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content-scout

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YouTube channel monitoring and daily content briefing pipeline. Monitors configured channels for new uploads, downloads videos, extracts/classifies visual frames (charts, slides, screens vs talking heads), transcribes audio, and generates a daily markdown brief with key takeaways. Use when: (1) processing YouTube videos for visual and transcript analysis, (2) generating daily content briefs from monitored channels, (3) running the content-scout pipeline or any of its steps, (4) managing channel watchlists, (5) frame extraction or classification tasks. Requires: yt-dlp, ffmpeg, Python 3.10+, PIL/Pillow, imagehash, python-slugify. Optional: OpenAI API (transcription fallback), notion-client (Notion sync).

195 days ago

Transcript Studio

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Deep YouTube video processing into rich Notion pages with speaker-diarized transcripts, embedded visual frames, and AI-generated summaries. Use when: (1) user asks to process, transcribe, or analyze a YouTube video, (2) creating a Notion page from a video, (3) running the transcript studio pipeline, (4) generating summaries, chapters, or shorts candidates from video content, (5) setting up a Transcript Studio Notion database. Depends on content-scout skill for frame extraction and classification steps. Requires: Apple Silicon Mac (mlx-whisper), ffmpeg, yt-dlp, Python 3.10+.

195 days ago

FAQ

AgentCC is a discovery hub for AI agent capabilities. We index Agent Skills as the primary dataset, and also organize MCP servers and selected AI tools so developers can quickly find, compare, and evaluate what to integrate into their workflows.
An Agent Skill is a reusable capability package for an AI agent. It can define workflows, tool usage patterns, domain knowledge, or execution rules that help the agent perform more reliably in a specific task or environment.
AgentCC is a resource and discovery layer, not a one-click installer. On each skill page, you should review the repository, file tree, install command, and usage notes, then integrate it according to the runtime or client you are using.
No. AgentCC primarily indexes external repositories and metadata. We help you understand what a skill is, where it comes from, and how it may be used, but execution and security decisions still belong to your own runtime environment.
No directory can guarantee absolute safety. AgentCC can help surface repository links, file structures, and metadata, but you should still verify permissions, external dependencies, API usage, and code quality before using a skill in production or on sensitive machines.
Yes. AgentCC is designed to be an evolving resource graph. As the submission and curation workflow matures, contributors will be able to recommend high-quality skills, MCP servers, and AI tools into the directory.
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