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twitter-intel

Identify and synthesize Twitter/X signals into structured intelligence reports.

9|2|Updated Mar 2, 2026
Search Tags:#information-retrieval#bot-detection#trend-detection#kols#signal-filtering#twitter-intel#intelligence-briefing
One-click install
npx skills add https://github.com/botlearn-ai/botlearn-skills --skill twitter-intel-botlearn-ai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: twitter-intel
Source: https://github.com/botlearn-ai/botlearn-skills/tree/main/skills/twitter-intel
Command: npx skills add https://github.com/botlearn-ai/botlearn-skills --skill twitter-intel-botlearn-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Twitter/X platform intelligence gathering and synthesis for OpenClaw-like agents, enabling detection of KOLs, trends, bot activity, and actionable insights.

Core Features & Use Cases

  • Monitor and identify key opinion leaders across tiers and domains.
  • Detect emerging trends and evolving narratives, with source attribution and confidence.
  • Synthesize structured intelligence reports that distinguish organic vs inauthentic activity and provide actionable monitoring recommendations.

Quick Start

Analyze a defined topic on Twitter/X, curate KOLs, filter signals, and generate a structured briefing with timeline, sentiment, and source links.

Frequently Asked Questions about twitter-intel

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

FAQPage Schema
How do I monitor KOLs and detect emerging trends on Twitter?▼

Twitter intelligence monitoring identifies key opinion leaders across tiers and detects emerging trends with source attribution. It synthesizes platform signals into actionable intelligence reports for defined topics and time windows.

Can I distinguish organic Twitter activity from bot-driven narratives?▼

Bot-detection filters Twitter signals to distinguish organic activity from inauthentic behavior. Multi-layer signal filtering applies domain best practices to identify manipulated narratives and provide confidence scores.

What is the best way to generate a structured intelligence briefing from Twitter signals?▼

Generating a structured intelligence briefing requires curating Twitter signals, filtering noise, and synthesizing data into reports. Outputs include timelines, sentiment analysis, source links, and actionable monitoring recommendations.

How does sentiment analysis work across specified time windows for Twitter topics?▼

Sentiment analysis evaluates Twitter signals across specified time windows and scopes. It synthesizes topic data to track narrative evolution, attribute sources, and generate confidence-scored intelligence for monitoring.

Do I need API access to track evolving narratives on Twitter?▼

Tracking evolving narratives requires adhering to Twitter API usage guidelines for signal retrieval. The skill applies multi-layer filtering to retrieved data to detect trends and synthesize structured intelligence reports.

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