General
tooluniverse-disease-research - Claude MCP Skill
Generate comprehensive disease research reports using 100+ ToolUniverse tools. Creates a detailed markdown report file and progressively updates it with findings from 10 research dimensions. All information includes source references. Use when users ask about diseases, syndromes, or need systematic disease analysis.
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Documentation
SKILL.md# ToolUniverse Disease Research
Generate a comprehensive disease research report with full source citations. The report is created as a markdown file and progressively updated during research.
**IMPORTANT**: Always use English disease names and search terms in tool calls. Respond in the user's language.
---
## LOOK UP, DON'T GUESS
When asked about a disease, query Orphanet/OMIM/DisGeNET FIRST. Don't rely on memory for prevalence, genetics, or treatment — these change over time. When you're not sure about a fact, your first instinct should be to SEARCH for it using tools, not to reason harder from memory.
---
## When to Use
- User asks about any disease, syndrome, or medical condition
- Needs comprehensive disease intelligence or a detailed research report
- Asks "what do we know about [disease]?"
---
## Core Workflow: Report-First Approach
**DO NOT** show the search process to the user. Instead:
1. **Create report file first** - Initialize `{disease_name}_research_report.md`
2. **Research each dimension** - Use all relevant tools
3. **Update report progressively** - Write findings after each dimension
4. **Include citations** - Every fact must reference its source tool
---
## Disease Mechanism Reasoning
When synthesizing disease etiology, trace the full pathogenic cascade:
1. **Genetic basis** - Which variants (rare or common) confer risk, and in which genes?
2. **Molecular mechanism** - How do those variants alter protein function, expression, or regulation?
3. **Cellular effect** - What downstream cellular processes are disrupted (signaling, metabolism, stress response)?
4. **Tissue/organ manifestation** - How does cellular dysfunction present as organ-level pathology?
This chain structures the Genetic & Molecular Basis (Section 3) and Biological Pathways (Section 5) sections.
---
## 10 Research Dimensions
| Dim | Section | Key Tools |
|-----|---------|-----------|
| 1 | Identity & Classification | OSL_get_efo_id_by_disease_name, ols_search_efo_terms, ols_get_efo_term, umls_search_concepts, icd_search_codes, snomed_search_concepts |
| 2 | Clinical Presentation | OpenTargets phenotypes, HPO lookup, MedlinePlus |
| 3 | Genetic & Molecular Basis | OpenTargets targets, ClinVar variants, GWAS associations, gnomAD |
| 4 | Treatment Landscape | OpenTargets drugs, clinical trials, GtoPdb |
| 5 | Biological Pathways | Reactome pathways, humanbase_ppi_analysis, GTEx expression, HPA |
| 6 | Epidemiology & Literature | PubMed, OpenAlex, Europe PMC, Semantic Scholar |
| 7 | Similar Diseases | OpenTargets similar entities |
| 8 | Cancer-Specific (if applicable) | CIViC genes/variants/therapies |
| 9 | Pharmacology | GtoPdb targets/interactions/ligands |
| 10 | Drug Safety | OpenTargets warnings, clinical trial AEs, FAERS |
See: tool_usage_details.md for complete tool calls per section.
