YouTube Intel

YouTube Intel

Local skill by Claw0x — runs entirely in your agent environment.

Runs locally. No external API calls, no API key required. Complete privacy. Your competitive intelligence stays on your machine.

YouTube content intelligence and competitive monitoring. Two modes: Monitoring (track specific channels) and Discovery (scan markets for content opportunities using a structured six-step workflow).

Quick Reference

5-Minute Quickstart

Step 1: Install (30 seconds)

openclaw skill add youtube-intel

Step 2: Monitor a Channel

const result = await agent.run('youtube-intel', {
  mode: 'monitoring',
  query: '@mkbhd'
});
// Returns: latest videos, view trends, content direction changes

Step 3: Discover Opportunities

const result = await agent.run('youtube-intel', {
  mode: 'discovery',
  query: 'AI tools'
});
// Returns: subcategory breakdown, competition levels, ranked opportunities

Step 4: Review the Report

The output includes:

• Competition assessment per subcategory (🔴 high / 🟡 medium / 🟢 low)
• Ranked content opportunities with evidence
• Viral pattern analysis with replicable lessons
• Channel profiles with aggregated metrics

Real-World Use Cases

Scenario 1: Entering a New Niche

Problem: You want to start a YouTube channel about AI tools but don't know which subcategory has the best opportunity.

Solution: Run Discovery mode with "AI tools" — the skill decomposes it into subcategories (AI image tools, AI coding tools, AI video tools, etc.), assesses competition for each, and ranks opportunities.

Example:

const report = await agent.run('youtube-intel', {
  mode: 'discovery',
  query: 'AI tools',
  options: { max_results: 30 }
});

// report.opportunities[0]:
// {
//   type: "timing",
//   sub_category: "AI avatar tools",
//   competition_level: "green",
//   suggested_angle: "Emerging market, supply is scarce",
//   suggested_titles: ["2026 Best AI Avatar Tools Compared"]
// }

Scenario 2: Tracking Competitors

Problem: You need to monitor what your top 3 competitors are publishing and how their content performs.

Solution: Run Monitoring mode for each channel — get latest uploads, view velocity, content type shifts, and trend analysis.

Example:

const report = await agent.run('youtube-intel', {
  mode: 'monitoring',
  query: '@competitor_channel'
});

// report.channel_profile:
// {
//   latest_video_days_ago: 3,
//   avg_views: 150000,
//   content_type_distribution: { tutorial: 40%, review: 35%, list: 25% }
// }

Scenario 3: Finding Viral Patterns

Problem: You want to understand what makes videos go viral in your niche.

Solution: Discovery mode identifies videos with 1M+ views, analyzes title formulas, timing context, and extracts replicable patterns.

Scenario 4: Content Calendar Planning

Problem: You need data-driven topic ideas for the next month.

Solution: Combine Discovery (find gaps) + Monitoring (track what competitors are NOT covering) to generate a prioritized topic list.

Two Modes

Monitoring Mode

Track specific YouTube channels over time.

Trigger phrases: "monitor this channel", "track @channel", "what did they publish recently"

Workflow:

1. Read channel history from memory (if exists)
2. Fetch latest channel data via browser
3. Compare with history: new videos, view changes, trend shifts
4. Update memory archive
5. Output change report

Discovery Mode (Six-Step Workflow)

Scan a market category for content opportunities. This is NOT a simple keyword search — it follows a structured intelligence workflow:

Step 1: Demand Analysis    → Understand what the user really wants, identify ambiguity
Step 2: Strategy Design    → Define search terms, subcategories, data sources
Step 3: Data Collection    → Execute searches via browser
Step 4: Data Cleaning      → Deduplicate, filter noise, normalize formats
Step 5: Analysis           → Assess competition, identify opportunities, extract viral patterns
Step 6: Save & Present     → Write to memory, output structured report

Data Models

Video Record

video:
  title: string
  video_id: string
  url: string
  channel_name: string
  channel_handle: string
  views: number
  published_days_ago: number
  duration: string
  is_short: boolean
  content_type: "review" | "tutorial" | "list" | "comparison" | "news" | "other"
  is_viral: boolean       # views > 1M
  is_emerging: boolean    # published < 30 days

Channel Profile

channel_profile:
  name: string
  handle: string
  videos_in_results: number
  avg_views: number
  max_views: number
  is_established: boolean  # 3+ videos, avg views > 200K
  is_emerging: boolean     # new account with viral hit

Competition Assessment

competition:
  sub_category: string
  total_videos: number
  unique_channels: number
  avg_views: number
  top_video_views: number
  competition_level: "red" | "yellow" | "green"
  # red: top video > 1M views AND 5+ established channels
  # yellow: top video 300K-1M OR 2-5 established channels
  # green: top video < 300K OR emerging market

Opportunity

opportunity:
  type: "differentiation" | "niche" | "format" | "timing" | "data"
  description: string
  evidence: string[]
  suggested_angle: string
  risk: string
  priority: number  # 1-5

Integration Recipes

OpenClaw Agent

import { Claw0xClient } from '@claw0x/sdk';

const claw0x = new Claw0xClient(process.env.CLAW0X_API_KEY);

// Discovery: find opportunities in a niche
const discovery = await claw0x.call('youtube-intel', {
  mode: 'discovery',
  query: 'productivity tools'
});

console.log('Top opportunity:', discovery.opportunities[0]);

// Monitoring: track a competitor
const monitoring = await claw0x.call('youtube-intel', {
  mode: 'monitoring',
  query: '@competitor'
});

console.log('Latest video:', monitoring.report.latest_video);

LangChain Agent

from claw0x import Claw0xClient

client = Claw0xClient(api_key="ck_live_...")

result = client.call("youtube-intel", {
    "mode": "discovery",
    "query": "AI video editing tools"
})

for opp in result["opportunities"]:
    print(f"[{opp['competition_level']}] {opp['sub_category']}: {opp['suggested_angle']}")

Custom Agent (Direct API)

const response = await fetch('https://api.claw0x.com/v1/call', {
  method: 'POST',
  headers: {
    'Authorization': 'Bearer ck_live_...',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    skill: 'youtube-intel',
    input: {
      mode: 'discovery',
      query: 'content creation tools'
    }
  })
});

const data = await response.json();

Error Handling

Important Notes

• Always analyze demand before searching — don't just search a keyword and output a report
• Broad categories MUST be decomposed into subcategories first
• Confidence levels are always marked (🟢 high / 🟡 medium / 🔴 low)
• Shorts and long-form videos are analyzed separately (different markets)
• Data is saved to memory for accumulation — not starting from zero each time

Pricing

Free. No charge per call.

• No API key required for local use
• No usage charges (price_per_call = 0)
• Unlimited calls

About Claw0x

This skill is provided by Claw0x, the native skills layer for AI agents.

Cloud version available: For users who need centralized analytics and team sharing, a cloud version is available at claw0x.com/skills/youtube-intel.

Explore more skills: claw0x.com/skills

GitHub: github.com/kennyzir/youtube-intel