hook-lab
Skill88 starsChanged 5 months agoMITView on GitHub
Use when the user gives a TikTok/Instagram Reels/YouTube Shorts URL (or runs /analyze <url>) and wants to know why the video works — extracts metadata and transcript, then breaks down hook, script structure, style tags, viral factors, and rewrite angles for Chinese platforms.
2 other projects use a version of this.
Adopted by
Most recently taken up by
- metaflora-app/metaflora-content-machinetheir own version, first seen Jul 14, 2026
- lumizone/social-content-os-claude-skilltheir own version, first seen Jun 30, 2026
Other versions2 projects use a version of this.
Word for word · 0
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Edited · 0
None found.
Wrote their own version · 2
- lumizone/social-content-os-claude-skill★ 0same name
- metaflora-app/metaflora-content-machine★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
The file
Files
/analyze — 短视频内容拆解
Input
$ARGUMENTS = 一个视频 URL(TikTok / Instagram Reels / YouTube Shorts)。
如果用户没有提供 URL,问他要。
Step 1: Extract
运行提取脚本:
python3 ~/.claude/skills/hook-lab/scripts/analyze-video.py "$ARGUMENTS"脚本返回 JSON,包含:
platform: tiktok / instagram / youtubemetadata: 标题、描述、作者、播放量、点赞、评论、时长等transcript: 视频字幕/转写文本(可能为 null)
提取失败的回退策略
如果 metadata._error 存在,按以下顺序尝试回退:
回退 1 — WebFetch: 用 WebFetch 工具访问视频 URL,prompt 设为:
"Extract all video metadata: title, description, author name, author handle, view count, like count, comment count, share count, duration, and any transcript/caption text visible on the page."
回退 2 — 用户提供信息: 如果 WebFetch 也拿不到数据,请用户提供:
- 视频的文案/字幕文本(可以从视频里手动复制)
- 基本数据(播放量、点赞数等,截图也行)
拿到任何数据后继续分析,在输出开头注明数据来源和完整度。
Step 2: Analyze
基于提取到的数据,进行以下分析。用中文输出。
2.1 基础数据面板
用表格展示关键指标:平台、作者、时长、播放量、点赞、评论、转发。 计算互动率 = (like + comment) / view。
2.2 Hook 分析(前 3 秒)
从 transcript 的前 1-3 句提取 hook 文案,分析:
- Hook 类型: curiosity gap / shocking stat / bold claim / question / visual hook / pattern interrupt
- Hook 强度判断: 为什么能让人停下来
- 可优化空间: 如果 hook 不够强,给出改写建议
如果没有 transcript,从 description 和 title 推断 hook 策略。
2.3 脚本结构拆解
将 transcript 按叙事结构分段:
| 段落 | 时间估算 | 内容 | 作用 |
典型结构:Hook → Problem/Context → Solution/Reveal → Proof/Example → CTA
分析脚本节奏:信息密度是否合理、转折点在哪、哪里容易流失观众。
2.4 风格与格式标签
给视频打标签(多选):
- 呈现方式: talking head / voiceover / text-on-screen / skit / montage / screencast / interview
- 内容类型: educational / entertainment / storytelling / review / tutorial / hot-take / news
- 情绪基调: 紧迫 / 好奇 / 幽默 / 震惊 / 共鸣 / 权威
2.5 为什么这条视频能爆
综合分析 2-3 个核心原因。要具体,不要泛泛而谈。 比如不要说「因为内容好」,要说「开头用了具体数字制造反差($0 → $10K),3 秒内给出明确价值承诺」。
2.6 可借鉴的改写方向
给出 3 个具体的改写角度,每个包含:
- 角度: 一句话概述
- Hook 示例: 写出改写后的 hook 文案
- 适合平台: TikTok / Instagram / 小红书 / 视频号
改写方向要考虑中文创作者的场景。
Step 3: Output
按上面 2.1-2.6 的顺序输出完整分析。格式用 markdown 表格和分段标题,清晰可读。
最后附一行:
数据来源:yt-dlp 提取 | 分析模型:Claude
Step 4: 记录到结果库
分析完成后,往 ~/.claude/skills/hook-lab/results/analyzed-videos.md 追加一条记录(直接 Append,不要覆盖已有内容),格式:
## [YYYY-MM-DD] 作者 — 标题/主题 (平台)
- URL: <原始链接>
- 数据: 播放 X / 赞 X / 评论 X / 转发 X
- Hook 类型: ...
- 为什么能爆: 一句话核心结论
- 可借鉴方向: 一句话核心结论
---这个文件是跨视频对比的素材库——后续如果用户要"把分析过的几条放一起找规律",直接读这个文件,不用重新跑提取。
Notes
- 如果没有 transcript,在输出开头注明「未能提取字幕,以下分析基于元数据和描述文本」,分析照做但标注信息置信度较低
- 不要编造数据,metadata 里没有的指标标注「N/A」
- 互动率计算如果缺少 view_count 就跳过
- 全程用中文输出,技术术语保留英文(hook、CTA、talking head 等)
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