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gkanogiannis

Gigwa-MCP

by gkanogiannis
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Python
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diversity_tree

Builds a UPGMA dendrogram from pairwise IBS allele-sharing distances and writes a Newick tree file to visualize genetic relationships among accessions.

Instructions

UPGMA dendrogram of accessions from IBS allele-sharing distance (Newick).

Builds a pairwise IBS similarity matrix, converts to distance (1 − IBS), and writes a UPGMA tree as tree.nwk (standard Newick, loadable in FigTree / iTOL / ape). Marker subsampling (max_markers) keeps it tractable on large sets.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
methodNoGenotype source: 'vcf' (full export, cached) or 'allelematrix' (paged, server-side subset).vcf
regionNoRestrict analysis to a genomic window: 'chrom' or 'chrom:start-end' (1-based).
output_dirNoDirectory for the output CSV(s) (default ./gigwa_results/<module>/).
max_markersNoCap analysis to the first N markers in canonical Gigwa search order; omit to use all.
variant_set_db_idYesBrAPI variantSetDbId identifying the run (MODULE§project§run) -- copy the exact string from list_variant_sets / list_content, never assemble one by hand: the middle segment is a numeric project index, not the project's name, and a wrong guess fails with an opaque HTTP 500 rather than a clear error.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed2 schema fields changedv1.9.1
    • changedInput schema / properties / max_markers / description
      Previous value: -"Cap the number of markers analysed (evenly-spaced subsample); omit to use all."New value: +"Cap analysis to the first N markers in canonical Gigwa search order; omit to use all."
    • changedInput schema / properties / variant_set_db_id / description
      Previous value: -"BrAPI variantSetDbId identifying the run (MODULE§project§run); from list_variant_sets / list_content."New value: +"BrAPI variantSetDbId identifying the run (MODULE§project§run) -- copy the exact string from list_variant_sets / list_content, never assemble one by hand: the middle segment is a numeric project index, not the project's name, and a wrong guess fails with an opaque HTTP 500 rather than a clear error."
  2. First observedv1.4.16

TDQS

A4/5.0
Behavior4/5

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

With no annotations, the description carries the transparency burden. It discloses the full workflow: pairwise IBS similarity, conversion to distance, and writing tree.nwk. It also calls out the max_markers subsampling behavior, which is useful operational context beyond the schema.

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 focused sentences, with the core purpose front-loaded. Every clause adds information: method, distance definition, output format, and scalability note.

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?

The description covers the algorithm, output file, and a key parameter trade-off, and an output schema exists so return value details are not required. It is complete enough for a compute-and-write tool, though it could have added a sentence about when to choose this over sibling diversity analyses.

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 description coverage is 100%, so the baseline is 3. The description adds a little context around max_markers ('keeps it tractable') and the Newick output, but does not substantially enrich the parameter semantics beyond the schema.

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 starts with a specific verb and resource: 'UPGMA dendrogram of accessions from IBS allele-sharing distance (Newick)'. It clearly explains the method and output, distinguishing it from sibling diversity tools like diversity_pca or diversity_structure.

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?

The description implies when to use the tool: when a hierarchical UPGMA tree of accessions is desired. However, it does not explicitly mention alternatives or conditions for choosing this over other diversity_* tools.

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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