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import_vcf

Import VCF files (.vcf or .vcf.gz) into Gigwa databases, projects, and runs. Supports replacing existing project data and returning progress tokens.

Instructions

Import a VCF file (.vcf or .vcf.gz) into Gigwa.

Uploads the VCF to create/append a database (module), project and run. technology is optional free-text (e.g. 'WGS', 'GBS'). Use clear_project_data=True to replace existing project data and wait=False to return a progress token instead of blocking.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
runYesTarget run name within the project.
waitNoBlock until the import finishes (True) or return a progress token immediately (False).
moduleYesTarget Gigwa database (module) name.
ploidyNoSample ploidy (default 2).
projectYesTarget project name within the database.
vcf_pathYesPath to the VCF file (.vcf or .vcf.gz) to import.
technologyNoFree-text genotyping technology label (e.g. 'DArTseq', 'WGS', 'GBS').
skip_monomorphicNoDrop non-variant (monomorphic) markers during import.
clear_project_dataNoReplace any existing data in the project before importing.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Though no annotations are provided, the description discloses key behaviors: it can append or clear project data (clear_project_data) and blocking vs non-blocking execution (wait). This covers safety and control aspects well.

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: first states core purpose, second elaborates key parameters. No wasted words, effectively front-loaded for quick understanding.

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

Completeness4/5

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

Given 9 parameters and presence of output schema (implied), the description covers required parameters, optional ones, and key behaviors (clear, wait). It adequately sets expectations for an import tool.

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

Parameters4/5

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

Schema coverage is 100%, so description adds context beyond the schema: explains the role of module/project/run in creating/appending, describes technology as optional free-text, and clarifies clear_project_data and wait. It groups and interprets parameters usefully.

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?

Description clearly states it imports a VCF file into Gigwa, specifying the action (import), resource (VCF), and target (Gigwa database/project/run). It distinguishes from sibling import_dartseq by format.

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?

Describes parameters like clear_project_data and wait, guiding usage in some scenarios, but does not explicitly state when to use this tool over siblings (e.g., import_dartseq) or exclude alternatives.

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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