| name | yt-research |
| description | Research competitor YouTube channels, niches, and trending topics for your content strategy.
Use this skill whenever the user says "research channels", "analyze competitors", "find trending topics",
"niche analysis", "competitive research", "what are other creators doing", "scrape YouTube channels",
or wants to understand the competitive landscape for a specific tool or topic area. Use when working with yt research. Trigger with 'yt', 'research'.
|
| allowed-tools | WebSearch, Read, Write, Task |
| version | 1.10.0 |
| author | Claude Code Plugins <plugins@claudecodeplugins.io> |
| license | MIT |
| tags | ["productivity","yt-research"] |
| compatibility | Designed for Claude Code, also compatible with Codex and OpenClaw |
YouTube Research
You are conducting competitive research for a YouTube channel. Your goal is to analyze competitor channels, identify content gaps, discover trending topics, and surface opportunities aligned with the creator's strategy.
Before You Start
You need from the user:
- Research focus - What niche, tool, or topic area to research (e.g., "AI tools for professionals", "MCP integrations", "productivity software")
- Competitor channels (optional) - Specific YouTube channel URLs to analyze
- Specific angle (optional) - Is there a particular feature, update, or trend they want to investigate?
If the user provided context already, confirm your understanding and proceed.
The Research Process
Step 1: Scope the Research
Define the research boundaries:
- Which channels to scrape (user-provided + discovered competitors)
- Which topics/keywords to search for
- Time horizon (recent 30 days, 90 days, or all-time)
Tell the user the plan: "I'll analyze [N] channels and search for [keywords]. This will involve web research and data collection."
Step 2: Collect Channel Data
Use web research to collect:
- Channel metadata (subscribers, total videos, posting frequency)
- Recent videos (last 30-50 per channel): titles, views, likes, comments, publish dates
- Video tags and categories where available
If Apify MCP is available, spawn yt-scraper sub-agent for bulk data collection.
Step 3: Analyze Channels
For each channel, analyze:
- Engagement pattern analysis (what gets views vs what doesn't)
- Content type distribution (tutorials, reviews, updates, opinions)
- Title pattern analysis (what structures and words correlate with views)
- Outlier video identification (3x+ above channel average)
- Topic coverage map (what's covered, what's missing)
If analyzing 4+ channels, spawn channel-analyzer sub-agents (3 channels per agent) for parallel processing.
Step 4: Identify Opportunities
Using the analysis results, identify:
Content Gaps:
- Topics the audience searches for but competitors cover poorly
- Topics that are developer-focused everywhere but could be made accessible
- Recent tool updates/features with no quality coverage yet
Trending Signals:
