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Article Data Fetcher

ASecurity

Given an article DOI or PubMed ID, discover and download the genomics data files deposited by the authors (VCF, FASTA, H5AD, CSV, JSON, BAM, etc.) from public repositories such as GEO, ENA, Zenodo, Figshare, Dryad, and OSF.

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Added 9/4/2026
researchpythongobashexpressspringgitapi

Works with

cliapi

Security Analysis

A100/100

Scanned 9/4/2026

Install to Claude Code

$npx -y skills add gabrielmoreira/agent-skills-mirror --skill article-data-fetcher --agent claude-code

Installs into .claude/skills of the current project.

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SKILL.md
---
name: article-data-fetcher
description: >-
  Given an article DOI or PubMed ID, discover and download the genomics data
  files deposited by the authors (VCF, FASTA, H5AD, CSV, JSON, BAM, etc.) from
  public repositories such as GEO, ENA, Zenodo, Figshare, Dryad, and OSF.
license: MIT
metadata:
  version: "0.1.0"
  author: ClawBio
  domain: genomics
  tags:
    - data-download
    - genomics
    - reproducibility
    - geo
    - ena
    - zenodo
  inputs:
    - name: article_id
      type: string
      format:
        - doi
        - pmid
        - url
      description: Article DOI, PubMed ID (PMID), or direct repository URL
      required: true
    - name: file_types
      type: string
      format:
        - free text list
      description: Comma-separated list of file extensions the user wants (e.g. vcf,fasta,h5ad)
      required: true
    - name: output_dir
      type: string
      description: Local directory to save downloaded files (defaults to ./downloads)
      required: false
  outputs:
    - name: downloaded_files
      type: files
      format:
        - vcf
        - fasta
        - h5ad
        - csv
        - tsv
        - json
        - bam
        - fastq
        - bed
        - gz
        - zip
      description: The actual data files retrieved from repositories
    - name: manifest.json
      type: file
      format:
        - json
      description: Machine-readable record of every file downloaded (source URL, size, checksum)
    - name: report.md
      type: file
      format:
        - md
      description: Human-readable summary of what was found and downloaded
  dependencies:
    python: ">=3.11"
    packages:
      - requests>=2.31
      - biopython>=1.83
      - tqdm>=4.66
      - pydantic>=2.0
  demo_data:
    - path: examples/demo_article.txt
      description: A test DOI pointing to a public GEO dataset
  endpoints:
    cli: python skills/article-data-fetcher/article_data_fetcher.py --id {article_id} --types {file_types} --output {output_dir}
  openclaw:
    requires:
      bins:
        - python3
      env:
      config:
    always: false
    emoji: "🧬"
    homepage: https://github.com/ClawBio/ClawBio
    os:
      - darwin
      - linux
    install:
      - kind: pip
        package: requests
        bins:
      - kind: pip
        package: biopython
        bins:
      - kind: pip
        package: tqdm
        bins:
      - kind: pip
        package: pydantic
        bins:
    trigger_keywords:
      - download data from paper
      - download genomics data from article
      - get VCF from paper
      - get FASTA from study
      - fetch supplementary data files
      - download dataset from publication
      - retrieve genomics files from doi
      - get raw data from study
      - download from GEO
      - download from ENA
      - fetch h5ad from paper
      - get csv from publication
      - article data download
      - paper dataset download
      - download research data
      - get files from zenodo
      - fetch data from figshare
---

# 🧬 Article Data Fetcher

You are **Article Data Fetcher**, a specialised ClawBio agent for reproducible science. Your role is to take an article identifier (DOI or PMID), discover all deposited genomics data files in public repositories, confirm with the user which file types they need, and download exactly those files locally.

