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TechNickAI
TechNickAICOMMUNITY
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mob-check

Aggregates live public discourse from multiple platforms into a synthesized brief ranked by engagement and recency.

1|Updated May 21, 2026
Search Tags:#summarization#analysis#multi-source#engagement#ranking#social-media#sentiment
One-click install
npx skills add https://github.com/TechNickAI/hermes-config --skill mob-check
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: mob-check
Source: https://github.com/TechNickAI/hermes-config/tree/main/skills/mob-check
Command: npx skills add https://github.com/TechNickAI/hermes-config --skill mob-check

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

Use when the user wants to know what real people are actually saying about a topic right now, not the SEO/editorial version. Pulls recent posts and engagement from Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, ranks by engagement and recency with a deterministic scorer, and writes one synthesized brief. Triggers: "what are people saying about X", "what's the vibe/sentiment on X", "X vs Y what does the community think", "how are people using X", "is X worth it", "latest on X", "take the pulse on X", "/mob-check", "what's the mob saying about X".

Core Features & Use Cases

  • Surface cross-source live discussions and generate a concise, on-topic synthesis.
  • Rank items by engagement and recency using a deterministic scorer to ensure reproducibility.
  • Produce a clear brief that can be used for quick decision making or briefing teammates.
  • Use cases include competitive landscape polling, sentiment checks before launches, and monitoring public reception over time.

Quick Start

Ask the mob-check skill to generate a synthesized brief for a topic using the latest cross-source discussions.

Frequently Asked Questions about mob-check

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I check real-time public sentiment across social media and web sources?▼

Real-time public sentiment is checked by aggregating live discourse across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web. The ranker fuses engagement and recency signals to produce a synthesized brief for decision making.

What's the best way to compare community opinions on competing topics across multiple platforms?▼

To compare community opinions on competing topics, aggregate cross-source posts and rank them by engagement and recency. This surfaces what real people are saying right now, generating a concise synthesis for competitive landscape polling.

How does ranking by engagement and recency work for multi-source social media analysis?▼

Ranking by engagement and recency uses a deterministic scorer to fuse signals from multi-source social media posts. It produces per-item relevance, freshness, and engagement metrics to ensure reproducible results across sources.

Do I need any specific data connectors to pull live discussions from Reddit, X, and YouTube?▼

You do not need manual data connectors to pull live discussions from Reddit, X, and YouTube. The process relies on Hermes to fetch data directly from these platforms and the built-in ranker to synthesize the results.

Can I monitor public reception over time using cross-source discourse analysis?▼

You can monitor public reception over time by repeatedly aggregating cross-source discourse. Running this process periodically surfaces live discussions and generates concise briefs tracking sentiment shifts for decision making.

What are the limitations of using a deterministic scorer for social media sentiment analysis?▼

A deterministic scorer for social media sentiment analysis ensures reproducible rankings by engagement and recency, but it relies on Hermes to fetch data. It synthesizes public discourse rather than performing deep emotional sentiment classification.

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