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Youtube Research

  • 149 installs
  • 80 repo stars
  • Updated May 18, 2026
  • manojbajaj95/claude-gtm-plugin

Search YouTube for competitor videos, trends, and audience questions so Claude can inform positioning, content strategy, and launch messaging.

About

Research skill for Claude to investigate YouTube for niche trends, competitor explainers, viewer comments, and content gaps that shape GTM messaging, tutorial plans, and launch creative direction.

  • Competitor video scans
  • Trend scouting
  • Comment mining
  • Content gap analysis
  • Audience question extraction

Youtube Research by the numbers

  • 149 all-time installs (skills.sh)
  • +1 installs in the week ending Aug 2, 2026 (Skillselion tracking)
  • Ranked #1,050 of 1,879 Marketing & SEO skills by installs in the Skillselion catalog
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/manojbajaj95/claude-gtm-plugin --skill youtube-research

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Listed on Skillselion
Installs149
repo stars80
Last updatedMay 18, 2026
Repositorymanojbajaj95/claude-gtm-plugin

What it does

Search YouTube for competitor videos, trends, and audience questions so Claude can inform positioning, content strategy, and launch messaging.

Files

SKILL.mdMarkdownGitHub ↗

YouTube Research

Workspace Context

Read bootstrap context before asking questions: strategy/brand.md for brand, audience, offer, channels, tools, constraints, and metrics; about/me.md for personal voice; content/ideas.md and content/calendar.md for content planning. Use legacy product-marketing context files only as fallback. Save generated drafts to content/<platform>/drafts/YYYY-MM-DD_short-topic-slug.md, and route durable learnings back to strategy/brand.md, about/me.md, or content/ideas.md.

Operating Contract

This skill is self-contained for its frontmatter scope: use its local instructions, references, scripts, and assets as the playbook; ask only for missing task-specific inputs; hand off to adjacent skills instead of expanding scope; and return an actionable artifact, decision, plan, draft, or diagnostic.

Three modes in one skill:

1. Topic Research — competitive landscape, content gaps, strategic insights before planning a video 2. Video Analysis — forensic deconstruction of transcripts to extract viral formulas and retention mechanics 3. API Queries — direct YouTube Data API v3 access for search, stats, comments, and channel info

---

When to Use

  • Researching a video topic before planning production
  • Analyzing a competitor video to extract what makes it work
  • Fetching channel stats, video metrics, or comments via the API
  • Identifying content gaps and opportunities in a niche

---

YouTube Data API Setup

1. Get an API Key

1. Go to Google Cloud Console → APIs & Services → Library 2. Enable YouTube Data API v3 3. Create Credentials → API Key

export YOUTUBE_API_KEY="your-api-key-here"
Important: When piping curl output, wrap the command in bash -c '...' to preserve env vars:
```bash
bash -c 'curl -s "https://..." -H "..." | jq .'
```

2. Key API Commands

Search Videos:

bash -c 'curl -s "https://www.googleapis.com/youtube/v3/search?part=snippet&q=YOUR_QUERY&type=video&maxResults=10&order=viewCount&key=${YOUTUBE_API_KEY}"' | jq '.items[] | {videoId: .id.videoId, title: .snippet.title, channel: .snippet.channelTitle}'

Get Video Details (stats, duration):

bash -c 'curl -s "https://www.googleapis.com/youtube/v3/videos?part=snippet,statistics,contentDetails&id=VIDEO_ID&key=${YOUTUBE_API_KEY}"' | jq '.items[0] | {title: .snippet.title, views: .statistics.viewCount, likes: .statistics.likeCount, duration: .contentDetails.duration}'

Get Channel by Handle:

bash -c 'curl -s "https://www.googleapis.com/youtube/v3/channels?part=snippet,statistics&forHandle=@HANDLE&key=${YOUTUBE_API_KEY}"' | jq '.items[0] | {id: .id, title: .snippet.title, subscribers: .statistics.subscriberCount, videos: .statistics.videoCount}'

Get Video Comments:

bash -c 'curl -s "https://www.googleapis.com/youtube/v3/commentThreads?part=snippet&videoId=VIDEO_ID&maxResults=20&order=relevance&key=${YOUTUBE_API_KEY}"' | jq '.items[] | {author: .snippet.topLevelComment.snippet.authorDisplayName, text: .snippet.topLevelComment.snippet.textDisplay, likes: .snippet.topLevelComment.snippet.likeCount}'

Get Trending Videos:

bash -c 'curl -s "https://www.googleapis.com/youtube/v3/videos?part=snippet,statistics&chart=mostPopular&regionCode=US&maxResults=10&key=${YOUTUBE_API_KEY}"' | jq '.items[] | {title: .snippet.title, channel: .snippet.channelTitle, views: .statistics.viewCount}'

Quota: 10,000 units/day. Search = 100 units. Most others = 1 unit.

