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run_gwas

Perform genome-wide association analysis with linear or logistic regression. Input genotype and phenotype files to obtain summary statistics including p-values and effect sizes.

Instructions

Perform genome-wide association study using linear or logistic regression. Returns summary statistics including p-values, beta coefficients, and standard errors.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
plink_prefixYesPath prefix for PLINK genotype files
phenotype_pathYesPath to phenotype file (tab-separated with FID, IID, PHENO columns)
covariate_pathNoOptional path to covariate file
modelNoRegression model type (default: linear)linear
output_pathNoPath to save GWAS results
Behavior2/5

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

No annotations provided, and description lacks details on prerequisites (e.g., PLINK software), side effects (e.g., file creation), or computational requirements. Only mentions regression type and output format, leaving many behavioral traits undisclosed.

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

Conciseness5/5

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

Two concise sentences, no redundancy, front-loaded with purpose. Every word adds value.

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

Completeness2/5

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

For a tool with 5 parameters, no output schema, and many siblings, the description is too minimal. It lacks context on expected inputs, output structure, and when to use this tool versus other GWAS analysis tools.

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

Parameters3/5

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

Schema covers 100% of parameters with descriptions. The description adds a high-level summary of return values but does not enhance parameter meaning beyond what is in the schema.

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

Purpose4/5

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

Description clearly states it performs GWAS with linear/logistic regression and lists output statistics. However, it does not differentiate from sibling tools like calculate_heritability_ldsc or clump_snps, which are also GWAS-related.

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

Usage Guidelines2/5

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

No explicit when-to-use or when-not-to-use guidance. The description does not mention alternatives or conditions for choosing this tool over siblings.

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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