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YouTube Video Topic Research

YouTube视频主题研究

Overview

概述

This skill conducts pure research for YouTube video topics. Execute all steps to produce actionable insights that identify content gaps and analyze competitors. This skill focuses ONLY on research - it does not generate titles, thumbnails, or hooks.

Core Principle: Focus on insights and big levers, not data dumping. Research should be comprehensive yet concise, backed by data, and designed to inform strategic decisions.

本技能专为YouTube视频主题开展纯研究工作。执行所有步骤以产出可落地的洞察，识别内容缺口并分析竞品。请注意：本技能仅聚焦研究环节——不生成标题、缩略图或钩子内容。

核心原则：聚焦洞察与关键影响因素，而非数据堆砌。研究需全面且简洁，以数据为支撑，旨在为战略决策提供依据。

When to Use

使用场景

Use this skill when:

You need to research a video topic before planning production
The user asks to research a video idea or topic
You want to understand the competitive landscape
You need to identify content gaps and opportunities

在以下场景中使用本技能：

视频制作规划前需要研究主题时
用户要求研究某个视频创意或主题时
你需要了解竞争格局时
你需要识别内容缺口与机遇时

Youtube Researcher Subagents

YouTube研究员子代理（Youtube Researcher Subagents）

You have access to youtube research subagents that can be used to conduct specific, focused research tasks. Youtube Researchers have access to all of the youtube analytics tools.

你可以调用YouTube研究员子代理来执行特定、聚焦的研究任务。这些子代理可访问所有YouTube分析工具。

Subagent Usage

子代理使用方式

Youtube Researchers can be invoked using the

Task

tool. You can call the

Task

tool multiple times in a single response to assign research tasks in parallel. This greatly improves performance. All research findings will be reported back to you for synthesis.

Bias towards using the

Task

tool to invoke the subagents rather than calling youtube analytics tools directly. Each

Task

prompt should be focused and specific, with a clear objective.

可通过

Task

工具调用YouTube研究员子代理。你可在单次响应中多次调用

Task

工具，并行分配研究任务，大幅提升效率。所有研究结果会反馈给你进行整合。

优先使用

Task

工具调用子代理，而非直接调用YouTube分析工具。每个

Task

指令需聚焦明确，目标清晰。

Research Workflow

研究工作流

Execute all steps below to complete the research.

执行以下所有步骤以完成研究。

Step 0: Create Research.md

步骤0：创建Research.md文件

Create a new research file for the video idea under

./youtube/episode/[episode]/

. If the user is organizing their videos into a series, include the episode number in the folder name. The folder name should be

[episode_number]_[topic_short_name]

, or

[topic_short_name]

if not part of a series. So the full research file path should be

./youtube/episode/[episode_number]_[topic_short_name]/research.md

All research MUST be written to this file.

If the file already exists, read it to understand what research has been done so far and continue from there.

在

./youtube/episode/[episode]/

路径下为视频创意新建研究文件。若用户将视频组织为系列，需在文件夹名称中包含集数。文件夹名称格式应为

[集数]_[主题简称]

，若不属于系列则为

[主题简称]

。因此，研究文件的完整路径应为

./youtube/episode/[集数]_[主题简称]/research.md

。

所有研究内容必须写入此文件。

若文件已存在，需先读取以了解已完成的研究内容，再继续后续工作。

Step 1: Understand the Topic

步骤1：理解主题

Analyze and document:

What problem does this video solve?
Why would someone click on this video?
What makes this topic relevant now?

分析并记录：

本视频解决什么问题？
用户为何会点击本视频？
该主题当下的相关性体现在哪里？

Step 2: Research User's Related Videos

步骤2：研究用户的相关视频

Execute these actions:

Use

mcp__plugin_yt-content-strategist_youtube-analytics__search_videos

to find related videos from user's channel

Use

mcp__plugin_yt-content-strategist_youtube-analytics__get_video_details

for performance metrics

Identify what's already been covered and how to differentiate

Document in research file:

Related videos (title, video ID, URL, key metrics)
Performance insights (what worked, what didn't)
Differentiation strategy for new video

执行以下操作：

使用

mcp__plugin_yt-content-strategist_youtube-analytics__search_videos

工具查找用户频道中的相关视频

使用

mcp__plugin_yt-content-strategist_youtube-analytics__get_video_details

工具获取表现数据

识别已覆盖的内容及差异化方向

在研究文件中记录：

相关视频（标题、视频ID、链接、关键数据）
表现洞察（哪些内容有效，哪些无效）
新视频的差异化策略

Step 3: Competitor Research

步骤3：竞品研究

Execute these actions:

