramirlm/skillshare-ramir/tree/main/video-bug-prompt
Command: npx skills add https://github.com/ramirlm/skillshare-ramir --skill video-bug-prompt

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires ffmpeg, pandoc, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill automates the tedious process of analyzing video recordings of software bugs, transforming raw footage into actionable reports with code insights.

Core Features & Use Cases

  • Automated Bug Analysis: Analyzes video frames to pinpoint exact bug occurrences.
  • Contextualization: Integrates with project documentation (Obsidian) and code to provide relevant context.
  • Report Generation: Creates detailed reports (PDF/Markdown) with visual timelines, code insights, and autonomous agent instructions.
  • Use Case: You encounter a visual bug in your application. You provide the video recording to the Skill, which then analyzes it, identifies the problematic frames, correlates them with your codebase, and generates a comprehensive bug report with suggested fixes.

Quick Start

Use the video-bug-prompt skill to analyze the bug in the video located at ~/Downloads/bug-login.mp4.

Frequently Asked Questions about video-bug-prompt

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I analyze a video recording of a software bug?▼

To analyze a video recording of a software bug, you can use an AI-driven tool to extract key frames, perform visual analysis, and correlate findings with your codebase. This process pinpoints exact bug occurrences and generates detailed reports.

Can I automatically generate bug reports from video footage?▼

Yes, you can automatically generate bug reports from video footage. The analysis tool extracts key frames, identifies visual timelines, provides code insights, and outputs comprehensive reports in both PDF and Markdown formats.

Do I need ffmpeg and pandoc to process video bug reports?▼

Yes, you need ffmpeg installed for video frame extraction and pandoc for generating PDF bug reports. These dependencies are required to process the video footage and output the final analyzed markdown and PDF documents.

How does AI bug analysis integrate with project documentation?▼

AI bug analysis integrates with project documentation by correlating extracted video frames with your existing Obsidian notes and indexed code. This contextualization provides relevant background and deeper code insights within the generated bug report.

What is the best way to pinpoint UI bugs from screen recordings?▼

The best way to pinpoint UI bugs from screen recordings is through AI-driven visual analysis. This approach automatically identifies problematic frames, correlates them with your source code, and highlights the exact moments the visual bugs occur.

What formats are supported for outputting code insights from bug videos?▼

Code insights and bug analysis results from videos are outputted in PDF and Markdown formats. These reports include visual timelines, identified key frames, and specific instructions designed for autonomous agents.

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