X Search Highlights

Search and extract high-value posts from X (Twitter) with engagement-based ranking. Use when user asks to search X, find best posts, get highlights from Twitter/X, or extract high-engagement content on a specific topic.

Search and extract high-value posts from X (Twitter) with engagement-based ranking.

Quick Start

bash

# Basic search
~/.openclaw/skills/x-search-highlights/scripts/x-search.sh "Claude Code"

# With filters
~/.openclaw/skills/x-search-highlights/scripts/x-search.sh "AI Agent" 10 5 1000 markdown

Description

Extract valuable posts from X search results based on engagement metrics (likes, retweets, replies, views). Ideal for discovering trending discussions, finding expert insights, or curating content for research.

When to Use

Activate when user asks to:

• Search X/Twitter for specific topics
• Find "best" or "high-value" posts on a subject
• Extract posts with engagement data
• Curate content from X discussions
• Discover trending discussions

Trigger phrases:

• "Search X for [topic]"
• "Find best posts about [topic] on Twitter"
• "Get highlights from X search"
• "Extract valuable tweets"

Input Parameters

Parameter	Type	Default	Description
topic	string	required	Search query (e.g., "Claude Code", "AI Agent")
maxResults	number	5	Maximum number of posts to return
minLikes	number	0	Minimum likes threshold (filter low-engagement)
scrollTimes	number	3	Number of scroll iterations (more = more candidates)
sortBy	string	"engagement"	Sort method: engagement, likes, views, recent
outputFormat	string	"markdown"	Output format: markdown, json, summary

Output Format

Markdown (default)

markdown

## 1. [Post Title/Summary]

- **标题**：[Content summary]
- **日期**：YYYY-MM-DD
- **标签**：#tag1 #tag2
- **亮点**：🎯 [Key insight] 💡 [Unique perspective]
- **互动**：X 回复 · X 转发 · X 点赞 · X 浏览
- **链接**：[点击阅读原文](URL)

JSON

json

{
  "total": 10,
  "posts": [
    {
      "text": "...",
      "author": "...",
      "likes": 1000,
      "retweets": 200,
      "views": 50000
    }
  ]
}

Workflow

1. Open search page: Navigate to X search with query
2. Load content: Scroll N times to collect candidate posts
3. Extract data: Parse DOM for post content and engagement metrics
4. Rank and filter: Calculate engagement scores, apply filters
5. Format output: Return results in requested format

Core Algorithm

Engagement Score:

text

Score = (likes × 2) + (retweets × 5) + (views × 0.01)

Weight Rationale:

• Retweets (×5): Strongest signal (public sharing)
• Likes (×2): Approval signal (low barrier)
• Views (×0.01): Reach indicator (easily inflated)

Dependencies

• bb-browser ≥ 0.11.2
• Chrome/Chromium browser
• X.com login state (in bb-browser profile)

Installation

bash

# Via ClawHub (after publishing)
clawhub install x-search-highlights

# Or clone from GitHub
git clone https://github.com/Ghostwritten/x-search-highlights.git ~/.openclaw/skills/x-search-highlights

Usage Examples

bash

# Search for "OpenClaw"
scripts/x-search.sh "OpenClaw"

# Get 10 posts with min 1000 likes
scripts/x-search.sh "AI Agent" 10 3 1000

# JSON output
scripts/x-search.sh "RAG" 20 5 0 json

Troubleshooting

No posts found:

• Check bb-browser is running: bb-browser status
• Verify X.com login state
• Try different search keywords

JSON parsing errors:

• Ensure bb-browser version ≥ 0.11.2
• Check Chrome/Chromium is accessible

Rate limits:

• Reduce scrollTimes parameter
• Add delays between operations

Limitations

• X lazy loading limits initial results
• Bookmark data not available via scraping
• Rate limits may affect large-scale scraping
• Search quality depends on X algorithm