X Search Highlights#

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#

ParameterTypeDefaultDescriptiontopicstringrequiredSearch query (e.g., "Claude Code", "AI Agent")maxResultsnumber5Maximum number of posts to returnminLikesnumber0Minimum likes threshold (filter low-engagement)scrollTimesnumber3Number of scroll iterations (more = more candidates)sortBystring"engagement"Sort method: engagement, likes, views, recentoutputFormatstring"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