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tooluniverse-target-research

Comprehensive drug-target intelligence — tissue expression (GTEx, HPA), pathways, protein interactions (STRING), variant landscape (ClinVar, gnomAD), druggability (DGIdb, ChEMBL approved drugs). 9 parallel research paths with citations. Use for full target profile reports, target characterization for drug discovery, and 'tell me about target X' queries.

plugin/skills/tooluniverse-target-research/SKILL.md

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Repository stars (not skill ratings): 1,779
Repository last updated: Nov 8, 2026
License: Apache-2.0

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EVIDENCE_GRADING.mddoc · 4,872 bytes
EXAMPLES.mddoc · 22,310 bytes
IMPLEMENTATION.mddoc · 24,756 bytes
REFERENCE.mddoc · 30,410 bytes
REPORT_FORMAT.mddoc · 19,045 bytes
SKILL.mdcore · 19,234 bytes
SKILL.mdcore · 19,234 bytes
SKILL.mdcore · 19,234 bytes
SKILL.mdcore · 19,234 bytes

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# Comprehensive Target Intelligence Gatherer

Gather complete target intelligence by exploring 9 parallel research paths. Supports targets identified by gene symbol, UniProt accession, Ensembl ID, or gene name.

**KEY PRINCIPLES**:
1. **Report-first approach** - Create report file FIRST, then populate progressively
2. **Tool parameter verification** - Verify params via `get_tool_info` before calling unfamiliar tools
3. **Evidence grading** - Grade all claims by evidence strength (T1-T4)
4. **Citation requirements** - Every fact must have inline source attribution
5. **Mandatory completeness** - All sections must exist with data minimums or explicit "No data" notes
6. **Disambiguation first** - Resolve all identifiers before research
7. **Negative results documented** - "No drugs found" is data; empty sections are failures
8. **Collision-aware literature search** - Detect and filter naming collisions
9. **English-first queries** - Always use English terms in tool calls, even if the user writes in another language. Translate gene names, disease names, and search terms to English. Only try original-language terms as a fallback if English returns no results. Respond in the user's language