Emerging Topic Scout
Real-time monitoring of bioRxiv, medRxiv preprints, and academic Twitter discussion trends to identify "latent" scientific research hotspots that have not yet been defined by mainstream journals (such as the early days of AlphaFold or CRISPR).
SKILL.md
Emerging Topic Scout
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:
# 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
cd /Users/z04030865/.openclaw/workspace/skills/emerging-topic-scout
pip install -r scripts/requirements.txt
Usage
Basic Scan (Recommended: Use arXiv)
python scripts/main.py --sources arxiv --days 7 --output json
Legacy bioRxiv/medRxiv (May not work due to Cloudflare)
python scripts/main.py --sources biorxiv medrxiv --days 7 --output json
Advanced Configuration (arXiv Recommended)
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)
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
# 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:
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:
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)
python scripts/main.py --sources arxiv --days 1 --output markdown
Example 2: Daily Scan with bioRxiv (May not work)
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
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:
- ✅ Added browser User-Agent headers → Failed (Cloudflare detects bot)
- ✅ Added complete browser headers (Accept, Accept-Language, etc.) → Failed
- ❌ 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:
# 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
# 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
- Basic Functionality: Standard input → Expected output
- Edge Case: Invalid input → Graceful error handling
- 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