Social Trend Report

Generate weekly trend reports by monitoring Reddit, Twitter/X, and YouTube for any niche or industry.

Overview

This skill automates the content research workflow:

1. Collect data from multiple platforms (Reddit, Twitter, YouTube)
2. Analyze trends, sentiment, and engagement patterns
3. Output a structured report with actionable content ideas

Setup

Prerequisites

• bird CLI for Twitter/X data (install: npm i -g @anthropic/bird)
• Requires Twitter auth cookies: AUTH_TOKEN and CT0 env vars
• web_fetch tool for Reddit JSON API
• web_search tool for YouTube discovery

Configuration

Create a config.json in your workspace to customize monitoring targets:

{
  "niche": "your industry/niche name",
  "reddit": {
    "subreddits": ["subreddit1", "subreddit2", "subreddit3"],
    "timeframe": "week",
    "limit": 10
  },
  "twitter": {
    "keywords": ["keyword1", "keyword2 phrase", "keyword3"],
    "lang": "en"
  },
  "youtube": {
    "search_queries": ["niche weekly update", "niche tutorial 2026"],
    "competitors": ["@competitor1", "@competitor2"]
  },
  "output": {
    "dir": "reports",
    "filename_pattern": "weekly-{date}.md",
    "discord_channel": null
  }
}

If no config.json exists, the skill will prompt you for niche and targets.

Workflow

Step 1: Data Collection

Run scripts/collect.sh or use the tools directly:

Reddit (via web_fetch):

URL pattern: https://www.reddit.com/r/{subreddit}/top/.json?t=week&limit=10
Extract: title, score, num_comments, selftext (first 200 chars)

Twitter/X (via bird CLI):

bird search "{keyword}" --limit 20

YouTube (via web_search):

Search: "{niche} {keyword} this week" + competitor channel names

Step 2: AI Analysis

Feed collected data to the agent with this analysis prompt:

> Analyze the following social media data for the {niche} niche.

> Identify: (1) trending topics with data backing, (2) frequently asked questions,

> (3) content ideas with suggested formats, (4) competitor moves, (5) keyword trends.

> Be specific and actionable. Prioritize by engagement metrics.

Step 3: Report Output

The report follows this structure:

📊 {Niche} Trend Report ({date_range})

🔥 Trending Topics (3-5)
- Topic — Why it's hot + data (upvotes/views/engagement)

❓ Frequently Asked Questions (3-5)
- Common question → content opportunity

💡 Content Ideas (5)
- Idea title
  - Rationale + data backing
  - Suggested format (video/article/reel/thread)
  - Urgency: 🔴 time-sensitive / 🟡 this week / 🟢 evergreen

📈 Competitor Activity (2-3)
- What competitors published + performance

🌟 Keyword Trends
- High-engagement keywords this period

Automation

Cron Setup (OpenClaw)

Schedule weekly reports via OpenClaw cron:

openclaw cron add \
  --name "Weekly Trend Report" \
  --schedule "0 10 * * 1" \
  --timezone "America/New_York" \
  --task "Read skills/social-trend-report/SKILL.md and generate this week's trend report using config.json. Save to reports/ and announce in Discord." \
  --model sonnet

Hotspot Alert Mode

For time-sensitive trend detection, add to your HEARTBEAT.md:

- Check if any monitored subreddit has a post with 500+ upvotes in last 24h
- If yes, generate a hotspot alert card and notify

Tips

• Start small: Monitor 2-3 subreddits first, expand later
• Reddit JSON: Append .json to any Reddit URL for structured data. Use web_fetch (not curl) if behind a firewall
• Twitter rate limits: bird search has rate limits; keep to 4-6 queries per run
• Iterate on keywords: Review each report and refine search terms based on what surfaces
• Cross-platform signals: A topic trending on both Reddit AND Twitter is high-confidence

Example Niches

This skill works for any niche. Example configs:

• Tarot/Astrology: r/tarot, r/astrology, r/spirituality + "tarot reading", "weekly horoscope"
• SaaS/Dev Tools: r/SaaS, r/startups, r/webdev + "developer tools", "AI coding"
• E-commerce/DTC: r/ecommerce, r/shopify, r/dropship + "shopify store", "DTC brand"
• Fitness: r/fitness, r/weightlifting, r/running + "workout routine", "fitness tips"