Data & ReproProtein Structure & DesignFreedomIntelligence/OpenClaw-Medical-SkillsData & Reproduction

tooluniverse-target-research

Maintainer FreedomIntelligence · Last updated April 1, 2026

Gather comprehensive biological target intelligence from 9 parallel research paths covering protein info, structure, interactions, pathways, expression, variants, drug interactions, and literature. Features collision-aware searches, evidence grading (T1-T4), explicit Open Targets coverage, and mandatory completeness auditing. Use when users ask about drug targets, proteins, genes, or need target validation, druggabi….

OpenClawNanoClawAnalysisReproductiontooluniverse-target-research🏥 medical & clinicalmedical toolsgather

Original source

FreedomIntelligence/OpenClaw-Medical-Skills

https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/tooluniverse-target-research

Maintainer: FreedomIntelligence
License: MIT
Last updated: April 1, 2026

Skill Snapshot

Key Details From SKILL.md

2 min

Key Notes

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.
tool_info = tu.tools.get_tool_info(tool_name="Reactome_map_uniprot_to_pathways").

Source Doc

Excerpt From SKILL.md

Phase 0: Tool Parameter Verification (CRITICAL)

BEFORE calling ANY tool for the first time, verify its parameters:


## Known Parameter Corrections (Updated)

| Tool | WRONG Parameter | CORRECT Parameter |
|------|-----------------|-------------------|
| `Reactome_map_uniprot_to_pathways` | `uniprot_id` | `id` |
| `ensembl_get_xrefs` | `gene_id` | `id` |
| `GTEx_get_median_gene_expression` | `gencode_id` only | `gencode_id` + `operation="median"` |
| `OpenTargets_*` | `ensemblID` | `ensemblId` (camelCase) |

## GTEx Versioned ID Fallback (CRITICAL)

GTEx often requires versioned Ensembl IDs. If `ENSG00000123456` returns empty:

```python