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video-content-strategist视频内容策略师

Agent Skill

用于辅助文档、README、Markdown、说明文和内容稿件的整理与改写。它适合让 Agent 提炼结构、补齐章节、统一术语、检查链接或把零散材料整理成可读文档。使用时应保留项目已有事实、命令和路径,不要把未确认的信息写成确定结论;涉及对外文案时,还需要控制语气,避免过度营销或夸大能力。

总安装

689

周安装

29

GitHub Stars

103

下载量

241
CodexClaudeCursorGemini CLI

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

unknown

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:video-content-strategist(视频内容策略师)
来源仓库:https://github.com/borghei/claude-skills
仓库路径:skills/video-content-strategist
安装命令:
npx skills add https://github.com/borghei/claude-skills --skill video-content-strategist
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 npx skills 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。

skills.shnpx skills
npx skills add https://github.com/borghei/claude-skills --skill video-content-strategist

简介

用于辅助文档、README、Markdown、说明文和内容稿件的整理与改写。

  • 适合让 Agent 提炼结构、补齐章节、统一术语、检查链接或整理成可读文档。
  • 使用时应保留项目已有事实、命令和路径,不把未确认信息写成确定结论。
  • 涉及对外文案时,还需控制语气,避免过度营销或夸大能力。
  • video-content-strategist 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Video Content Strategist Skill

Overview

Production-ready video content strategy toolkit for planning content calendars, analyzing thumbnail effectiveness, and optimizing video metadata for platform SEO. Designed for content creators, marketing teams, and video producers managing consistent video output across YouTube, TikTok, LinkedIn, and other platforms.

Quick Start

# Plan a video content calendar from topics and audience data
python scripts/video_content_planner.py topics.json --weeks 8 --frequency 3

# Analyze thumbnail text and composition patterns
python scripts/thumbnail_analyzer.py thumbnails.csv

# Optimize video titles, descriptions, and tags for SEO
python scripts/video_seo_optimizer.py video_data.json --platform youtube

Tools Overview

ToolPurposeInputOutput
video_content_planner.pyContent calendar generationJSON with topics/audienceWeekly calendar + production schedule
thumbnail_analyzer.pyThumbnail pattern analysisCSV with thumbnail dataOptimization recommendations
video_seo_optimizer.pyVideo metadata SEOJSON with video detailsOptimized titles, descriptions, tags

Workflows

Workflow 1: Monthly Video Strategy

  1. Define audience personas and content pillars in topics JSON
  2. Run video_content_planner.py to generate 4-week calendar
  3. For each planned video, run video_seo_optimizer.py for metadata
  4. After publishing, collect thumbnail data and run thumbnail_analyzer.py
  5. Feed learnings back into next month's planning cycle

Workflow 2: YouTube Channel Optimization

  1. Export existing video data (titles, descriptions, tags, performance)
  2. Run video_seo_optimizer.py on underperforming videos to identify metadata gaps
  3. Run thumbnail_analyzer.py on top vs bottom performers
  4. Apply optimizations to existing videos and use patterns for new content

Workflow 3: Multi-Platform Video Strategy

  1. Create topics JSON with platform-specific audience data
  2. Run video_content_planner.py with --platforms youtube,tiktok,linkedin
  3. Get platform-adapted content recommendations
  4. Optimize each platform's metadata with video_seo_optimizer.py

Reference Documentation

See references/video-strategy-guide.md for comprehensive frameworks covering:

  • Content pillar strategy
  • Platform-specific best practices
  • Thumbnail design principles
  • Video SEO fundamentals
  • Production workflow optimization

Common Patterns

Pattern: Topics JSON Format

{
  "channel": "TechStartupTV",
  "audience": {
    "primary": "SaaS founders, 25-45",
    "interests": ["startup growth", "fundraising", "product development"],
    "pain_points": ["scaling teams", "finding product-market fit", "managing burn rate"]
  },
  "content_pillars": [
    {"name": "Founder Stories", "ratio": 0.3, "format": "interview", "avg_length_min": 25},
    {"name": "Tactical Guides", "ratio": 0.4, "format": "tutorial", "avg_length_min": 12},
    {"name": "Industry Analysis", "ratio": 0.2, "format": "commentary", "avg_length_min": 8},
    {"name": "Behind the Scenes", "ratio": 0.1, "format": "vlog", "avg_length_min": 5}
  ],
  "topics": [
    {"title": "How We Hit $1M ARR", "pillar": "Founder Stories", "priority": "high"},
    {"title": "5 Pricing Strategies That Work", "pillar": "Tactical Guides", "priority": "high"},
    {"title": "AI in SaaS: 2026 Trends", "pillar": "Industry Analysis", "priority": "medium"}
  ]
}

Pattern: Thumbnail CSV Format

video_id,title,views,ctr_pct,has_face,has_text,text_words,colors_dominant,emotion
V001,How to Scale,15000,8.2,yes,yes,3,red-yellow,surprise
V002,Tech Review,8500,4.1,no,yes,5,blue-white,neutral

Platform Video Length Guidelines

PlatformOptimal LengthMax Recommended
YouTube (standard)8-15 min25 min
YouTube Shorts30-60 sec60 sec
TikTok30-90 sec3 min
LinkedIn1-3 min10 min
Instagram Reels15-60 sec90 sec

适合场景

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用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

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需要对比不同来源的安装命令和来源信息时

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

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

Codex

37.2%
按下载量换算90

Claude

32.12%
按下载量换算77

Cursor

18.44%
按下载量换算44

Gemini CLI

8.73%
按下载量换算21

安全审计

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权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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