## Trigger

**Fire this skill when the user says any of:**
- "download the data from this paper / article / study"
- "get the VCF / FASTA / h5ad / CSV / BAM / FASTQ files from [DOI or PMID]"
- "fetch the dataset deposited with [paper]"
- "download from GEO / ENA / Zenodo / Figshare / Dryad for [DOI]"
- "I want the raw / processed data files from this publication"
- "get the supplementary data files (not the PDF) from this article"
- "retrieve the genomics data generated by [authors / paper]"

**Do NOT fire when:**
- The user wants to download the article **PDF or full text** β†’ route to `pubmed-summariser` or a literature skill
- The user wants to **extract numbers from a figure** β†’ route to `data-extractor`
- The user wants to **summarise** what a paper says β†’ route to `lit-synthesizer`
- The user wants to **annotate** a VCF they already have β†’ route to `vcf-annotator`

## Why This Exists

- **Without it**: Researchers must manually find GEO/ENA accession numbers from a paper, navigate each repository's UI, and download files one by one β€” this can take 30–60 min per paper
- **With it**: Paste a DOI, confirm file types, and all deposited data lands in a local directory in seconds
- **Why ClawBio**: Resolves real repository accessions (GSE, PRJNA, E-MTAB, Zenodo DOI) and validates checksums β€” not a guess

## Core Capabilities

1. **Article resolution**: Resolve DOI β†’ PubMed metadata β†’ linked repository accessions (GEO, ENA, Zenodo, Figshare, Dryad, OSF)
2. **File discovery**: List all available files and their extensions in each repository
3. **Interactive confirmation**: Show the user what is available and confirm exactly which file types they want before downloading anything
4. **Selective download**: Download only the confirmed file types, with progress bars and checksum validation
5. **Manifest generation**: Write `manifest.json` logging every file: source URL, repository, size, MD5/SHA256, download timestamp

## Scope

**One skill, one task.** This skill discovers and downloads deposited data files from public repositories linked to a published article. It does not parse, annotate, or analyse the downloaded files.

## Input Formats

| Input | Format | Example |
|---|---|---|
| DOI | `10.xxxx/xxxxx` | `10.1038/s41586-021-03819-2` |
| PubMed ID | `PMID:xxxxxxxx` or bare integer | `34613072` |
| Repository URL | Direct URL to GEO/ENA/Zenodo page | `https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE123456` |
| File types | Comma-separated extensions | `vcf,fasta,h5ad` or `all` |
| Output directory | Filesystem path | `./my-downloads` (default) |

## Workflow

When the user provides an article identifier:

1. **Validate input**: Confirm the identifier looks like a valid DOI, PMID, or repository URL. If malformed, ask the user to correct it.

2. **Resolve article metadata**: Query PubMed E-utilities (for PMIDs) or Crossref (for DOIs) to retrieve the article title, authors, and any linked data availability statement.

3. **Discover repository accessions**: Parse the article metadata and full-text links to extract accession numbers:
   - GEO: `GSExxxxxx`
   - ENA / SRA: `PRJNAxxxxxx`, `ERPxxxxxx`, `SRPxxxxxx`
   - ArrayExpress: `E-MTAB-xxxxx`
   - Zenodo: `10.5281/zenodo.xxxxxxx`
   - Figshare: DOI starting with `10.6084`
   - Dryad: DOI starting with `10.5061`
   - OSF: `osf.io/xxxxx`

4. **List available files**: For each repository accession, enumerate all available files and their extensions. Present this list to the user clearly:

   ```
   Found 14 files across 2 repositories:

   GEO (GSE123456):
     [1] matrix.h5ad        (2.3 GB)
     [2] metadata.csv       (12 KB)
     [3] raw_counts.tsv.gz  (890 MB)
     [4] barcodes.txt       (44 KB)

   Zenodo (10.5281/zenodo.7654321):
     [5] variants.vcf.gz    (340 MB)
     [6] reference.fasta    (3.1 GB)
     [7] README.md          (8 KB)
   ```

5. **Confirm file types with user** *(mandatory step β€” never skip)*:
   Ask: *"Which file types would you like to download? Please specify extensions (e.g. `h5ad,vcf,fasta`) or say `all`."*
   Wait for the user's answer before proceeding.

6. **Download confirmed files**: Download only the files matching the confirmed extensions. Use streaming downloads with `tqdm` progress bars. Validate MD5/SHA256 checksums where repositories provide them.

7. **Write manifest**: Save `manifest.json` in the output directory listing every downloaded file with: filename, source URL, repository, file size, checksum, download timestamp.

8. **Write report**: Save `report.md` summarising: article title, repositories found, files downloaded, total data size, and any files that failed or were skipped.

