Social Pulse Scanner

The problem

Standard search engines prioritize SEO-optimized articles and outdated blog posts, making it difficult to find what real people are discussing right now. Traditional market research is too slow to capture rapid shifts in social sentiment or emerging niche trends.

What it does

• Scans ~20 platforms including Reddit, X, YouTube, TikTok, Hacker News, Polymarket, and GitHub simultaneously.
• Enforces a strict 30-day content window to ensure maximum freshness and relevance.
• Clusters data across sources, identifying high-signal trends when topics appear on 3+ platforms.
• Calculates engagement scores using platform-specific formulas like upvote ratios and liquidity volume.
• Generates cited briefings with verbatim community comments and normalized sentiment ranking.

Frameworks & tools

Python-based engine, yt-dlp for video metadata, SQLite for watchlist persistence, and CLI adapters for multi-platform scraping.

Why this beats prompting it yourself

Manually prompting an LLM to search the web often results in hallucinated links or surface-level summaries of a few Google results. This skill implements a complex multi-step orchestration that resolves handles, calculates cross-platform engagement scores, and enforces a strict output contract for consistent, data-backed reports.

Use cases

• Identify high-demand features by analyzing competitor complaints on Reddit and X.
• Monitor market sentiment and betting odds for industry events via Polymarket.
• Detect emerging technical trends by tracking GitHub stars and Hacker News discussions.
• Generate weekly automated briefings on specific brand or product mentions.

Known limitations

Briefings strictly exclude content older than 30 days. API keys are required for some platforms like X or Perplexity to access full depth, though several sources work zero-config.