Use

mcp__plugin_yt-content-strategist_youtube-analytics__search_videos

to find 5-8 top videos on the topic

Filter for recent videos with high engagement

Use

mcp__plugin_yt-content-strategist_youtube-analytics__get_video_details

for each top video

Analyze patterns in successful videos

Document for each competitor:

Title, channel, video ID, URL
Subscriber count, views, engagement
Focus/angle and what makes it successful

Synthesize key insights: Identify common patterns and different approaches across competitors.

执行以下操作：

使用

mcp__plugin_yt-content-strategist_youtube-analytics__search_videos

工具查找该主题下的5-8个热门视频

筛选近期发布且互动量高的视频

使用

mcp__plugin_yt-content-strategist_youtube-analytics__get_video_details

工具获取每个热门视频的详细信息

分析成功视频的规律

为每个竞品记录：

标题、频道、视频ID、链接
订阅数、播放量、互动数据
核心主题/角度及其成功原因

整合关键洞察：识别竞品间的共性规律与差异化做法。

Step 4: Content Gap Analysis

步骤4：内容缺口分析

Analyze and identify:

What topics are saturated?
What's missing or underexplored?
Where can the user add unique value?

Document in research file:

What's Already Well-Covered: 3-5 saturated topics/approaches
Content Gaps (Opportunities): Specific opportunities rated ⭐⭐⭐ (high), ⭐⭐ (medium), ⭐ (low)
Recommended Focus: The specific angle and unique value proposition

Rating Criteria:

⭐⭐⭐ High: Significant gap, strong demand, clear differentiation
⭐⭐ Medium: Moderate gap, some competition, good potential
⭐ Low: Minor gap, heavily competed

分析并识别：

哪些主题已饱和？
哪些内容缺失或未被充分挖掘？
用户可在哪些方面提供独特价值？

在研究文件中记录：

已充分覆盖的内容：3-5个饱和主题/方向
内容缺口（机遇）：具体机遇，按⭐⭐⭐（高）、⭐⭐（中）、⭐（低）评级
推荐聚焦方向：具体切入角度与独特价值主张

评级标准：

⭐⭐⭐ 高：缺口显著，需求旺盛，差异化清晰
⭐⭐ 中：缺口中等，存在一定竞争，潜力良好
⭐ 低：缺口微小，竞争激烈

Output Structure

输出结构

Save all research to:

./youtube/episode/[episode_number]_[topic_short_name]/research.md

Use this template structure:

markdown

undefined

将所有研究内容保存至：

./youtube/episode/[集数]_[主题简称]/research.md

使用以下模板结构：

markdown

undefined

[Episode_Number]: [Topic] - Research

[集数]：[主题] - 研究

Episode Overview

集数概述

Topic: [Brief description] Target Audience: [Who this is for] Goal: [What viewers will learn/gain]

主题：[简要描述] 目标受众：[面向人群] 目标：[观众将学到/获得的内容]

Research Notes

研究笔记

Key Concepts to Cover

需覆盖的核心概念

[High-level list]

[高阶列表]

YouTube Research

YouTube研究

Content Gap Analysis

内容缺口分析

What's Already Well-Covered: [List]

已充分覆盖的内容：[列表]

Content Gaps (Opportunities): [Rated list]

内容缺口（机遇）：[带评级的列表]

Recommended Focus: [Specific angle and value prop]

推荐聚焦方向：[具体角度与价值主张]

Technical Implementation

技术实现

[Only if applicable]

[仅在适用时填写]

Production Notes

制作笔记

Episode Number: [Number] Status: Research Complete Created/Updated: [Dates]

集数：[编号] 状态：研究完成 创建/更新日期：[日期]

Execution Guidelines

执行指南

Focus on Insights, Not Data

聚焦洞察，而非数据

Execute research with these principles:

Synthesize patterns from research
Identify 3-5 key insights with supporting data
Explain WHY approaches work
Limit competitor research to 5-8 videos

执行研究时遵循以下原则：

整合研究中的规律
结合支撑数据，识别3-5个关键洞察
解释不同做法有效的原因
将竞品研究限制在5-8个视频内

Prioritize Big Levers

优先关注关键影响因素

Focus research on these impact areas in order:

