research-paper-downloader
Download academic papers from open-access sources when the user provides a DOI/arXiv ID or requests a keyword-based paper search, and return the saved PDF path.
Best use case
research-paper-downloader is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Download academic papers from open-access sources when the user provides a DOI/arXiv ID or requests a keyword-based paper search, and return the saved PDF path.
Teams using research-paper-downloader should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/research-paper-downloader/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How research-paper-downloader Compares
| Feature / Agent | research-paper-downloader | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Download academic papers from open-access sources when the user provides a DOI/arXiv ID or requests a keyword-based paper search, and return the saved PDF path.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
> **Source**: [https://github.com/aipoch/medical-research-skills](https://github.com/aipoch/medical-research-skills)
## When to Use
- The user provides a DOI (e.g., `10.1038/s41586-020-2649-2`) and wants the corresponding open-access PDF.
- The user provides an arXiv ID (e.g., `1706.03762`) and wants the preprint PDF.
- The user asks to search papers by keywords (e.g., "attention mechanism") and download available open-access PDFs.
- The user requests downloading an academic/research paper and expects the tool to try multiple open-access providers automatically.
- The user needs the final local save path for the downloaded PDF(s).
## Key Features
- Multi-source open-access retrieval with priority-based fallback until a PDF is found.
- Supports three input modes:
- DOI download
- arXiv ID download
- Keyword search + download (with `max_results`)
- Configurable output directory and network behavior (timeouts, retries, preferred source order).
- Clear failure modes:
- invalid identifiers
- no open-access location found
- network timeouts / source unavailable
- Safe file writing: downloads are saved only under the configured output directory.
- Consistent naming convention: `{first_author}_{year}_{title}.pdf` (truncated to a maximum length).
## Dependencies
- Python `>= 3.8`
- `requests >= 2.0.0`
- Internet access (HTTPS) to the following services:
- `api.semanticscholar.org`
- `api.openalex.org`
- `api.unpaywall.org`
- `arxiv.org`
- `pubmed.ncbi.nlm.nih.gov`
- `api.crossref.org`
## Example Usage
### CLI (scripts/download.py)
Download by DOI:
```bash
python scripts/download.py --doi "10.1038/s41586-020-2649-2" --output "~/Downloads/ResearchPapers"
```
Download by arXiv ID:
```bash
python scripts/download.py --arxiv "1706.03762" --output "~/Downloads/ResearchPapers"
```
Search by keywords and download up to 3 results:
```bash
python scripts/download.py --search "attention mechanism" --max-results 3 --output "~/Downloads/ResearchPapers"
```
### Python (import and call)
```python
from pathlib import Path
# These functions are expected to be provided by the skill implementation (e.g., scripts/download.py or a module it exposes).
from download import download_by_doi, download_by_arxiv, search_download
output_dir = Path.home() / "Downloads" / "ResearchPapers"
output_dir.mkdir(parents=True, exist_ok=True)
# 1) Download by DOI
pdf_path = download_by_doi(doi="10.1016/j.clinimag.2022.03.004", output_dir=str(output_dir))
print("Saved to:", pdf_path)
# 2) Download by arXiv ID
pdf_path = download_by_arxiv(arxiv_id="2310.12345", output_dir=str(output_dir))
print("Saved to:", pdf_path)
# 3) Keyword search and download
pdf_paths = search_download(query="transformer attention", max_results=5, output_dir=str(output_dir))
for p in pdf_paths:
print("Saved to:", p)
```
## Implementation Details
### Source Priority and Fallback
The downloader attempts open-access sources in priority order and stops at the first successful PDF retrieval:
1. Semantic Scholar (Open Access API) — `api.semanticscholar.org`
2. OpenAlex (Open Academic Graph) — `api.openalex.org`
3. Unpaywall (OA location finder) — `api.unpaywall.org`
4. arXiv (preprint server) — `arxiv.org`
5. PubMed (biomedical database) — `pubmed.ncbi.nlm.nih.gov`
6. Crossref (DOI registry/metadata) — `api.crossref.org`
If a source is unavailable, returns no OA link, or times out, the implementation should automatically proceed to the next source.
