youtube-model-feederFood for your model — extract transcripts, key frames, OCR, slides, and LLM summaries from YouTube videos into structured AI-ready knowledge.
Install via ClawdBot CLI:
clawdbot install celstnblacc/youtube-model-feederGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Sends data to undocumented external endpoint (potential exfiltration)
POST → http://localhost:8000/jobsCalls external URL not in known-safe list
https://github.com/celstnblacc/youtube-model-feederAI Analysis
The skill's primary external call is to a localhost endpoint (localhost:8000/jobs), which is likely a local processing service under user control, not an unauthorized external server. The GitHub reference is for the skill's source code, not a runtime data sink. The risk is low as no clear exfiltration to third parties is present.
Audited Apr 16, 2026 · audit v1.0
Generated May 6, 2026
Teachers and course creators extract structured knowledge from tutorial videos, including transcripts, key frames, and OCR of code and slides, to build searchable lesson archives or generate summaries for students.
Developers and technical writers automatically generate documentation from video walkthroughs, capturing code snippets, terminal outputs, and slide content with timestamps for easy reference.
Researchers and analysts process conference talks, lectures, and webinars into structured knowledge bundles, enabling quick retrieval of specific points via semantic search in tools like Obsidian.
Marketing teams transform video tutorials into blog posts, social media snippets, and SEO-optimized text by extracting key insights, quotes, and visual highlights automatically.
Lifelong learners and professionals capture and organize knowledge from educational YouTube videos into a personal knowledge base, eliminating manual note-taking and improving retention.
Offer a free tier with limited video processing (e.g., 5 videos/month) and paid subscriptions for unlimited processing, priority queue, and advanced features like custom LLM models or team collaboration.
License the software to enterprises (e.g., universities, corporate training departments) for deployment on their own infrastructure, ensuring data privacy and compliance.
Charge developers per video processed via API, with tiered pricing based on volume and features like OCR or LLM summarization, enabling integration into third-party apps.
💬 Integration Tip
Integrate with Obsidian via exported markdown or ZIP bundles for semantic search, and consider automating video processing by connecting your API with notification services like Slack for job completion alerts.
Scored Jun 29, 2026
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.
AI social media video and content creation powered by CellCog. Instagram Reels, TikTok videos, Stories, carousels, social posts. Full video production from a single prompt — scripted, shot, stitched, and scored automatically.
Interact with Twitter/X — read tweets, search, post, like, retweet, and manage your timeline.
TikTok 数据查询与工具助手。覆盖视频详情、用户数据、搜索、广告、创作者工具、电商等模块。含部分交互触发和协议工具接口（已标注）。
Twitter/X 数据查询助手。覆盖推文详情、用户资料、搜索、评论、趋势等全功能。
YouTube 全场景数据查询助手。支持Web/V2双版本API，覆盖视频详情、频道数据、搜索、评论、字幕、Shorts等全功能。