Install
$ agentstack add skill-bigbio-sdrf-skills-sdrf-review ✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
About
SDRF Review Workflow
You are performing a comprehensive quality review of an SDRF file — like a peer reviewer would for a PRIDE submission or a community annotation PR.
Step 1: Load Context
- Read the SDRF content
- Detect templates from metadata or content
- If PXD available → fetch project context + publication:
``text mcp PRIDE → get_project_details(project_accession="PXD######") Extract PMID → mcp PubMed → get_article_metadata([pmid]) ``
- If GitHub PR → read the diff to understand what changed
Step 2: Run Full Validation (sdrf-validate workflow)
Apply the complete validation checklist from the sdrf-validate skill. Read spec/sdrf-proteomics/TERMS.tsv for column definitions and spec/sdrf-proteomics/sdrf-templates/templates.yaml for template metadata. Collect all errors and warnings.
Step 3: Cross-Reference with Publication
If a publication is available:
- Does the sample count in SDRF match the paper?
- Are all conditions from the paper represented?
- Do the instruments match?
- Are demographics (age, sex) consistent with the paper?
- Is
characteristics[developmental stage]supported by the cohort description even if age is reported only at group level? - Are tissue types correctly annotated?
When Europe PMC full text is available, do not inspect raw XML directly. First run: python scripts/europepmc_fulltext.py PMC_ID --section methods --section results --section discussion --format text or use --format json when structured links, captions, or accession detection will help the review.
Flag any discrepancies:
DISCREPANCY: Paper says "24 patients" but SDRF has 20 unique source names.
DISCREPANCY: Paper mentions "hippocampus and temporal cortex" but SDRF only has "brain".
For technical metadata (instrument, tolerances, modifications, DDA/DIA), consider recommending /sdrf:techrefine — techsdrf can verify these parameters directly from the raw MS files, which is more reliable than cross-referencing with the publication.
Conflict Resolution
When SDRF and paper/PRIDE disagree:
- Sample count mismatch: Check if some samples were excluded (QC failure, outliers). Paper may report enrolled patients while SDRF has analyzable samples. Check supplementary tables.
- Instrument mismatch: PRIDE might say "Q Exactive" while paper says "Q Exactive HF". The paper is usually more specific — update SDRF to match the paper's instrument model.
- Tissue specificity: If paper says "hippocampus" but SDRF says "brain", update SDRF to the more specific term from the paper.
- Demographic mismatch: If paper has a demographics table, prioritize it. SDRF might have been filled from incomplete metadata.
- Cohort-only demographics: If the paper reports only cohort summaries,
developmental stagemay still be supportable, but do not force per-sampleage,sex, orethnicitywithout an individual-level mapping table. - File count mismatch: Some files in PRIDE may be non-raw (search results, FASTA, etc.). Compare only raw files.
Step 4: Cross-Reference with PRIDE
If a PXD accession is available:
- Do file names in SDRF match files in PRIDE?
``text mcp PRIDE → get_project_files(project_accession="PXD######") ` REST fallback: `text GET https://www.ebi.ac.uk/pride/ws/archive/v3/projects/PXD######/files/all ``
- Does the organism match?
- Does the instrument match?
- Are all raw files accounted for?
If PRIDE exposes no raw files and the dataset is hosted by MassIVE, use the deterministic helper:
python -m tools massive-files PXD016117 --mode raw --format tsv
Treat this as a fallback for reconstructing defensible comment[data file] values when the repository metadata is incomplete.
Step 5: Design Analysis
Analyze the experimental design:
- Are factor values properly defined?
- Is the comparison clear?
- Are replicates adequate?
- Are there potential batch effects? (instrument × condition confounding)
- Are there confounders? (age × disease, sex × treatment)
Step 6: Quality Score
Calculate and present an overall quality score:
# SDRF Quality Review: PXD012345
# Date: [date]
# Templates: ms-proteomics, human, clinical-metadata
## Quality Score: 78/100
### Breakdown:
Completeness: 85/100 ████████░░
Specificity: 70/100 ███████░░░
Consistency: 90/100 █████████░
Standards: 65/100 ██████░░░░
Design Clarity: 80/100 ████████░░
### Errors Found: 3
1. [ERROR] Row 12: UNIMOD:21 used for Acetyl (should be UNIMOD:1)
2. [ERROR] Missing required column: characteristics[biological replicate]
3. [ERROR] "cancer" is too generic — specify cancer subtype
### Warnings: 5
1. [WARN] Case inconsistency in characteristics[sex]: "Male" vs "male"
2. [WARN] Not using latest template version (v1.0.0 → v1.1.0 available)
3. [WARN] Missing recommended column: characteristics[cell type]
4. [WARN] Age format "58 years" should be "58Y"
5. [WARN] Missing SDRF metadata columns (comment[sdrf version])
### Improvements Suggested: 3
1. [IMPROVE] Disease term could be more specific (EFO:0000311 "cancer" → EFO:0000305 "breast carcinoma")
2. [IMPROVE] Add characteristics[developmental stage] — 80% of human studies include it
3. [IMPROVE] Consider adding comment[sdrf annotation tool] for provenance
### Cross-Reference:
Publication match: ✓ Sample count matches paper
PRIDE file match: ✓ All 240 raw files present
Instrument match: ✓ Q Exactive HF confirmed
### Verdict: NEEDS MINOR FIXES
Fix the 3 errors and this SDRF is ready for submission.
Step 7: Actionable Next Steps
Provide clear next steps:
- List fixes in priority order
- Offer to auto-fix what can be auto-fixed (
/sdrf:fix) - Identify what needs human input (e.g., missing demographics)
- Suggest running final validation after fixes
- If the SDRF is for a ProteomeXchange dataset and the verdict is VALID or NEEDS MINOR FIXES:
suggest contributing the annotation via /sdrf:contribute {PXD} to the sdrf-annotated-datasets community repository
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: bigbio
- Source: bigbio/sdrf-skills
- License: MIT
- Homepage: https://sdrf.quantms.org
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.