claude-real-video is a local command-line tool that helps Claude or another language model inspect video by combining selected video frames with a transcript. It is for developers who want an AI agent to answer questions about videos from URLs or local files while reducing redundant visual input. The catalogue add-ons extend agent workflows around the tool.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add HUANGCHIHHUNGLeo/claude-real-video --skill claude-real-video-for-agentsgit clone --depth 1 https://github.com/HUANGCHIHHUNGLeo/claude-real-videoWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/huangchihhungleo/claude-real-video/claude-real-video-for-agents)<a href="https://agentmods.dev/skills/huangchihhungleo/claude-real-video/claude-real-video-for-agents"><img src="https://agentmods.dev/badge/skills/huangchihhungleo/claude-real-video/claude-real-video-for-agents/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/huangchihhungleo/claude-real-video/claude-real-video-for-agents"><img src="https://agentmods.dev/badge/skills/huangchihhungleo/claude-real-video/claude-real-video-for-agents.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high YARA Match · line 114 YARA rule matched a known malware signature (reverse shell, backdoor, ransomware, C2 framework, or info stealer).Fix: Remove the malware payload or compromised file entirely. Investigate how it entered the skill and audit all other artifacts for additional indicators of compromise.
- medium Privilege Escalation · line 26 Commands invoke sudo or root privileges. Verify this elevated access is necessary and justified.Fix: Avoid sudo/root unless strictly required. Prefer least-privilege patterns. If elevation is needed, document the justification and scope.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00066 | $0.02101 |
| Opus 5 | $0.00033 | $0.01051 |
| Sonnet 5 | $0.00013 | $0.00420 |
| Haiku 4.5 | $0.00007 | $0.00210 |
Grade B, and why
claude-real-video-for-agents scanned grade B with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 13d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Asks for rootmediumPrivilege escalation
A mod that escalates privileges can change anything on the machine, not only the project.
sudo apt install ffmpeg How it starts
The opening of the file, as written. The whole thing — 222 lines — stays where its author put it; the contents beside it link to each section on GitHub.
claude-real-video for AI agents
What is crv?
crv (claude-real-video) is a CLI tool that extracts meaningful frames and transcripts from videos so AI agents can "see" and "read" them. It uses scene-change detection (not fixed-interval sampling), sliding-window deduplication, and optional Whisper transcription.
Key advantage: Same 58-second clip at fixed 1fps = 58 frames. crv keeps the 26 that actually differ, and --grid packs them into 3 contact sheets. Fewer tokens, nothing missed.
Installation
Prerequisites
- Python 3.10+
- ffmpeg / ffprobe on PATH
# macOS
brew install ffmpeg
# Linux
sudo apt install ffmpeg
# Windows
winget install Gyan.FFmpeg
Install crv
# Recommended: with audio transcription support
pip install "claude-real-video[whisper]"
# Core only (frames + dedup)
pip install claude-real-video
The [whisper] extra never installs itself — without it there is no speech-to-text
(videos that ship their own subtitles still get a transcript).
Verify installation
crv --help
ffmpeg -version
Install as agent skill
Run the bundled installer to symlink this skill into all detected agent platforms:
bash install-skill.sh
Or manually copy to your agent's skill directory:
# Claude Code
cp -r skills/claude-real-video-for-agents ~/.claude/skills/
# Codex
cp -r skills/claude-real-video-for-agents ~/.codex/skills/
# OpenCode
cp -r skills/claude-real-video-for-agents ~/.opencode/skills/
# Gemini CLI
cp -r skills/claude-real-video-for-agents ~/.gemini/skills/
Usage
Basic: Watch a video from URL
crv "https://www.youtube.com/watch?v=VIDEO_ID"
Output in crv-out/:
frames/— deduplicated keyframestranscript.txt— plain-text transcriptMANIFEST.txt— summary for LLM consumption
Recommended: With grid and intent
crv "https://youtu.be/VIDEO_ID" -o crv-out --grid --why "what the user wants to know"
--grid— tiles frames into 3x3 contact sheets (cuts image count ~9x)--why— focuses the analysis on a specific question
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 13d ago First seen · 222 lines · 66 tokens per session scan B 0f70312abf8f
claude-real-video-for-agents is a skill published in the GitHub repository HUANGCHIHHUNGLeo/claude-real-video (2,132 stars, last pushed yesterday), licensed MIT. It adds 66 tokens to every session and 2,101 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it B with 1 finding (asks for root). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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