### Configuration (config.json)
Recommended configuration keys:
- `output_dir`: default download directory (e.g., `~/Downloads/ResearchPapers`)
- `timeout`: request timeout in seconds (recommended range: `30`-`120`)
- `max_retries`: maximum retry attempts for transient failures
- `preferred_sources`: ordered list of sources to try (overrides default priority)
### File Output Rules
- **Path restriction**: all files must be written only inside `output_dir`.
- **Default directory**: `~/Downloads/ResearchPapers` (if not overridden).
- **Filename format**: `{first_author}_{year}_{title}.pdf`
- **Maximum filename length**: 80 characters (truncate safely).
- The tool should return (or print) the full absolute path of each saved PDF.
### Error Handling Expectations
- **Invalid DOI/arXiv ID**: return a clear error and suggest correcting the identifier format.
- **No open-access version found**: report that no OA PDF is available and suggest alternatives (library access or contacting the authors).
- **Timeouts**: retry according to `max_retries`, then fall back to the next source.
- **Source unavailable**: skip to the next source and report which sources failed if all fail.
### Safety Constraints
- No paywall bypassing or restricted-content circumvention.
- No credential handling is required (sources are expected to work without API keys).
- The downloader must not execute external code; it only performs network requests and writes files to disk.
## When Not to Use
- Do not use this skill when the required source data, identifiers, files, or credentials are missing.
- Do not use this skill when the user asks for fabricated results, unsupported claims, or out-of-scope conclusions.
- Do not use this skill when a simpler direct answer is more appropriate than the documented workflow.
## Required Inputs
- A clearly specified task goal aligned with the documented scope.
- All required files, identifiers, parameters, or environment variables before execution.
- Any domain constraints, formatting requirements, and expected output destination if applicable.
## Recommended Workflow
1. Validate the request against the skill boundary and confirm all required inputs are present.
2. Select the documented execution path and prefer the simplest supported command or procedure.
3. Produce the expected output using the documented file format, schema, or narrative structure.
4. Run a final validation pass for completeness, consistency, and safety before returning the result.
## Output Contract
- Return a structured deliverable that is directly usable without reformatting.
- If a file is produced, prefer a deterministic output name such as `research_paper_downloader_result.md` unless the skill documentation defines a better convention.
- Include a short validation summary describing what was checked, what assumptions were made, and any remaining limitations.
## Validation and Safety Rules
- Validate required inputs before execution and stop early when mandatory fields or files are missing.
- Do not fabricate measurements, references, findings, or conclusions that are not supported by the provided source material.
- Emit a clear warning when credentials, privacy constraints, safety boundaries, or unsupported requests affect the result.
- Keep the output safe, reproducible, and within the documented scope at all times.
## Failure Handling
- If validation fails, explain the exact missing field, file, or parameter and show the minimum fix required.
- If an external dependency or script fails, surface the command path, likely cause, and the next recovery step.
- If partial output is returned, label it clearly and identify which checks could not be completed.
## Quick Validation
Run this minimal verification path before full execution when possible:
```bash
python scripts/download.py --help
```
Expected output format:
```text
Result file: research_paper_downloader_result.md
Validation summary: PASS/FAIL with brief notes
Assumptions: explicit list if any
```Related Skills
two-sample-mr-research-planner
Generates complete two-sample Mendelian randomization (MR) research designs from a user-provided research direction. Use when users want to design, plan, or build a study using two-sample MR to test causal relationships. Triggers:"design a two-sample MR study", "build a publishable MR paper", "test whether this biomarker causally affects this disease", "generate Lite/Standard/Advanced MR plans", "screen multiple exposures with MR", "bidirectional MR design", "causal inference using GWAS summary statistics", or "I want to study X and Y using MR". Always outputs four workload configurations (Lite / Standard / Advanced / Publication+) with a recommended primary plan, step-by-step workflow, figure plan, validation strategy, minimal executable version, and publication upgrade path.