Content Gaps (Unique value)
Competitor Patterns
Audience Needs
Technical Requirements

按以下优先级聚焦研究的核心影响领域：

内容缺口（独特价值）
竞品规律
受众需求
技术要求

Back Recommendations with Data

以数据支撑建议

When documenting findings:

❌ "Make a video about AI agents"
✅ "Focus on AI agent memory systems (⭐⭐⭐ gap) - competitors get 50K+ views but don't cover persistent memory"

记录研究发现时：

❌ "制作关于AI Agent的视频"
✅ "Focus on AI agent memory systems (⭐⭐⭐ gap) - competitors get 50K+ views but don't cover persistent memory"

Maintain Episode Continuity

保持系列连贯性

During research:

Reference previous episode research
Check for topic overlap
Identify opportunities to build on previous content

研究过程中：

参考过往集数的研究内容
检查主题重叠情况
识别可基于过往内容拓展的机遇

Quality Checklist

质量检查清单

Tools to Use

可用工具

Execute research using these tools:

YouTube Analytics MCP:

mcp__plugin_yt-content-strategist_youtube-analytics__search_videos

- Find videos by query

mcp__plugin_yt-content-strategist_youtube-analytics__get_video_details

- Get video metrics

mcp__plugin_yt-content-strategist_youtube-analytics__get_channel_details

- Get channel info

Web Research: Use

web-search

and

web-fetch

for industry trends and context

Filesystem: Use

view

for channel context and previous research

执行研究时使用以下工具：

YouTube Analytics MCP:

mcp__plugin_yt-content-strategist_youtube-analytics__search_videos

- 通过关键词查找视频

mcp__plugin_yt-content-strategist_youtube-analytics__get_video_details

- 获取视频数据

mcp__plugin_yt-content-strategist_youtube-analytics__get_channel_details

- 获取频道信息

网页研究：使用

web-search

和

web-fetch

工具了解行业趋势与背景信息

文件系统：使用

view

工具查看频道背景与过往研究内容

Common Pitfalls to Avoid

需避免的常见误区

Data Dumping: Listing every video found without synthesis → Limit to 5-8 top videos, focus on patterns
Vague Content Gaps: "Not much content on this topic" → Identify specific angles missing
Over-Researching Technical Details: Deep implementation research → Keep high-level, focus on what to cover
Long Reports: 800+ line documents → Focus on insights and big levers

数据堆砌：列出所有找到的视频而不进行整合 → 限制为5-8个热门视频，聚焦规律总结
模糊的内容缺口："该主题内容不多" → 需识别具体缺失的切入角度
过度研究技术细节：深入研究实现细节 → 保持高阶视角，聚焦需覆盖的内容
过长的报告：超过800行的文档 → 聚焦洞察与关键影响因素

Example Execution

执行示例

Scenario: User requests research for video about "Building AI agents with memory"

Execute workflow:

Load channel context → Read CLAUDE.md, get channel details (1,500 subs, tech tutorial niche)
Find related videos → Search user's channel, find Episode 15 on personal assistants, viewers asked about memory
Competitor research → Search and analyze 8 top videos, identify they cover theory not implementation
Gap analysis → Document ⭐⭐⭐ opportunity for practical memory implementation

Save research → Write to

./youtube/18_ai_agents_with_memory/research.md

Result: Comprehensive research document ready for review or to proceed to the planning phase.

Next Step: If the user has asked to plan the video, invoke the

youtube-plan-new-video

skill to generate title, thumbnail, and hook concepts based on this research.

场景：用户要求研究"Building AI agents with memory"主题的视频

执行工作流：

加载频道背景 → 读取CLAUDE.md，获取频道详情（1,500 subs，技术教程领域）
查找相关视频 → 搜索用户频道，找到Episode 15 on personal assistants，观众询问了记忆相关内容
竞品研究 → 搜索并分析8个热门视频，发现它们仅覆盖理论未涉及实现
缺口分析 → 记录"实用记忆系统实现"为⭐⭐⭐级机遇

保存研究 → 写入

./youtube/18_ai_agents_with_memory/research.md

结果：产出全面的研究文档，可供审核或进入规划阶段。

下一步：若用户要求规划视频，调用

youtube-plan-new-video

技能，基于此研究生成标题、缩略图和钩子创意。