SkillJavaScriptv1.0.0

ft-reader

Use this skill to perform deep, structured, and bilingual analysis of top articles from Financial Times (ft.com).

1 downloads
zhouziyue233
Updated Feb 15, 2026

Financial Times Deep Reader (ft-reader)

Use this skill to perform deep, structured, and bilingual analysis of top articles from Financial Times (ft.com). This skill automates login, article selection, and high-quality summarization suitable for academic and professional use.

Capabilities

  • Automated Access: Logs into FT.com using stored credentials via Browser tool.
  • Strategic Selection: Identifies "Most Read" based on user preference.
  • Bilingual Synthesis: Provides high-fidelity English-Chinese summaries with a focus on core arguments.
  • Academic Rigor: Extracts specific data, quotes, and important charts in the article.

Configuration & Credentials

  • Browser Profile: Use openclaw profile to maintain session persistence.
  • Credentials:
    • User: xxxxxx
    • Pass: xxxxxx

Workflow (Mandatory Steps)

Phase 1: Authentication & Navigation

  1. Open https://www.ft.com/login.
  2. Enter email and password.
  3. Navigate to the homepage or a specific section requested by the user.

Phase 2: Content Extraction

  1. Use evaluate to identify the top N articles from the homepage (targeting .o-teaser__heading or most-read sections).

  2. For each target article:

    • Navigate to the article URL.

    • Use evaluate with the following JavaScript to extract clean content:

      () => {
        const title = document.querySelector('h1')?.innerText;
        const standfirst = document.querySelector('div[class*="standfirst"]')?.innerText;
        const paragraphs = Array.from(document.querySelectorAll('div[class*="article-body"] p, article p'))
          .map(p => p.innerText.trim())
          .filter(text => text.length > 0);
        return { title, summary: standfirst, content: paragraphs.join('\n\n') };
      }
      

Phase 3: Analysis & Reporting

For each article, generate a report (around 600 words) using the following structure:

  • Title (Bilingual)
  • Core Opinion (Bilingual)
  • Arguments (Bilingual)
  • Conclusion (Bilingual)

Constraints

  • Style: Professional, academic, and fluff-free (follow SOUL.md).
  • Language: Always provide both English and Chinese translations for technical terms and core ideas.
  • Independent Reading: Treat each article as a standalone piece unless cross-analysis is requested.
  • Token Management: If many articles are requested, split the delivery into multiple turns to avoid truncation.

Usage Examples

  • "Lulu, use ft-reader to analyze the top 3 Most Read articles from today."
  • "Perform a deep dive into the top story on FT regarding AI productivity using the ft-reader skill."
Free
Installation
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