---
## Report Template
Create this file structure at the start:
```markdown
# Disease Research Report: {Disease Name}
**Report Generated**: {date}
**Disease Identifiers**: (to be filled)
---
## Executive Summary
(Brief 3-5 sentence overview - fill after all research complete)
---
## 1. Disease Identity & Classification
### Ontology Identifiers
| System | ID | Source |
### Synonyms & Alternative Names
### Disease Hierarchy
---
## 2. Clinical Presentation
### Phenotypes (HPO)
| HPO ID | Phenotype | Description | Source |
### Symptoms & Signs
### Diagnostic Criteria
---
## 3. Genetic & Molecular Basis
### Associated Genes
| Gene | Score | Ensembl ID | Evidence | Source |
### GWAS Associations
| SNP | P-value | Odds Ratio | Study | Source |
### Pathogenic Variants (ClinVar)
---
## 4. Treatment Landscape
### Approved Drugs
| Drug | ChEMBL ID | Mechanism | Phase | Target | Source |
### Clinical Trials
| NCT ID | Title | Phase | Status | Source |
---
## 5. Biological Pathways & Mechanisms
## 6. Epidemiology & Risk Factors
## 7. Literature & Research Activity
## 8. Similar Diseases & Comorbidities
## 9. Cancer-Specific Information (if applicable)
## 10. Drug Safety & Adverse Events
---
## References
### Tools Used
| # | Tool | Parameters | Section | Items Retrieved |
```
---
## Citation Format
Every piece of data MUST include its source:
**In tables**: Add a `Source` column with tool name
**In lists**: `- Finding [Source: tool_name]`
**In prose**: `(Source: tool_name, query: "...")`
**References section**: Complete tool usage log with parameters
---
## Progressive Update Pattern
```python
# After each dimension's research:
# 1. Read current report
# 2. Replace placeholder with formatted content
# 3. Write back immediately
# 4. Continue to next dimension
```
---
## Evidence Grading & Interpretation
Every finding in the report should be graded:
| Grade | Criteria | Example |
|-------|---------|---------|
| **T1 (Strong)** | Replicated genetic evidence (GWAS, rare variants), FDA-approved therapy | BRCA1 → breast cancer; trastuzumab for HER2+ |
| **T2 (Moderate)** | Single genetic study, phase II+ trial data, strong biological evidence | FOXO3 → longevity (centenarian studies) |
| **T3 (Association)** | Observational data, gene expression changes, pathway membership | IL-6 elevated in Alzheimer's CSF |
| **T4 (Computational)** | Network proximity, text mining, predicted associations | DisGeNET text-mined gene-disease link |
### Synthesis Questions (answer in Executive Summary)
After collecting data from all 10 dimensions, the report MUST answer:
1. **What causes this disease?** Summarize the genetic architecture (monogenic vs polygenic, key loci, penetrance)
2. **What are the therapeutic options?** Ranked by evidence level and approval status
3. **What biomarkers exist?** For diagnosis, prognosis, and treatment selection
4. **What's the unmet need?** What aspects lack effective treatment or understanding?
5. **What are the active research frontiers?** Based on clinical trials and recent publications
### Interpreting Cross-Database Concordance
When multiple databases provide different data for the same disease:
- **OpenTargets + DisGeNET + OMIM agree on a gene**: T1 evidence — high confidence
- **Only OpenTargets reports an association**: Check the datasource scores — genetic_association > literature > animal_model
- **DisGeNET score > 0.5 but not in OpenTargets**: May be text-mined; verify with PubMed
- **Gene in GWAS but not OMIM**: Likely a complex disease susceptibility locus, not Mendelian
### Handling Conflicting Data
| Conflict | Resolution |
|----------|-----------|
| Different prevalence estimates across sources | Report range; note the most recent/largest study |
| Drug approved in one country but not another | Note regulatory status per region |
| Gene-disease association in one DB but absent in another | Grade by evidence type; text-mining alone is T4 |
| Clinical trial results contradict label indications | The trial result is newer evidence; note both |
---
## Final Report Quality Checklist
- [ ] All 10 sections have content (or marked "No data available")
- [ ] Every data point has a source citation
- [ ] Executive summary reflects key findings
- [ ] References section lists all tools used
- [ ] Tables properly formatted
- [ ] No placeholder text remains
---
## Expected Output Scale
For a well-studied disease (e.g., Alzheimer's), the final report should include:
- 5+ ontology IDs, 10+ synonyms, disease hierarchy
- 20+ phenotypes with HPO IDs
- 50+ genes, 30+ GWAS associations, 100+ ClinVar variants
- 20+ drugs, 50+ clinical trials
- 10+ pathways, PPI network, expression data
- 100+ publications
- 15+ similar diseases
- Drug warnings and adverse events
Total: 500+ individual data points, each with source citation.
---
## Cross-Skill References
For rare disease differential diagnosis, run: `python3 skills/tooluniverse-rare-disease-diagnosis/scripts/clinical_patterns.py --type differential --symptoms 'symptom1,symptom2'`
---
## Reference Files
- **[REPORT_TEMPLATE.md](REPORT_TEMPLATE.md)** - Full report markdown template and citation format guide
- **[RESEARCH_PROTOCOL.md](RESEARCH_PROTOCOL.md)** - Step-by-step code procedures, progressive update pattern, quality checklist
- **[tool_usage_details.md](tool_usage_details.md)** - Complete tool calls for each research dimension
- **[TOOLS_REFERENCE.md](TOOLS_REFERENCE.md)** - Complete tool documentation
- **[EXAMPLES.md](EXAMPLES.md)** - Sample disease research reportsSignals
Information
- Repository
- mims-harvard/ToolUniverse
- Author
- mims-harvard
- Last Sync
- 5/10/2026
- Repo Updated
- 5/10/2026
- Created
- 2/4/2026
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