| name | research-tracking |
| description | Research direction tracking, trend discovery, and author monitoring. |
| metadata | {"nanobot": {"always": false}} |
Research Tracking Skill
This skill helps you monitor research directions, discover emerging trends, and track influential authors.
When to Use This Skill
Activate when the user asks for:
- "最近 XXX 有什么新进展?"
- "帮我追踪一下 XXX 方向"
- "XXX 领域现在最火的是什么?"
- "XXX 团队最近在做什么?"
- "有没有什么跨学科的机会?"
Trend Discovery Methods
Method 1: Keyword Frequency Analysis
Track which keywords are appearing more frequently in recent papers:
- Search for papers in the last 6 months on arXiv
- Extract key terms from titles and abstracts
- Compare with 1-2 years ago to identify rising terms
Example: If "speculative decoding" appears in 5% of LLM inference papers in 2024 vs. 0% in 2023, it's an emerging trend.
Method 2: Citation Velocity
Papers gaining citations rapidly (relative to their age) indicate hot topics:
- Use Semantic Scholar API to get citation counts and velocity
- Compare across subfields
Method 3: Conference Proceedings Scan
Top conference acceptance patterns reveal trends:
- NeurIPS/ICML/ICLR: What topics have dedicated workshops?
- ACL/EMNLP: What shared tasks are new this year?
- CVPR/ICCV/ECCV: What challenges are being organized?
Method 4: Cross-Pollination Detection
Breakthroughs often come from borrowing ideas across fields:
- Look for papers combining previously separate areas
- Example: "Transformer + graph neural networks" → Graph Transformers
- Example: "Diffusion models + protein design" → new bio-AI intersection
Author Tracking Strategy
Identifying Key Authors
- Pioneers: First paper on the topic, highly cited
- Prolific contributors: 3+ papers on the topic in recent years
- Influential critics: Papers that spark debate or correction
Tracking Workflow
- Use
academic_search with au:AuthorName to find their recent papers
- Use
get_related_papers on their most influential work
- Check their collaborators (co-authors) for related work
Author Alert Setup
Guide the user to set up research_feed in config:
{
"research": {
"research_feed": {
"enabled": true,
"feeds": [
{
"source": "arxiv",
"categories": ["cs.CL", "cs.LG"],
"keywords": ["your keyword 1", "your keyword 2"],
"schedule": "0 8 * * *",
"max_results": 5,
"notify_channel": "feishu"
}
]
}
}
}
Trend Report Format
When reporting trends to the user, use this structure:
# 🔥 [Topic] 最新趋势报告
## 热门方向
1. **[Trend Name]** — [Brief description]
- 代表论文: [Paper 1], [Paper 2]
- 热度指标: [Citations, frequency, etc.]
2. **[Trend Name]** — ...
## 值得关注的论文
| 论文 | 作者 | 核心创新 | 为什么重要 |
|------|------|---------|-----------|
| ... | ... | ... | ... |
## 新兴交叉领域
- **[Intersection A + B]** — [Description and potential]
## 建议行动
1. [具体建议:阅读某篇论文、关注某个作者、尝试某个方法]
Research Profile Maintenance
If memory/research_profile.md exists:
- Update it with newly discovered keywords and authors
- Mark topics that are becoming less relevant
- Add new research questions that emerge from trend analysis
Proactive Tracking Tasks
You can suggest adding these to HEARTBEAT.md:
- Weekly arXiv scan for top keywords
- Monthly citation velocity check for tracked papers
- Quarterly trend summary report