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AI EngineeringTypeScript

Video Perception

by jordanrendric

Video Perception is an AI Engineering skill for Claude Code, published by jordanrendric in claude-video-vision.

1.2K stars152 forkson jordanrendric/claude-video-visionAdded 2026/08/20+1% in starsRepository updated 2026/08/07

View source on GitHub Download repo ZIP

claude-codeclaude-code-pluginffmpeggeminimcpmcp-servermultimodalvideo-analysiswhisper

Install in seconds

Install Video Perception

Copy Video Perception into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.

terminal

npx degit https://github.com/jordanrendric/claude-video-vision/tree/main/skills/video-perception ~/.claude/skills/video-perception

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/jordanrendric/claude-video-vision.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file: skills/video-perception/SKILL.md in jordanrendric/claude-video-vision
Installs to: ~/.claude/skills/video-perception
Collection: The only skill cataloged from this repository
Category: AI Engineering — 2451 skills

What Video Perception does

Video Perception analyzes video files and YouTube URLs by extracting frames, transcribing audio, and detecting scene changes. Use it when asked to watch, review, or answer questions about a video.

Video Perception is cataloged under AI Engineering on DirSkills. Video Perception comes from a repository tagged claude-code, claude-code-plugin, ffmpeg, gemini and mcp.

Documentation

README

Excerpt

Video Perception

You have access to video understanding tools via the claude-video-vision MCP server.

Available Tools

video_analyze — Analyze video structure with ffmpeg filters (scene changes, silence, motion, etc.). Use this BEFORE extracting frames to plan your strategy.
video_watch — Extract frames + process audio from a video. Supports variable FPS/resolution per segment.
video_detail — Drill into specific segments. Separates extraction from viewing — extract many frames, view few at a time.
video_info — Get video metadata without processing.
video_configure — Change settings (backend, resolution, enable_index, etc.).
video_setup — Check/install dependencies.

Workflow

IMPORTANT: You MUST follow these steps in order. Do NOT skip step 2.

This is the opening of the README. Read the full README on GitHub.

Frequently asked about Video Perception

How does Video Perception compare to other AI Engineering skills?
Video Perception ranks #1140 by stars among the 2451 AI Engineering skills in this catalog. The most-starred ones next to it are Architecture Decision Records, AI-First Engineering and Agentic OS. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of Video Perception against them. Open each page to compare what they document and how they install.

More AI Engineering skills

Video Perception is one of 2451 AI Engineering skills cataloged on DirSkills, ranked #1140 by stars among them.

Browse all AI Engineering skills →

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Architecture Decision Records captures architectural decisions made during Claude Code sessions as structured ADRs, recording context, alternatives, and rationale. Use it when significant technical choices are made so future developers understand why the codebase is shaped the way it is.

AI-First Engineering

AI-First Engineering defines process, review, and architecture standards for teams where AI agents produce most implementation output. Use it to set ownership rules, quality gates, and evaluation criteria for agent-generated code.

Agentic OS

Agentic OS codifies a persistent multi-agent operating system architecture for Claude Code. Use it when building a multi-agent workflow with file-based memory, slash commands, and scheduled automation that survives session restarts.