Ai Research Tracker

Directory Structure

OpenAI Research/                    # Or "AI Research/" for multiple sources
├── README.md                       # System documentation
├── Index.md                        # Navigation hub
├── Papers/                         # Detailed research notes
│   ├── o3-o4-mini.md
│   ├── gpt-5.md
│   └── ...
├── Daily Updates/                  # Daily summaries
│   ├── 2025-04-09.md
│   └── ...
├── Insights/                       # Trend analysis
│   ├── trends.md
│   └── ...
├── _templates/                     # Note templates
│   ├── paper-template.md
│   └── daily-template.md
└── _scripts/                       # Automation
    └── fetch_research.py

Content Fetching Strategy

Method 1: Direct Browser Navigation (Preferred for Anthropic)

For sites like Anthropic that don't block browser access:

# Navigate to research page
browser_navigate(url="https://www.anthropic.com/research")

# Extract full text content
browser_console(expression="document.body.innerText")

# For long articles, get content in chunks
browser_console(expression="document.body.innerText.substring(0, 15000)")
browser_console(expression="document.body.innerText.substring(15000, 30000)")

Advantages:

• Full content extraction (not just summary)
• Preserves article structure
• No proxy needed for many sites
• Can scroll and navigate sections

Method 2: jina.ai Proxy (For Cloudflare-Protected Sites like OpenAI)

When direct access fails:

# Use jina.ai proxy
curl -sL --proxy "http://127.0.0.1:7890" \
  "https://r.jina.ai/http://openai.com/research" 2>&1

# For specific articles
curl -sL --proxy "http://127.0.0.1:7890" \
  "https://r.jina.ai/http://openai.com/index/article-slug/" 2>&1

When to use:

• Site blocks direct browser access
• Need quick text extraction
• Don't need interactive navigation

Response Format

jina.ai returns clean Markdown:

Title: Article Title

URL Source: http://original-url.com

Markdown Content:
# Article content...

Note Structure (Bilingual - Enhanced Format)

Each research note follows this comprehensive structure:

# [Article Title in Chinese]

**原文标题**: [Original Title]
**发布日期**: [Date]
**分类**: [Category]
**原文链接**: [URL]

## 摘要 (Abstract)
[Chinese translation of abstract/summary]

## 核心内容翻译 (Full Translation)
[Complete Chinese translation of the article content]

## 深度解读 (Deep Analysis)

### 1. 研究背景与动机
[Research context and why this matters]

### 2. 方法论与创新点
[Methods used and what's novel]

### 3. 主要发现与结论
[Key findings and conclusions]

### 4. 技术细节剖析
[Technical deep dive - architecture, algorithms, benchmarks]

### 5. 实际应用与影响
[Practical implications for developers, businesses, policymakers]

### 6. 局限性与未来方向
[Limitations and future work]

## 思考与反思 (Personal Reflection)
[Your critical thinking about the research]
- What are the implications?
- What concerns does it raise?
- How does it connect to other work?

## 相关阅读 (Related Reading)
- [Links to related papers/articles]
- [Previous work from same lab]
- [Follow-up research]

---
*Generated on [date]*

Alternative Structure (for quick notes)

For faster processing of multiple articles:

# Article Title

**原文标题**: [Original]
**发布日期**: [Date]
**分类**: [Category]
**原文链接**: [URL]

## 核心发现 (Key Findings)
- Finding 1
- Finding 2
- Finding 3

## 中文翻译 (Translation)
[Key sections translated]

## 分析 (Analysis)
[Brief analysis]

## 影响 (Implications)
[Practical implications]

---
*Generated: [date]*

Setup Instructions

Step 1: Create Directory Structure

mkdir -p "{OBSIDIAN_PATH}/OpenAI Research/"{Papers,Daily Updates,Insights,_templates,_scripts}

Step 2: Create Templates

paper-template.md:

---