Analyze research hotspots for a disease or topic and recommend representative literature. Use when users need to identify trending directions, topic clusters, or generate hotspot review reports. Input is a disease name or research topic; output is a structured hotspot analysis report and representative literature list.
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tessl review fix ./scientific-skills/Evidence Insight/research-hotspot-analysis/SKILL.mdOutput must strictly follow this structured report format to ensure users receive directly readable decision-ready content rather than a simple text description.
Display all identified hotspot topics and their popularity metrics in tabular form.
| Hotspot Topic | Popularity Index | Trend Direction | Representative Papers | Active Years |
|---|---|---|---|---|
| [Topic 1] | ★★★★★ | Rising | 45 papers | 2023-2026 |
| [Topic 2] | ★★★★ | Stable | 28 papers | 2022-2026 |
| [Topic 3] | ★★★ | Declining | 12 papers | 2020-2024 |
Each hotspot is expanded independently, including popularity rating, trend description, sub-direction composition, and key papers.
| Paper | Journal | Year | Citations | Evidence Level |
|---|---|---|---|---|
| [Title] | Nature | 2025 | 230 | High |
| [Title] | Cell Rep | 2024 | 98 | Medium |
| [Title] | Front Immunol | 2024 | 15 | Low |
...
Analyze under-explored areas in current literature.
| Research Gap | Potential Value | Feasibility | Reason |
|---|---|---|---|
| [Gap 1 - underexplored direction] | High | Medium | Few than 10 papers, but clear clinical demand |
| [Gap 2] | Medium | High | Mature tools available, but not yet applied in this field |
Based on the preceding analysis, provide concrete actionable research entry suggestions.
| Priority | Recommended Direction | Reason | Expected Output |
|---|---|---|---|
| 1 | [Direction A] | High popularity + existing gap + good feasibility | 1 review / 1 experimental design |
| 2 | [Direction B] | Emerging hotspot + low competition | 1-2 research papers |
| 3 | [Direction C] | Niche but high clinical value | Case series / methodology paper |
| Field | Required | Format/Source | Example | If Missing |
|---|---|---|---|---|
topic | Yes | Text | lung cancer immunotherapy | Stop and request topic |
time_range | No | Time range | last 5 years | Default to recent literature |
focus | No | Text | mechanism, clinical translation | Default to comprehensive hotspot output |
search_pubmed from scripts/analysis_ops.py to search relevant literature and obtain PMIDs and basic metadata.word_frequency on the returned medline_texts to count high-frequency keywords or MeSH terms.references/prompt_templates.md to cluster high-frequency keywords into 3-6 hotspot topics.match_keywords to map representative literature to each topic, avoiding mismatches between topics and evidence.sort_by_jif_and_select to choose representative literature, then use fetchPMCArticleDetails or fetchPubmedArticleDetails to supplement details.topic overview, hotspot topics, supporting papers, next-step suggestions.PARTIAL.fetchPMCArticleDetails: Get article details.fetchPubmedArticleDetails: Get PubMed details.scripts/analysis_ops.py: Contains helper functions for PubMed search, frequency analysis, keyword matching, and result formatting.references/prompt_templates.md: Contains the system prompts for LLM analysis.This skill accepts requests that match the documented purpose of research-hotspot-analysis and include enough context to complete the workflow safely.
scripts/analysis_ops.py exists and can perform at least the three core steps: search, word frequency, and matching.63c61d3
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