By xiaomoBoy
Claude Code skills for long-form content workflow: research collection via NotebookLM, multi-platform publishing via wechatsync, viral-score evaluation, single-article rewrite loops, and yt-dlp media helpers.
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.
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A toolkit of Claude Code skills for long-form content creators — research, score, rewrite, and publish, end to end.
中文版: README.zh-CN.md
5 skills extracted from a real working writing setup. They are opinionated, narrow in scope, and meant to compose. Each one does one thing.
Skill descriptions (frontmatter) are English so they trigger correctly. Skill bodies are written in Chinese — that's the author's working language. If you don't read Chinese, the script files and command examples are still usable, and the descriptions tell you what each skill does. PRs translating bodies welcome.
Add this repo as a Claude Code marketplace, then install:
/plugin marketplace add xiaomoBoy/claude-writing-skills
/plugin install claude-writing-skills@claude-writing-skills
That's it — you now have all 5 skills available.
Each skill may need its own upstream CLI (e.g. yt-dlp, nlm, codex, wechatsync). See INSTALL.md for the full per-OS install guide (macOS / Linux / Windows + verification + troubleshooting).
Not using Claude Code? See INTEGRATIONS.md for using these skills with Cursor, Aider, Codex CLI, the Claude API directly, or as standalone scripts.
| Skill | What it does | Depends on |
|---|---|---|
| research-collector | Collect YouTube videos + web articles for a topic, push into a NotebookLM notebook, run analysis queries, save results as markdown. | notebooklm-mcp-cli (nlm), yt-dlp |
| publisher-wechatsync | Publish a finished markdown article to 知乎 / 掘金 / CSDN / 公众号 etc. as drafts via the wechatsync CLI. Handles pre-flight checks, dry-run, and image-path normalization. | @wechatsync/cli + Chrome extension |
| article-optimizer | Score a single article against a fixed viral-content rubric, then iterate rewrites round by round to raise the score. | codex CLI |
| score-optimizer | Calibrate / improve the scoring rubric itself by batch-scoring a labeled sample set. The companion to article-optimizer when you want to tune the evaluator. | codex CLI |
| yt-dlp-direct | A pragmatic command-reference skill for the installed yt-dlp CLI — single videos, playlists, audio extraction, subtitles, cookies-from-browser. No reinvention, just operational knowledge. | yt-dlp |
I write long-form articles on my own publication and cross-post to several Chinese platforms. After a year of doing it with Claude Code, I had accumulated maybe 30 ad-hoc prompts and shell helpers. These 5 skills are the parts that survived the consolidation — the ones I actually use every week.
Two design principles run through all of them:
yt-dlp, nlm, wechatsync, codex), the skill wraps operational knowledge around it rather than reinventing in pure prompt.If you want the writing workflow as a whole (idea → outline → draft → style alignment), it's deeply coupled to my personal vault and not part of this release. These 5 are the parts I could cleanly extract.
You: 帮我收集 "Claude Code skills" 这个话题的素材,输出到 ./research/claude-skills
Claude: [invokes research-collector] → creates notebook, adds ~15 YouTube + ~40 web sources,
runs 3 analysis queries, saves summary markdown
You: 把 path/to/article.md 发到知乎和掘金(先 dry-run)
Claude: [invokes publisher-wechatsync] → checks auth, normalizes image paths,
runs dry-run, asks confirmation, then syncs
You: 给 path/to/article.md 跑一遍评分
Claude: [invokes article-optimizer] → returns 9-dimension score JSON
You: 评分器对 "title_score" 给得太松,帮我校准
Claude: [invokes score-optimizer] → re-runs prompt on labeled samples, compares
You: 把这个 YouTube 播放列表的音频下下来
Claude: [invokes yt-dlp-direct] → constructs the exact yt-dlp invocation, runs it
Most skills work with zero config. A few env vars are useful:
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