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blog-discourse

Aggregate social and developer platform discourse into structured research briefs.

Updated Jun 5, 2026
Search Tags:#content strategy#blogging#research#social listening#trend analysis#discourse
One-click install
npx skills add https://github.com/smarmen86/claude-code-kit --skill blog-discourse-smarmen86
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: blog-discourse
Source: https://github.com/smarmen86/claude-code-kit/tree/main/skills/blog-discourse
Command: npx skills add https://github.com/smarmen86/claude-code-kit --skill blog-discourse-smarmen86

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires python3, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This skill solves the lack of recency and practitioner-level insights in standard research by aggregating what people are actually saying about a topic across major social and developer platforms.

Core Features & Use Cases

  • Multi-Platform Aggregation: Scrapes discourse from Reddit, X, YouTube, Hacker News, and more using targeted search operators.
  • Structured Briefing: Automatically generates a DISCOURSE.md file containing consensus themes, new trends, and practitioner-specific insights.
  • Use Case: Use this before writing a trend piece or product-update reaction to ensure your content reflects current community sentiment rather than just static, evergreen information.

Quick Start

Run the blog discourse skill for the topic of generative AI to generate a research brief on the latest community discussions.

Frequently Asked Questions about blog-discourse

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

FAQPage Schema
How do I aggregate real-time public discourse for content strategy?▼

To aggregate real-time public discourse for content strategy, you can use this skill to scrape and synthesize social listening data from major platforms. It processes platform-targeted searches using Python to produce structured, citation-rich research briefs.

What is the best way to find trending community sentiment before writing a blog post?▼

The best way to find trending community sentiment for a blog post is to aggregate real-time public discourse across social and developer platforms. This approach captures current practitioner-level insights and new trends instead of relying on static, evergreen information.

Can I use Python to scrape social listening data from Reddit and Hacker News?▼

Yes, you can use Python to scrape social listening data from Reddit, Hacker News, X, and YouTube. This skill utilizes Python-based data processing alongside targeted web search operators to aggregate and structure recency-focused insights.

Do I need Python3 to generate social listening research briefs?▼

Yes, you need Python3 installed in your environment to generate social listening research briefs. It is a required dependency for running the scripts that process aggregated discourse and produce the structured DISCOURSE.md file.

How do trend analysis tools differ from standard research methods?▼

Trend analysis tools differ from standard research by prioritizing recency and practitioner-level insights. While standard research provides static information, social listening tools aggregate live public discourse to identify new trends and current community consensus.

What limitations exist when scraping social media platforms for trend identification?▼

A limitation when scraping social media platforms for trend identification is the reliance on public discourse and targeted search operators. The resulting briefs reflect current community sentiment but may lack structured evergreen depth or proprietary data.

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