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douyin-video-analysis抖音视频分析

Agent Skill

用于辅助视频生成、动画合成、脚本化剪辑或 Remotion 等视频项目开发。它适合让 Agent 组织镜头、生成素材说明、维护合成代码或排查渲染问题。使用时需要确认分辨率、时长、素材路径和导出格式;涉及外部素材、人物肖像或商业发布时,应先核对版权授权和内容审核要求。

总安装

25,684

周安装

1,039

GitHub Stars

1

下载量

8,063
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:douyin-video-analysis(抖音视频分析)
来源仓库:https://github.com/zzmbobby/douyin-video-analysis
安装命令:
openclaw skills install douyin-video-analysis
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install douyin-video-analysis

简介

从抖音分享链接提取视频元数据进行分析。

  • 支持获取标题、作者、时长与互动指标等信息。
  • 适用于内容调研与竞品对标分析。douyin-video-analysis 属于效率类 Skill,可作为该场景下的辅助能力补充。
  • 安装命令:openclaw skills install douyin-video-analysis,需验证链接有效性。
  • 部分私有视频可能无法获取完整数据。

SKILL.md

name
douyin-video-analysis
description
抖音视频分析流水线:输入抖音链接后,自动/半自动抓取页面信息与音频、转写口播、总结内容、提取有用信息与对应证据、进行批判性思维分析,并把转写与分析结果写入 Obsidian。 / Analyze a Douyin video from a shared URL by extracting page metadata, capturing audio when possible, transcribing speech into readable text, summarizing content, extracting useful information plus evidence, applying critical analysis, and saving both transcript and analysis into Obsidian.

Douyin Video Analysis

Use this skill when the user gives a Douyin video URL and wants:

  • the real video topic/content extracted
  • the title and hook analyzed
  • audio downloaded from the page if possible
  • audio transcribed into readable Chinese text
  • critical thinking analysis of the script/content
  • results saved into Obsidian notes

Scope

This skill is for analysis and note capture, not reposting or bulk scraping.

Inputs

Expected user input:

  • a Douyin short URL or full video URL
  • optional analysis focus, such as:

- whether the copy is AI-generated - title strategy - persuasion methods - logical flaws / manipulation / exaggeration

Output contract

Produce:

  1. short status update in chat
  2. transcript note in Obsidian
  3. analysis note in Obsidian
  4. final chat summary with note paths

Workflow

1. Resolve the real video page

  • Open the Douyin URL in Chrome if needed.
  • Extract:

- canonical video URL - title - description - account name - visible chapter points / page text

  • Be explicit about what came from page metadata vs full transcript.

2. Extract media URLs if possible

  • Prefer reading browser performance resources from the actual loaded page.
  • Capture candidate audio/video stream URLs.
  • If direct download gets 403, retry with browser-derived headers/cookies when available.
  • Save temporary files under /tmp/douyin_transcribe/.

3. Transcribe audio

  • Prefer a local/offline path.
  • Current practical path on this machine:

- Python venv in /tmp/douyin_transcribe/venv - mlx-whisper

  • First pass:

- use a smaller model to get a usable draft quickly

  • If needed:

- do a second pass or manual cleanup for readability

  • Clearly label transcript status:

- raw machine transcript - cleaned readable version - final polished version

4. Summarize before criticizing

Before any critical-thinking judgment, always do these two steps:

A. Content summary

  • produce a concise summary of what the video actually says
  • separate hook / core claim / support / conclusion
  • avoid mixing your judgment into the summary

B. Useful information + evidence extraction

List the video's actually useful information and pair each item with the evidence the video itself provides. For each item, give an initial confidence judgment:

  • high
  • medium
  • low

This prevents the analysis from becoming pure attitude.

5. Analyze critically

Always cover, unless the user narrows scope:

  • what the video is actually saying
  • whether the title/hook exaggerates or distorts the case
  • whether the script appears AI-generated / AI-assisted / human-written
  • emotional triggers used
  • hidden assumptions
  • survivorship bias / overgeneralization / false lessons
  • what is genuinely useful vs what is manipulative or shallow

6. Save into Obsidian

Default destination:

  • transcript note → OpenClaw/Inbox/YYYY-MM-DD 抖音视频口播转写 - <topic>.md
  • analysis note → OpenClaw/Inbox/YYYY-MM-DD 抖音视频分析 - <topic>.md

Include:

  • source URL
  • canonical URL
  • account name if available
  • what was directly obtained vs inferred
  • transcript quality warning if imperfect

Response rules

  • Never pretend a full transcript was obtained if only page metadata was captured.
  • If only metadata is available, say so plainly.
  • Distinguish between:

- page title/description analysis - full script analysis

  • Prefer usefulness over theatrical certainty.

Local implementation notes

Useful browser path

  • Probe browser bridge
  • Use macOS Chrome bridge to:

- open the page - evaluate page JS - inspect visible text - inspect performance.getEntriesByType("resource")

Useful temporary files

  • /tmp/douyin_transcribe/audio*.mp4
  • /tmp/douyin_transcribe/venv

Suggested helper scripts

A. Grab page and audio

python3 /Users/bobzhong/.openclaw/workspace/skills/douyin-video-analysis/helpers/douyin_grab.py '<douyin-url>'

It will:

  • open the Douyin page in Chrome
  • fetch page metadata from the loaded Chrome tab
  • extract candidate media URLs
  • attempt authenticated audio download via curl with copied headers/cookies
  • return JSON containing canonical URL, title, body preview, audio URL, and local audio path

B. Transcribe and create notes

python3 /Users/bobzhong/.openclaw/workspace/skills/douyin-video-analysis/helpers/transcribe_and_note.py \
  --audio-file /tmp/douyin_transcribe/audio_latest.mp4 \
  --title '<video-title>' \
  --source-url '<shared-url>' \
  --page-url '<canonical-url>' \
  --account '<creator>' \
  --topic '<short-topic>'

It will:

  • transcribe the local audio with mlx-whisper
  • create a transcript note in Obsidian
  • create an analysis-note skeleton in Obsidian
  • return both note paths as JSON

Limits

  • Some videos may block direct media download.
  • Machine transcripts may contain proper noun and number errors.
  • Large-model transcription may be slow; start fast, then refine if needed.

When done

Tell the user:

  • whether transcript is metadata-only / rough transcript / cleaned transcript
  • where the notes were saved
  • whether further cleanup would materially improve the analysis

适合场景

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02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

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能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

87.03%
按下载量换算7,017

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

通过

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

安装前确认

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来源信息

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