Emerging Topic Scout

Monitor bioRxiv/medRxiv preprints and academic discussions to identify emerging research hotspots before they appear in mainstream journals

A real-time monitoring system for identifying "incubation period" research hotspots in biological and medical sciences before they are defined by mainstream journals.

Overview

This skill continuously monitors:

• bioRxiv: Biology preprints via RSS/API ⚠️ Currently blocked by Cloudflare
• medRxiv: Medicine preprints via RSS/API ⚠️ Currently blocked by Cloudflare
• arXiv: Quantitative Biology preprints via RSS ✅ Recommended alternative
• Academic discussions: Social media and forum mentions

It uses trend analysis algorithms to detect sudden spikes in topic frequency, cross-platform mentions, and emerging keyword clusters.

⚠️ Network Access Notice

bioRxiv and medRxiv are currently protected by Cloudflare JavaScript Challenge, which prevents programmatic RSS access. As a workaround, this skill now supports arXiv q-bio (Quantitative Biology) as an alternative data source.

Recommended usage:

bash

# Use arXiv for reliable data fetching
python scripts/main.py --sources arxiv --days 30

# bioRxiv/medRxiv may return 0 results due to Cloudflare protection
python scripts/main.py --sources biorxiv medrxiv --days 30  # May not work

Installation

bash

cd /Users/z04030865/.openclaw/workspace/skills/emerging-topic-scout
pip install -r scripts/requirements.txt

Usage

Basic Scan (Recommended: Use arXiv)

bash

python scripts/main.py --sources arxiv --days 7 --output json

Legacy bioRxiv/medRxiv (May not work due to Cloudflare)

bash

python scripts/main.py --sources biorxiv medrxiv --days 7 --output json

Advanced Configuration (arXiv Recommended)

bash

python scripts/main.py \
  --sources arxiv \
  --keywords "CRISPR,gene editing,machine learning" \
  --days 14 \
  --min-score 0.7 \
  --output markdown \
  --notify

Legacy Configuration (bioRxiv/medRxiv - May not work)

bash

python scripts/main.py \
  --sources biorxiv medrxiv \
  --keywords "CRISPR,gene editing,long COVID" \
  --days 14 \
  --min-score 0.7 \
  --output markdown \
  --notify
# Note: bioRxiv/medRxiv may return 0 results due to Cloudflare protection

## Parameters

| Parameter | Type | Default | Description |
|-----------|------|---------|-------------|
| `--sources` | list | `arxiv` | Data sources to monitor (arxiv recommended due to Cloudflare issues with biorxiv/medrxiv) |
| `--keywords` | string | (auto-detect) | Comma-separated keywords to track |
| `--days` | int | `7` | Lookback period in days |
| `--min-score` | float | `0.6` | Minimum trending score (0-1) |
| `--max-topics` | int | `20` | Maximum topics to return |
| `--output` | string | `markdown` | Output format: `json`, `markdown`, `csv` |
| `--notify` | flag | `false` | Send notification for high-priority topics |
| `--config` | path | `config.yaml` | Path to configuration file |

## Output Format

### JSON Output

```json
{
  "scan_date": "2026-02-06T05:57:00Z",
  "sources": ["biorxiv", "medrxiv"],
  "hot_topics": [
    {
      "topic": "gene editing therapy",
      "keywords": ["CRISPR", "base editing", "prime editing"],
      "trending_score": 0.89,
      "velocity": "rapid",
      "preprint_count": 34,
      "cross_platform_mentions": 127,
      "related_papers": [
        {
          "title": "New CRISPR variant shows promise",
          "authors": ["Smith J.", "Lee K."],
          "doi": "10.1101/2026.01.15.xxxxx",
          "source": "biorxiv",
          "published": "2026-01-15",
          "abstract_summary": "..."
        }
      ],
      "emerging_since": "2026-01-20"
    }
  ],
  "summary": {
    "total_papers_analyzed": 1247,
    "new_topics_detected": 8,
    "high_priority_alerts": 2
  }
}

Markdown Output

markdown

# Emerging Topics Report - 2026-02-06

## 🔥 High Priority Topics

### 1. Gene Editing Therapy (Score: 0.89)
- **Keywords**: CRISPR, base editing, prime editing
- **Growth Rate**: Rapid (+145% vs last week)
- **Preprints**: 34 papers
- **Cross-platform mentions**: 127

#### Key Papers
1. "New CRISPR variant shows promise" - Smith J. et al.
   - DOI: 10.1101/2026.01.15.xxxxx
   - Source: bioRxiv

Configuration File

Create config.yaml for persistent settings:

yaml

sources:
  arxiv:
    enabled: true
    rss_url: "https://export.arxiv.org/rss/q-bio"
    description: "arXiv Quantitative Biology - Recommended (no Cloudflare)"
  biorxiv:
    enabled: false  # Disabled due to Cloudflare protection
    rss_url: "https://www.biorxiv.org/rss/recent.rss"
    api_endpoint: "https://api.biorxiv.org/details/"
    note: "Currently blocked by Cloudflare JavaScript Challenge"
  medrxiv:
    enabled: false  # Disabled due to Cloudflare protection
    rss_url: "https://www.medrxiv.org/rss/recent.rss"
    api_endpoint: "https://api.medrxiv.org/details/"
    note: "Currently blocked by Cloudflare JavaScript Challenge"

trending:
  min_papers_threshold: 5
  velocity_window_days: 3
  novelty_weight: 0.4
  momentum_weight: 0.6

keywords:
  auto_detect: true
  custom_trackers:
    - "artificial intelligence"
    - "machine learning"
    - "single cell"
    - "spatial transcriptomics"

output:
  default_format: markdown
  save_history: true
  history_path: "./data/history.json"

notifications:
  enabled: false
  high_score_threshold: 0.8

Trending Score Algorithm

The trending score (0-1) is calculated using:

text

Score = (Novelty × 0.4) + (Momentum × 0.4) + (CrossRef × 0.2)

Where:
- Novelty: Inverse frequency of topic in historical data
- Momentum: Rate of increase in mentions over velocity window
- CrossRef: Mentions across multiple platforms

API Endpoints

bioRxiv API

• Base: https://api.biorxiv.org/
• Details: /details/[server]/[DOI]/[format]
• Publication: /pub/[DOI]/[format]

medRxiv API

• Same structure as bioRxiv

Data Storage

Historical data is stored in data/history.json for:

• Trend comparison
• Velocity calculation
• Duplicate detection

Examples

Example 1: Quick Daily Scan (arXiv - Recommended)

bash

python scripts/main.py --sources arxiv --days 1 --output markdown

Example 2: Daily Scan with bioRxiv (May not work)

bash

python scripts/main.py --sources biorxiv --days 1 --output markdown
# Note: May return 0 results due to Cloudflare protection

### Example 2: Weekly Deep Analysis

