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ld_pruning

Remove highly correlated SNPs by pruning based on linkage disequilibrium. Filters variants exceeding a specified r² threshold within a sliding window to yield an independent set.

Instructions

Prune SNPs based on linkage disequilibrium (LD). Removes variants in high LD to create an independent set.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
plink_prefixYesPath prefix for PLINK files
r2_thresholdNor² threshold for LD pruning (default: 0.2)
window_sizeNoWindow size in kb for LD calculation (default: 500)
step_sizeNoStep size in variants (default: 50)
Behavior3/5

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

Without annotations, the description carries full burden but only states the core behavior. It does not disclose side effects (e.g., file output, data loss risk) or prerequisites beyond the plink_prefix.

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 sentences, no redundant words, directly conveys purpose and action.

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

Completeness3/5

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

With 4 parameters and no output schema or annotations, the description is minimal. It omits return values, output files, and default behavior context, leaving gaps for an AI agent.

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 coverage is 100% and includes descriptions for all parameters. The tool description adds no extra clarification, so baseline score applies.

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 action (pruning), the basis (linkage disequilibrium), and the goal (create independent set), distinguishing it from sibling tools like clump_snps.

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

Usage Guidelines3/5

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

No explicit guidance on when to use this tool vs alternatives, nor conditions for use. The purpose is implied but lacks context-specific direction.

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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