Skillget

eyeroll

agent
Guvenlik Denetimi
Uyari
Health Uyari
  • License — License: MIT
  • Description — Repository has a description
  • Active repo — Last push 0 days ago
  • Low visibility — Only 5 GitHub stars
Code Gecti
  • Code scan — Scanned 12 files during light audit, no dangerous patterns found
Permissions Gecti
  • Permissions — No dangerous permissions requested
Purpose
This plugin analyzes video content from screen recordings, links, and local files to help AI coding agents understand bugs, implement features, and generate code actions based on what it sees.

Security Assessment
Overall risk: Medium. The tool inherently makes network requests to download videos via yt-dlp and sends extracted frames and audio to external AI APIs (like Google Gemini or OpenAI). Depending on the videos analyzed, this could expose sensitive code, proprietary screen recordings, or personal data to third-party LLMs. Users can mitigate this by using the local Ollama backend. No hardcoded secrets were found in the scanned code. While the `/eyeroll:fix` command executes significant autonomous actions (grep, read, write, run tests, and raise PRs), it requires explicit user invocation and no dangerous system-level permissions were requested.

Quality Assessment
The project is licensed under the permissive MIT license, which is excellent for open-source adoption. Development appears highly active, with the most recent code push happening today. However, it currently has extremely low community visibility with only 5 stars on GitHub. Because it is a very new and niche tool, it has not yet undergone broad community testing or security auditing.

Verdict
Use with caution — the codebase appears clean and is actively maintained, but its low visibility means it lacks proven maturity, and sending screen recordings to external AI APIs inherently carries data privacy risks.
SUMMARY

AI eyes that roll through video footage — watch videos, understand them, turn them into code actions.

README.md

eyeroll

AI eyes that roll through video footage — watch, understand, act.

eyeroll is a Claude Code plugin that analyzes screen recordings, Loom videos, YouTube links, and screenshots, then helps coding agents fix bugs, build features, and create skills.

Install

# Add the plugin to Claude Code
npx skills add mnvsk97/eyeroll

# Install the CLI
pip install eyeroll[gemini]      # Gemini Flash API (recommended)
pip install eyeroll[openai]      # OpenAI GPT-4o
pip install eyeroll              # Ollama only (local, no API key)
pip install eyeroll[all]         # everything

Setup

/eyeroll:init

Picks your backend, configures API key, and generates codebase context — all in one step.

Commands

Command What it does
/eyeroll:init Set up eyeroll — pick backend, configure API key, generate .eyeroll/context.md
/eyeroll:watch <url> Analyze a video and present a structured summary
/eyeroll:fix <url> Watch a bug video → diagnose → fix the code → raise a PR
/eyeroll:history List past video analyses

Usage

In Claude Code

You: /eyeroll:watch https://loom.com/share/abc123
     → Analyzes video, presents: what's shown, the bug, key evidence, suggested fix

You: /eyeroll:fix https://loom.com/share/abc123
     → Watches video, greps codebase, finds the bug, fixes it, raises a PR

You: watch this tutorial and create a skill from it: ./demo.mp4
     → video-to-skill activates, watches video, generates SKILL.md

You: /eyeroll:history
     → Lists past analyses with timestamps and sources

Standalone CLI

eyeroll watch https://loom.com/share/abc123
eyeroll watch ./bug.mp4 --context "checkout broken after PR #432"
eyeroll watch ./bug.mp4 -cc .eyeroll/context.md --parallel 4
eyeroll watch ./bug.mp4 --backend ollama -m qwen3-vl:2b
eyeroll history

How it works

/eyeroll:watch https://loom.com/share/abc123
    ↓
1. Download video (yt-dlp)
    ↓
2. Extract frames (1 per 2s, deduplicate, enhance contrast)
    ↓
3. Analyze frames (Gemini / GPT-4o / Qwen3-VL)
   + transcribe audio if present
    ↓
4. Cache intermediates (reuse on next run)
    ↓
5. Synthesize report with codebase context:
   - Bug Description
   - Fix Directions (Visible / Codebase-informed / Hypothesis)
   - Search patterns for the coding agent
    ↓
6. Present summary to user
    ↓
/eyeroll:fix goes further:
   → grep codebase → read files → implement fix → run tests → PR

Backends

Backend Video Audio API Key Cost Best for
gemini Direct upload Yes GEMINI_API_KEY ~$0.15 Best quality
openai Frame-by-frame Whisper OPENAI_API_KEY ~$0.20 Existing OpenAI users
ollama Frame-by-frame No None Free Privacy, offline

Ollama auto-installs if not found (macOS/Linux).

Codebase context

/eyeroll:init generates .eyeroll/context.md — a summary of your project that eyeroll uses to ground its analysis in real file paths instead of hallucinating them.

Without context, all file paths in the report are labeled as hypotheses.

Caching

eyeroll caches frame analyses and transcripts in .eyeroll/cache/. Same video = no re-analysis. Different --context re-runs only the cheap synthesis step.

eyeroll watch video.mp4                    # full analysis (~15s)
eyeroll watch video.mp4 -c "new context"   # instant — cached frames
eyeroll watch video.mp4 --no-cache         # force fresh

Plugin structure

eyeroll/
  commands/              ← slash commands
    init.md              ← /eyeroll:init
    watch.md             ← /eyeroll:watch
    fix.md               ← /eyeroll:fix
    history.md           ← /eyeroll:history
  skills/                ← background skills
    video-to-skill/      ← activated by "create a skill from this video"
  eyeroll/               ← Python CLI package
    cli.py, watch.py, analyze.py, extract.py, backend.py, history.py
  tests/                 ← 143 unit + 8 integration tests

Supported inputs

Input Formats
Video .mp4, .webm, .mov, .avi, .mkv, .flv, .ts, .m4v, .wmv, .3gp, .mpg, .mpeg
Image .png, .jpg, .jpeg, .gif, .webp, .bmp, .tiff, .heic, .avif
URL YouTube, Loom, Vimeo, Twitter/X, Reddit, 1000+ sites via yt-dlp

Development

git clone https://github.com/mnvsk97/eyeroll.git
cd eyeroll
pip install -e '.[dev,all]'
pytest                                                    # unit tests
pytest tests/test_integration.py -v -m integration        # real API tests

License

MIT

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