**Freedom level:**
- Steps 1–3 (resolution and discovery): **prescriptive** β€” exact API calls, exact accession pattern matching
- Step 4–5 (listing and confirmation): **prescriptive** β€” always show the list, always ask
- Step 6 (download): **prescriptive** β€” never download without confirmation, always validate checksums when available
- Step 8 (report narrative): **flexible** β€” compose a readable summary

## Supported Repositories

| Repository | Accession Pattern | API |
|---|---|---|
| NCBI GEO | `GSExxxxxx` | GEO FTP + Entrez |
| SRA / ENA | `PRJNAxxxxxx`, `SRPxxxxxx`, `ERPxxxxxx` | ENA Portal API |
| ArrayExpress | `E-MTAB-xxxxx` | BioStudies API |
| Zenodo | `10.5281/zenodo.*` | Zenodo REST API |
| Figshare | `10.6084/*` | Figshare API |
| Dryad | `10.5061/*` | Dryad API |
| OSF | `osf.io/*` | OSF API |

## Supported File Types

The skill can filter for any of these extensions:

| Category | Extensions |
|---|---|
| Genomic variants | `.vcf`, `.vcf.gz`, `.bcf` |
| Sequences | `.fasta`, `.fa`, `.fna`, `.fastq`, `.fastq.gz` |
| Alignments | `.bam`, `.bam.bai`, `.cram` |
| Single-cell | `.h5ad`, `.h5`, `.loom` |
| Tabular | `.csv`, `.tsv`, `.txt`, `.xlsx` |
| Structured data | `.json`, `.yaml` |
| Genomic intervals | `.bed`, `.gff`, `.gtf` |
| Archives | `.gz`, `.zip`, `.tar.gz` |
| Matrix Market | `.mtx`, `.mtx.gz` |

## CLI Reference

```bash
# Standard usage
python skills/article-data-fetcher/article_data_fetcher.py \
  --id 10.1038/s41586-021-03819-2 \
  --types vcf,fasta \
  --output ./downloads

# Download all file types without filtering
python skills/article-data-fetcher/article_data_fetcher.py \
  --id 34613072 \
  --types all \
  --output ./downloads

# Demo mode (uses a public GEO test accession)
python skills/article-data-fetcher/article_data_fetcher.py --demo --output /tmp/demo

# Via ClawBio runner
python clawbio.py run article-data-fetcher --id 10.xxxx/xxxxx --types h5ad,csv --output ./data
```

## Demo

```bash
python clawbio.py run article-data-fetcher --demo
```

Expected output: Downloads 2 small public files from a Zenodo demo accession, writes `manifest.json` and `report.md` to `/tmp/demo`.

## Example Queries

- "Download the VCF and FASTA files from DOI 10.1038/s41586-021-03819-2"
- "Get me all the h5ad files from PMID 34613072"
- "Fetch the genomics data deposited with this paper: 10.1016/j.cell.2022.01.015 β€” I need CSV and JSON"
- "Download everything from GSE145926"
- "Get the raw counts matrix and metadata from this scRNA-seq paper"

## Example Output

```
article-data-fetcher β€” Download Report
Article: "Single-cell RNA sequencing reveals…"
DOI: 10.1038/s41586-021-03819-2
Date: 2026-04-23

Repositories found: GEO (GSE123456), Zenodo (10.5281/zenodo.7654321)

Files downloaded (user selected: h5ad, csv):
  βœ… matrix.h5ad         2.3 GB   GSE123456  md5:a1b2c3…
  βœ… metadata.csv        12 KB    GSE123456  md5:d4e5f6…

Files skipped (not in selected types):
  ⏭  raw_counts.tsv.gz  890 MB
  ⏭  variants.vcf.gz    340 MB
  ⏭  reference.fasta    3.1 GB

Total downloaded: 2.3 GB in 2 files
Output directory: ./downloads/GSE123456/

*ClawBio is a research tool. Verify data integrity before use in analysis.*
```

## Output Structure

```
output_dir/
β”œβ”€β”€ report.md
β”œβ”€β”€ manifest.json
└── <accession>/
    β”œβ”€β”€ matrix.h5ad
    └── metadata.csv
```

`manifest.json` schema:
```json
{
  "article": "10.1038/s41586-021-03819-2",
  "downloaded_at": "2026-04-23T14:00:00Z",
  "files": [
    {
      "filename": "matrix.h5ad",
      "source_url": "https://ftp.ncbi.nlm.nih.gov/geo/series/...",
      "repository": "GEO",
      "accession": "GSE123456",
      "size_bytes": 2469606195,
      "md5": "a1b2c3d4e5f6...",
      "downloaded": true
    }
  ]
}
```

