Use when the user wants to improve a specific article under a fixed viral-scoring rubric, iterate on one article to raise its score, or run single-article scoring plus rewrite loops. Best for content optimization experiments where the scoring prompt stays fixed and the article text is the thing being changed.
Use when the user has a finished blog master draft and wants to publish it to multiple content platforms (知乎/掘金/CSDN/公众号 等) via the @wechatsync/cli tool. Handles pre-flight auth checks, platform selection, dry-run preview, and the actual sync. Do NOT use for writing, rewriting, compliance rewriting, or topic selection — this skill only publishes existing drafts as-is.
Use when the user wants to collect research material for an article or topic by gathering YouTube videos and web articles into a NotebookLM notebook, then running analysis queries and saving results as markdown. Best for "收集素材"、"给我找这个话题的相关视频和文章"、"整理成 NotebookLM 分析" type requests. Combines yt-dlp YouTube search, NotebookLM `nlm` CLI research, and markdown report output.
Use when the user wants to iterate on a viral-article scoring system itself, calibrate or improve a scoring prompt against labeled samples, or run batch scoring experiments on a fixed article set. Best for prompt-only scoring research where the evaluator scripts stay fixed and only the scoring rubric/prompt is meant to evolve.
Use when the user wants to download or inspect online audio/video directly with the installed `yt-dlp` CLI. Best for single videos, playlists, audio extraction, subtitle download, format inspection, output templates, cookies-from-browser flows, and practical troubleshooting of `yt-dlp` commands.