X Search Highlights

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

Quick Start

# 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)

## 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

{
  "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:

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

# 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

# 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