| name | research-papers |
| description | Find, rank, and summarize academic papers with OpenAlex. Use for paper search, DOI lookup, citation-chain inspection, open-access PDF discovery/download, and Markdown literature reviews. Optimized for neuroimaging and AI research topics such as dynamic functional brain networks, rs-fMRI/fMRI, graph neural networks, spatiotemporal attention, Alzheimer's disease, MCI, Parkinson's disease, and neurodegenerative disease classification. |
Research Papers
Use OpenAlex to search scholarly works, inspect DOI/citation context, discover legal open-access PDFs, and generate structured Markdown literature reviews.
This skill is especially useful for neuroimaging + AI workflows: dynamic functional brain networks, rs-fMRI/fMRI, graph neural networks, spatiotemporal attention, Alzheimer's disease, MCI, Parkinson's disease, and neurodegenerative disease classification.
What it helps with
- Search recent or highly cited papers by topic, author, DOI, or title.
- Expand short Chinese/English research prompts into stronger OpenAlex queries.
- Build citation context around a DOI.
- Find open-access full text when legally available.
- Generate longer Markdown literature reviews and optionally hand them off through QQBot.
Originally based on an academic-research workflow and adapted for neuroimaging literature search.
Default Research Profile
When the user asks for papers, related work, recent methods, baselines, or literature reviews without giving a full topic, assume the default research context is:
- Dynamic functional brain networks
- rs-fMRI / fMRI neuroimaging
- Dynamic functional connectivity
- Alzheimer's disease, MCI, and Parkinson's disease
- Neurodegenerative disease classification
- Graph neural networks for brain networks
- Spatiotemporal attention and temporal-spatial interaction
- Cross-time-slice dynamic brain state modeling
Do not ask the user to repeat this research direction unless the request is ambiguous across fields.
Query Expansion Rules
When the user gives a short or Chinese query, expand it into English academic search terms before calling OpenAlex.
Examples:
- "recent papers" โ
dynamic functional brain network rs-fMRI graph neural network neurodegenerative disease classification
- "AD classification" โ
Alzheimer's disease classification mild cognitive impairment rs-fMRI dynamic functional connectivity graph neural network
- "brain network GNN" โ
functional brain network dynamic brain connectivity GCN GAT graph neural network disease diagnosis
- "ๆถ็ฉบๆณจๆๅ" โ
spatiotemporal attention dynamic brain network fMRI temporal-spatial interaction neurodegenerative disease classification
- "ๅจๆ่็ฝ็ป่ฎบๆ" โ
dynamic functional brain network dynamic functional connectivity rs-fMRI graph neural network Alzheimer's disease classification
If the user gives a specific DOI, author, paper title, or clearly defined topic, do not over-expand.
Language Behavior
The user may ask in Chinese.
For Chinese requests:
- Translate or expand the search query into English academic keywords.
- Return explanations in Chinese unless the user asks for English.
- Explain why each selected paper is relevant to the user's research direction.
Quick Start
Search papers by topic
python scripts/scholar-search.py search "dynamic functional brain network Alzheimer's disease graph neural network" --limit 10 --years 2020-2026
Search rs-fMRI and disease classification papers
python scripts/scholar-search.py search "rs-fMRI graph neural network neurodegenerative disease classification" --limit 10 --years 2020-2026
Search spatiotemporal attention papers
python scripts/scholar-search.py search "spatiotemporal attention dynamic brain network fMRI" --limit 10 --years 2020-2026
Search by author
python scripts/scholar-search.py author "Yann LeCun" --limit 5
Look up by DOI
python scripts/scholar-search.py doi "10.1038/s41586-021-03819-2"
Get citation chain
python scripts/scholar-search.py citations "10.1038/s41586-021-03819-2" --direction both
Deep read
python scripts/scholar-search.py deep "10.1038/s41586-021-03819-2"
New Features
Cache
API responses are cached locally to reduce repeated requests.
Useful options:
--no-cache--refresh-cache--cache-ttl N
Example:
python scripts/scholar-search.py --refresh-cache search "dynamic functional brain network Alzheimer's disease" --limit 10
Open-Access PDF Download
Use --download-pdf to download PDFs only when they are legally available from open-access sources.
python scripts/scholar-search.py search "dynamic functional brain network Alzheimer's disease" --limit 5 --oa --download-pdf
Do not bypass paywalls or use unauthorized sources.
QQBot Handoff
For long literature reviews, generate a Markdown review file and send it through qqbot-send:
python scripts/scholar-search.py review "dynamic functional brain networks in Alzheimer's disease" --papers 30 --years 2020-2026 --qqmedia
If needed, specify the staging script manually:
python scripts/scholar-search.py review "dynamic brain network Alzheimer's disease" --papers 20 --qqmedia --stage-media-script "../qqbot-send/scripts/stage_media.py"
Literature Review Workflow
Generate a Markdown literature review:
python scripts/scholar-search.py review "dynamic functional brain networks in Alzheimer's disease" --papers 30 --years 2020-2026 --output review.md
This will:
- Search across multiple query variations.
- Deduplicate and rank papers.
- Identify thematic clusters.
- Generate a structured Markdown synthesis.
- Optionally download open-access PDFs.
- Optionally hand off the review file to QQBot.
Options:
--papers N โ Target number of papers.--output FILE โ Write review to file.--years 2020-2026 โ Restrict publication years.--json โ Output JSON.--oa โ Open-access papers only.--download-pdf โ Download open-access PDFs.--qqmedia โ Generate a file and output a <qqmedia>...</qqmedia> tag.
Preferred Output
When presenting paper results, include:
- Title
- Year
- Authors
- Source
- Citation count
- DOI
- Open-access URL or PDF URL if available
- Why the paper is relevant to the user's research
For literature reviews, organize by:
- Research background
- Main methods
- Representative papers
- Model architectures
- Dynamic brain network modeling strategies
- Limitations
- Relevance to the user's own research
When the result is long, prefer generating a Markdown file and using --qqmedia.
Output Format
Search commands return structured data including:
- Title and year
- Authors
- Abstract
- Citation count
- DOI
- Open-access URL
- PDF URL or downloaded PDF path
- Source journal/venue
- OpenAlex ID
Tips
- Use
--sort citations for highly cited papers.
- Use
--sort recent for newer papers.
- Use
--oa --download-pdf when the user wants downloadable full text.
- Use
review --qqmedia when the literature review is too long for direct chat output.