See YouTube Data API docs for full reference.

---

Mode 1: Topic Research

Conduct research before planning a new video. Focus on insights and big levers — not data dumping.

Workflow

Step 0: Create research file

Save all research to: ./youtube/episode/[episode_number]_[topic_short_name]/research.md

If it already exists, read it and continue from where it left off.

Step 1: Understand the topic

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

Step 2: Research your own channel

Use the API to find related videos you've already published. Document:

  • Related videos (title, video ID, URL, key metrics)
  • What's already been covered and how to differentiate

Step 3: Competitor research

Search for 5–8 top videos on the topic. For each:

  • Get video details (views, likes, duration)
  • Note the title, angle, and what makes it successful
  • Synthesize common patterns and approaches

Step 4: Content gap analysis

Document:

  • What's saturated — 3–5 over-covered angles
  • Gaps (Opportunities) — rated ⭐⭐⭐ high / ⭐⭐ medium / ⭐ low
  • Recommended focus — specific angle + unique value proposition

Rating criteria:

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

Research File Template

# [Episode]: [Topic] - Research

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

## YouTube Research
### Your Previous Videos
[Related videos with metrics]

### Top Competing Videos
[5-8 videos: title, channel, views, angle, what works]

### Key Insights
[Patterns and findings synthesized]

## Content Gap Analysis
### What's Already Well-Covered
[List]

### Content Gaps (Opportunities)
[Rated list with ⭐ ratings]

### Recommended Focus
[Specific angle and unique value proposition]

## Production Notes
**Status**: Research Complete
**Created**: [Date]

Parallel Research

If the host environment supports parallel research, split focused tasks such as competitor search, own-channel review, and comment mining. Otherwise, do them sequentially and synthesize findings after each section.

Pitfalls

  • Data dumping — Limit to 5–8 competitors, synthesize patterns instead of listing every video
  • Vague gaps — "Not much content on this" → identify the specific missing angle
  • Long reports — Focus on insights and big levers

Next step: Use youtube-content skill to plan the video based on this research.

---

Mode 2: Video Analysis

Forensic deconstruction of video transcripts to extract viral formulas, hooks, and retention mechanics.

Getting the Transcript

Auto-fetch:

python skills/youtube-research/scripts/fetch_transcript.py "YOUTUBE_URL_OR_VIDEO_ID"

Manual paste: YouTube's built-in transcript (click "..." → "Show transcript") or ytscribe.ai.

Analysis Framework

Approach the transcript like a crime scene — extract everything systematically. See reference/analysis-framework.md for the full checklist and templates.

Analyze these 11 dimensions:

1. Hook Architecture — Primary hook (first 3–8s), hook type, secondary hooks, fill-in-blank templates 2. Structural Blueprint — Content framework (PAS, Story-Lesson-CTA, List-Depth-Summary), beat map, pacing 3. Retention Mechanics — Open loops, pattern interrupts, curiosity gaps, payoff points 4. Emotional Engineering — Emotional arc, trigger words, identity hooks, Us vs. Them dynamics 5. Storytelling Elements — Narrative framework, character positioning, conflict/stakes, specificity 6. Linguistic Patterns — Power phrases, sentence rhythm, repetition, conversational triggers 7. Algorithm Signals — Watch time optimizers, engagement bait, share/save triggers 8. CTA Architecture — Primary CTA, soft CTAs, timing, value exchange 9. Viral Coefficient — Shareability score (1–10), comment bait density, crossover potential 10. Reusable Templates — Fill-in-blank opening hooks (3 variations), section templates, transition library 11. Implementation Playbook — Top 10 steal-this elements, niche adaptation, A/B test suggestions

Before Analysis, Collect Context

  • Your niche/topic
  • Your content style (casual, educational, hype, etc.)
  • Target platform and video length goal

Output Format

Structure output with all 11 sections. End with a Quick Reference Cheatsheet — one-page summary of all extracted patterns for rapid implementation.

---

Tools

  • YouTube API: bash -c 'curl ...' with $YOUTUBE_API_KEY
  • MCP (if available): mcp__plugin_yt-content-strategist_youtube-analytics__search_videos, get_video_details, get_channel_details
  • Web: WebSearch and WebFetch for industry trends and context

Related skills

Marketing & SEOcontentdistribution

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