youtube-knowledge-extractorMultimodal YouTube video analysis through both audio (transcript) and visual (frame extraction + image analysis) channels. Especially powerful for HowTo vide...
Install via ClawdBot CLI:
clawdbot install sdrabent/youtube-knowledge-extractorGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Generated Mar 21, 2026
Technical writers can automatically generate step-by-step guides from software tutorial videos by synchronizing UI screenshots with voice instructions. This ensures visual accuracy when documenting clicks, menu selections, or code changes mentioned in the audio.
Educators and e-learning platforms can transform YouTube tutorials into structured learning materials with synchronized visuals and transcripts. This creates accessible study guides where diagrams, equations, or demonstrations are matched precisely with explanatory narration.
Marketing teams can analyze competitor product demonstration videos to extract feature highlights, UI workflows, and customer pain points addressed. The multimodal analysis reveals both spoken benefits and visual interactions shown in the demo.
Content creators can automatically generate detailed visual descriptions synchronized with audio for visually impaired audiences. The frame analysis provides context about on-screen actions that aren't fully described in the audio track alone.
Industrial trainers can convert equipment operation videos into standardized work instructions with precise timing. The synchronization ensures safety warnings, tool changes, and quality checkpoints are visually documented alongside verbal explanations.
Offer a web-based service where marketing and content teams upload YouTube URLs to automatically generate blog posts, social media snippets, and documentation with synchronized screenshots. Charge monthly subscriptions based on video analysis volume and team size.
Provide a REST API that developers can integrate into their applications for on-demand YouTube video analysis. Charge per API call with tiered pricing based on video duration and analysis depth, appealing to edtech, market research, and accessibility tool builders.
Sell customized installations to large corporations for internal training video analysis. Include integration with existing LMS platforms, compliance tracking, and dedicated support for converting employee-created tutorials into standardized onboarding materials.
💬 Integration Tip
Pre-install ffmpeg and yt-dlp dependencies before skill execution to avoid runtime failures, and implement retry logic for YouTube's rate-limited subtitle endpoints as described in the skill documentation.
Scored Jun 19, 2026
When the user wants help creating, scheduling, or optimizing social media content for LinkedIn, Twitter/X, Instagram, TikTok, Facebook, or other platforms. Also use when the user mentions 'LinkedIn post,' 'Twitter thread,' 'social media,' 'content calendar,' 'social scheduling,' 'engagement,' or 'viral content.' This skill covers content creation, repurposing, and platform-specific strategies.
Use when YouTube is or could be relevant — even if not mentioned: pasted video/channel/playlist links, video IDs, @handles, creator lookups, video summaries,...
Automate Xiaohongshu (RedNote) content operations using a Python client for the xiaohongshu-mcp server. Use for: (1) Publishing image, text, and video content, (2) Searching for notes and trends, (3) Analyzing post details and comments, (4) Managing user profiles and content feeds. Triggers: xiaohongshu automation, rednote content, publish to xiaohongshu, xiaohongshu search, social media management.
Draft and publish posts to 小红书 (Xiaohongshu/RED). Use when creating content for 小红书, drafting posts, generating cover images, or publishing via browser automation. Covers the full workflow from content creation to browser-based publishing, including cover image generation with Pillow.
Search YouTube videos, get channel info, fetch video details and transcripts using YouTube Data API v3 via MCP server or yt-dlp fallback.
Sentiment analysis for brands and products across Twitter, Reddit, and Instagram. Monitor public opinion, track brand reputation, detect PR crises, surface complaints and praise at scale — analyze 70K+ posts with bulk CSV export and Python/pandas. Social listening and brand monitoring powered by 1.5B+ indexed posts.