What this skill does

# 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: ```javascript () => { 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."