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x-demand-radar

Collect and summarize X posts with AI pain points into a Feishu digest.

261|119|Updated Apr 3, 2026
Search Tags:#automation#ai#twitter#scraping#x#radar#demand
One-click install
npx skills add https://github.com/kennyzir/7deer_skills --skill x-demand-radar
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: x-demand-radar
Source: https://github.com/kennyzir/7deer_skills/tree/main/x-demand-radar
Command: npx skills add https://github.com/kennyzir/7deer_skills --skill x-demand-radar

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

AI Demand Radar identifies unmet AI-related product demands from X/Twitter posts and delivers concise, prioritized insights to Feishu.

Core Features & Use Cases

  • Automated daily social listening across X/Twitter to surface posts containing explicit pain points and AI-related keywords.
  • Deduplicate, filter by engagement (min_faves) and recency (last 30 days), then rank top insights.
  • AI-assisted analysis that converts each post into a structured brief (title, pain point, MVP idea, score, and validation).
  • Push digest to Feishu (optionally by Notion integration), with a configurable delivery cadence and routing.

Quick Start

Configure and run the X Demand Radar daily to scan X/Twitter posts, analyze unmet AI demands, and push a Feishu digest.

Frequently Asked Questions about x-demand-radar

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

FAQPage Schema
How do I identify unmet AI product needs from X/Twitter posts?▼

To identify unmet AI needs from X/Twitter posts, this Skill scans social chatter for explicit pain points and AI-related keywords, deduplicates content, and applies AI analysis to generate structured product briefs.

What is the best way to automate social listening for AI demand on Twitter?▼

Automating social listening for AI demand involves a four-step pipeline: searching X/Twitter, collecting posts via browser, deduplicating and ranking by engagement, and pushing AI-analyzed insights directly to Feishu.

Does this Twitter scraping pipeline filter posts by engagement and recency?▼

Yes, the Twitter scraping pipeline filters posts by a minimum favorites threshold (min_faves) and restricts collection to trend posts within the last 30 days to ensure high-quality, recent demand signals.

How do I push AI demand radar insights to Feishu?▼

To push AI demand radar insights to Feishu, the Skill converts analyzed posts into structured briefs—containing titles, pain points, MVP ideas, scores, and validations—and delivers them via a configurable routing cadence.

Can I use Notion integration instead of Feishu for receiving Twitter demand digests?▼

Yes, you can use Notion integration as an optional alternative to Feishu to receive your daily Twitter demand digest, allowing flexible routing of the analyzed AI product needs insights.

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