research-proposal-generator
Generates a comprehensive research proposal design based on input literature, including hypothesis, mechanism verification, and budget. Use when the user wants to design a research project from a paper.
research-grants
Write competitive research proposals for NSF, NIH, DOE, DARPA, and Taiwan's NSTC when you need agency-compliant narratives, budgets, and review-criteria alignment for a specific solicitation/FOA/BAA.
non-tumor-ml-research-planner
Generates complete non-tumor biomedical machine learning research designs from a user-provided research direction. Always use this skill when users want to plan bioinformatics + ML papers for non-cancer diseases (metabolic, cardiovascular, kidney, inflammatory, autoimmune, infectious, neurological, endocrine, wound healing, chronic multifactor), design diagnostic biomarker studies, combine GEO datasets with feature selection and ML modeling, or generate Lite/Standard/Advanced/Publication+ workload plans. Trigger for:"non-tumor ML study", "bioinformatics paper outside oncology", "key genes and diagnostic model for a disease", "pyroptosis/ferroptosis/senescence/autophagy + disease", "GEO datasets + machine learning", "RF + LASSO diagnostic model", "DEG + feature selection + validation", "immune infiltration + biomarker", "non-cancer biomarker paper". Trigger even for casual phrasings like "I want to study X using machine learning", "help me design a non-tumor bioinformatics paper", or "how do I build a diagnostic model for disease Y".
network-tox-docking-research-planner
Generates complete network toxicology + molecular docking research designs from a user-provided toxicant and disease/phenotype. Always use this skill when users want to investigate how an environmental toxicant, endocrine disruptor, heavy metal, food contaminant, pharmaceutical residue, or consumer product chemical may contribute to a disease through shared molecular targets, hub genes, pathways, and docking evidence. Trigger for:"network toxicology study", "toxicology mechanism paper", "target prediction + PPI + docking", "environmental pollutant and disease mechanism", "hub genes and docking for toxicant", "Lite/Standard/Advanced toxicology plan", "CTD + SwissTargetPrediction + GeneCards + STRING", "CB-Dock2 docking study", "triclosan/BPA/cadmium/PFAS + disease". Also triggers for Chinese phrasings:"网络毒理学研究设计"、"毒物机制论文"、"靶点预测+PPI+对接"、"环境污染物与疾病机制". Trigger even for casual phrasings like "I want to study how chemical X affects disease Y" or "help me design a toxicology paper". Always output four workload configurations (Lite / Standard / Advanced / Publication+) with a recommended primary plan, step-by-step workflow, figure plan, validation strategy, minimal executable version, and publication upgrade path.
clinic-research-design
Generates a structured prompt framework for clinical study protocols. Supports Diagnostic, Efficacy, Etiology, and Prognosis studies. Calculates sample size and provides logic guides for LLMs.
basic-research-design
A biomedical research topic designer that generates progressive experimental subtitles and detailed research outlines based on a given subject. Use when the user wants to design a research proposal, outline experiments for a topic, or structure a biomedical study.
sci-paper-reviewer
Simulates a strict SCI peer-review workflow; trigger when a user uploads or pastes a manuscript (PDF/DOC/DOCX/TXT) and requests an innovation score (1–12) plus experimental-logic vulnerability checks and revision suggestions.
paper-tweet-generator
Generates a structured reading tweet from an academic paper (PDF, Word, or Text), highlighting specific product advantages. Use when the user wants to turn a document into a social media post or reading summary.
market-research-report-generator
Generates professional market research reports by analyzing business intent, decision levels, and conducting multi-source data retrieval (Web, PubMed, Clinical Trials).
research-hotspot-analysis
Analyzes research hotspots and recommends literature based on a disease or topic. Use when the user wants to identify current research trends, hot topics, or get literature recommendations for a specific medical field or disease.
research-article-weekly
Generates a weekly academic literature report based on keywords using PubMed. Use when the user wants to track recent research progress on a specific topic, automatically retrieving, classifying, and summarizing relevant papers from the last 7 days.