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Search biomedical literature, clinical trials, genetic variants, genes, drugs, and diseases using a unified query language or domain-specific filters. Access data from PubMed/PubTator3, ClinicalTrials.gov, MyVariant.info, and BioThings suite for precise research insights.

Instructions

Search biomedical literature, clinical trials, genetic variants, genes, drugs, and diseases.

⚠️ IMPORTANT: Have you used the 'think' tool first? If not, STOP and use it NOW!
The 'think' tool is REQUIRED for proper research planning and should be your FIRST step.

This tool provides access to biomedical data from PubMed/PubTator3, ClinicalTrials.gov,
MyVariant.info, and the BioThings suite (MyGene.info, MyChem.info, MyDisease.info).
It supports two search modes:

## 1. UNIFIED QUERY LANGUAGE
Use the 'query' parameter with field-based syntax for precise cross-domain searches.

Syntax:
- Basic: "gene:BRAF"
- AND logic: "gene:BRAF AND disease:melanoma"
- OR logic: "gene:PTEN AND (R173 OR Arg173 OR 'position 173')"
- Domain-specific: "trials.condition:melanoma AND trials.phase:3"

Common fields:
- Cross-domain: gene, disease, variant, chemical/drug
- Articles: pmid, title, abstract, journal, author
- Trials: trials.condition, trials.intervention, trials.phase, trials.status
- Variants: variants.hgvs, variants.rsid, variants.significance

Example:
```
await search(
    query="gene:BRAF AND disease:melanoma AND trials.phase:3",
    max_results_per_domain=20
)
```

## 2. DOMAIN-SPECIFIC SEARCH
Use the 'domain' parameter with specific filters for targeted searches.

Domains:
- "article": Search PubMed/PubTator3 for research articles and preprints ABOUT genes, variants, diseases, or chemicals
- "trial": Search ClinicalTrials.gov for clinical studies
- "variant": Search MyVariant.info for genetic variant DATABASE RECORDS (population frequency, clinical significance, etc.) - NOT for articles about variants!
- "gene": Search MyGene.info for gene information (symbol, name, function, aliases)
- "drug": Search MyChem.info for drug/chemical information (names, formulas, indications)
- "disease": Search MyDisease.info for disease information (names, definitions, synonyms)
- "nci_organization": Search NCI database for cancer centers, hospitals, and research sponsors (requires API key)
- "nci_intervention": Search NCI database for drugs, devices, procedures used in cancer trials (requires API key)
- "nci_biomarker": Search NCI database for biomarkers used in trial eligibility criteria (requires API key)
- "nci_disease": Search NCI controlled vocabulary for cancer conditions and terms (requires API key)

Example:
```
await search(
    domain="article",
    genes=["BRAF", "NRAS"],
    diseases=["melanoma"],
    page_size=50
)
```

## DOMAIN SELECTION EXAMPLES:
- To find ARTICLES about BRAF V600E mutation: domain="article", genes=["BRAF"], variants=["V600E"]
- To find VARIANT DATA for BRAF mutations: domain="variant", gene="BRAF"
- To find articles about ERBB2 p.D277Y: domain="article", genes=["ERBB2"], variants=["p.D277Y"]
- Common mistake: Using domain="variant" when you want articles about a variant

## IMPORTANT NOTES:
- For complex research questions, use the separate 'think' tool for systematic analysis
- The tool returns results in OpenAI MCP format: {"results": [{"id", "title", "text", "url"}, ...]}
- Search results do NOT include metadata (per OpenAI MCP specification)
- Use the fetch tool to get detailed metadata for specific records
- Use get_schema=True to explore available search fields
- Use explain_query=True to understand query parsing (unified mode)
- Domain-specific searches use AND logic for multiple values
- For OR logic, use the unified query language
- NEW: Article search keywords support OR with pipe separator: "R173|Arg173|p.R173"
- Remember: domain="article" finds LITERATURE, domain="variant" finds DATABASE RECORDS

## RETURN FORMAT:
All search modes return results in this format:
```json
{
    "results": [
        {
            "id": "unique_identifier",
            "title": "Human-readable title",
            "text": "Summary or snippet of content",
            "url": "Link to full resource"
        }
    ]
}
```

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
api_keyNoNCI API key for searching NCI domains (nci_organization, nci_intervention, nci_biomarker, nci_disease). Required for NCI searches. Get a free key at: https://clinicaltrialsapi.cancer.gov/
call_benefitNoBrief explanation of why this search is being performed and expected benefit. Helps improve search accuracy and provides context for analytics. Highly recommended for better results.
chemicalsNo
conditionsNo
diseasesNo
distanceNo
domainNoDomain to search: 'article' for papers/literature ABOUT genes/variants/diseases, 'trial' for clinical studies, 'variant' for genetic variant DATABASE RECORDS, 'gene' for gene information from MyGene.info, 'drug' for drug/chemical information from MyChem.info, 'disease' for disease information from MyDisease.info, 'nci_organization' for NCI cancer centers/sponsors, 'nci_intervention' for NCI drugs/devices/procedures, 'nci_biomarker' for NCI trial eligibility biomarkers, 'nci_disease' for NCI cancer vocabulary, 'fda_adverse' for FDA adverse event reports, 'fda_label' for FDA drug labels, 'fda_device' for FDA device events, 'fda_approval' for FDA drug approvals, 'fda_recall' for FDA drug recalls, 'fda_shortage' for FDA drug shortages
explain_queryNo
genesNo
get_schemaNo
interventionsNo
keywordsNo
latNo
longNo
max_results_per_domainNo
pageNo
page_sizeNo
phaseNo
queryYes
recruiting_statusNo
significanceNo
variantsNo
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden and does an excellent job disclosing behavioral traits: it explains the two search modes, return format (OpenAI MCP format without metadata), logic rules (AND for domain-specific, OR with unified query), API key requirements for NCI domains, and recommendations like using 'fetch' for metadata. It could improve by mentioning rate limits or error handling, but covers most critical aspects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with sections and bullet points, but it is overly long and includes some redundant information (e.g., repeating return format details). While most content is valuable, it could be more front-loaded and condensed, as some examples and notes could be streamlined without losing clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (22 parameters, no annotations, no output schema), the description is highly complete: it covers purpose, usage guidelines, behavioral traits, parameter semantics, and return format. It addresses the lack of structured data by providing comprehensive textual explanations, making it sufficient for an agent to use the tool effectively despite the sparse schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Given the low schema description coverage (14%), the description compensates extensively by explaining parameter semantics beyond the schema: it details the 'query' parameter syntax with examples, clarifies the 'domain' parameter with all possible values and use cases, and provides context for parameters like 'max_results_per_domain', 'page_size', 'get_schema', and 'explain_query'. It adds significant value over the minimal schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool searches biomedical literature, clinical trials, genetic variants, genes, drugs, and diseases, specifying the verb 'search' and the resources. It distinguishes from siblings by explaining this is a unified search tool that can access multiple domains, unlike specialized getter/searcher tools like 'article_searcher' or 'variant_searcher'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance on when to use this tool vs alternatives: it mandates using the 'think' tool first for research planning, distinguishes between unified query language and domain-specific search modes, and gives clear examples of when to use specific domains (e.g., 'domain="article"' for literature vs 'domain="variant"' for database records). It also warns against common mistakes like using the wrong domain.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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