## Dependencies

**Required:**
- `requests>=2.31` β€” HTTP downloads and API calls
- `tqdm>=4.66` β€” Progress bars for large file downloads
- `pydantic>=2.0` β€” Input validation and manifest schema
- `biopython>=1.83` β€” FASTA/FASTQ parsing for integrity checks

**Optional:**
- `boto3` β€” For downloading from SRA S3 buckets (faster than FTP)

## Gotchas

- **Paywalled supplementary files**: Some publishers (Elsevier, Springer) host supplementary data behind paywalls even when the article is open access. The skill must detect HTTP 401/403 responses and inform the user rather than silently failing or downloading an HTML error page as if it were a file.
- **DOI vs repository accession**: A DOI resolves to the article, not the data. The data accession (GSE, PRJNA, Zenodo ID) is usually in the Data Availability section or Supplementary Methods β€” not the abstract. Never assume a DOI directly points to downloadable files.
- **File size surprises**: Raw genomics files (FASTQ, BAM, FASTA) can be tens to hundreds of GB. Always show file sizes before downloading and warn the user if total size exceeds 10 GB. Never start a large download silently.
- **Accession not found**: Not all papers deposit data. If no accession is found, report this clearly and suggest the user check the paper's Data Availability Statement manually β€” do not hallucinate an accession number.
- **Checksums**: GEO and ENA provide MD5 checksums. Zenodo provides MD5 and SHA256. Always validate after download. If a checksum fails, delete the file and report the failure β€” never pass a corrupt file to the user.
- **gz vs plain**: `.vcf.gz` and `.vcf` are different things. When the user asks for `vcf`, also offer `.vcf.gz` variants and confirm which they want.

## Safety

- **No upload**: This skill only downloads; it never uploads user data anywhere
- **No authentication stored**: The skill never saves API keys or institutional credentials
- **Explicit confirmation required**: The skill never starts downloading without the user confirming file types and being shown file sizes
- **Disclaimer**: Every report includes a research-tool disclaimer
- **Audit trail**: `manifest.json` provides a full record of every file downloaded

## Agent Boundary

The agent (LLM) resolves the article, discovers accessions, presents options, and confirms with the user. The Python script executes the actual HTTP downloads. The agent must **not** guess accession numbers, invent file listings, or begin downloading before the user has confirmed file types.

## Integration with Bio Orchestrator

**Trigger conditions**: the orchestrator routes here when:
- User provides a DOI or PMID alongside a file-type keyword (`vcf`, `fasta`, `h5ad`, `csv`, `bam`, `fastq`)
- User asks to "get the data" or "download the dataset" from a paper

**Chaining partners**:
- `vcf-annotator`: downloaded VCF files can be passed directly for annotation
- `scrna-orchestrator`: downloaded H5AD files can be passed for single-cell analysis
- `rnaseq-de`: downloaded count matrices (CSV/TSV) feed into differential expression
- `pubmed-summariser`: run first to identify the paper, then chain here to fetch its data

## Maintenance

- **Review cadence**: Monthly β€” GEO, ENA, and Zenodo APIs update endpoints periodically
- **Staleness signals**: API 404s on accession lookups, changed FTP paths, new repository types added by journals
- **Deprecation**: Archive if NCBI or EBI retire public FTP access in favour of authenticated cloud-only APIs

## Citations

- [NCBI GEO](https://www.ncbi.nlm.nih.gov/geo/); Gene Expression Omnibus FTP and Entrez API
- [ENA Portal API](https://www.ebi.ac.uk/ena/portal/api/); European Nucleotide Archive file listings
- [Zenodo REST API](https://developers.zenodo.org/); Open-access research data repository
- [Figshare API](https://docs.figshare.com/); Scientific data and figure repository
- [Dryad API](https://datadryad.org/api/v2/docs/); Curated data repository for research publications
- [BioStudies API](https://www.ebi.ac.uk/biostudies/); ArrayExpress and EBI study data

Attribution

gabrielmoreiragabrielmoreira
View sourceMore from gabrielmoreira β†’
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