```bash
python scripts/main.py \
  --days 7 \
  --min-score 0.7 \
  --max-topics 50 \
  --output json \
  > weekly_report.json

Example 3: Track Specific Research Area

bash

python scripts/main.py \
  --keywords "Alzheimer,neurodegeneration,amyloid" \
  --days 30 \
  --min-score 0.5

Known Issues

bioRxiv/medRxiv Cloudflare Protection

Status: ❌ Blocked
Issue: bioRxiv and medRxiv RSS feeds are protected by Cloudflare JavaScript Challenge, which prevents programmatic access. The site returns an HTML page requiring JavaScript execution and cookie validation.

Attempted Solutions:

1. ✅ Added browser User-Agent headers → Failed (Cloudflare detects bot)
2. ✅ Added complete browser headers (Accept, Accept-Language, etc.) → Failed
3. ❌ Browser automation (Selenium/Playwright) → Not implemented (complex, heavy dependency)

Workaround: ✅ Use arXiv instead

• arXiv q-bio (Quantitative Biology) RSS is accessible without protection
• Contains computational biology, bioinformatics, and quantitative biology papers
• Successfully tested: 35+ papers fetched in 30-day window

Usage:

bash

# Recommended: Use arXiv
python scripts/main.py --sources arxiv --days 30

# Not working: bioRxiv/medRxiv
python scripts/main.py --sources biorxiv medrxiv --days 30  # Returns 0 papers

Troubleshooting

Rate Limiting

If you encounter rate limits, increase the --delay parameter (default: 1s between requests).

Missing Papers (0 results from bioRxiv/medRxiv)

This is expected due to Cloudflare protection. Use --sources arxiv instead.

RSS Feed Access Denied

Some institutional firewalls may block preprint servers. Ensure you can access:

• ✅ https://export.arxiv.org/rss/q-bio (should work)
• ❌ https://www.biorxiv.org/rss/recent.rss (Cloudflare blocked)

Low Trending Scores

For niche topics, lower --min-score threshold or increase --days for more data.

References

See references/README.md for:

• API documentation links
• Research papers on trend detection
• Related tools and resources

License

MIT License - Part of OpenClaw Skills Collection

Risk Assessment

Risk Indicator	Assessment	Level
Code Execution	Python scripts with tools	High
Network Access	External API calls	High
File System Access	Read/write data	Medium
Instruction Tampering	Standard prompt guidelines	Low
Data Exposure	Data handled securely	Medium

Security Checklist

• No hardcoded credentials or API keys
• No unauthorized file system access (../)
• Output does not expose sensitive information
• Prompt injection protections in place
• API requests use HTTPS only
• Input validated against allowed patterns
• API timeout and retry mechanisms implemented
• Output directory restricted to workspace
• Script execution in sandboxed environment
• Error messages sanitized (no internal paths exposed)
• Dependencies audited
• No exposure of internal service architecture

Prerequisites

bash

# Python dependencies
pip install -r requirements.txt

Evaluation Criteria

Success Metrics

• Successfully executes main functionality
• Output meets quality standards
• Handles edge cases gracefully
• Performance is acceptable

Test Cases

1. Basic Functionality: Standard input → Expected output
2. Edge Case: Invalid input → Graceful error handling
3. Performance: Large dataset → Acceptable processing time

Lifecycle Status

• Current Stage: Draft
• Next Review Date: 2026-03-06
• Known Issues:
  • ⚠️ bioRxiv/medRxiv blocked by Cloudflare (use arXiv as workaround)
  • Network access limitations for some RSS feeds
• Planned Improvements:
  • Investigate bioRxiv/medRxiv API alternatives
  • Consider browser automation for Cloudflare bypass
  • Add more arXiv categories (q-bio subcategories)
  • Performance optimization