phylokit-mcp

Overview Schema Source Related Servers Discussions Admin

Rank substitution models, with the margin over the runners-up

select_substitution_model

Read-onlyIdempotent

Compare substitution models for aligned DNA or protein sequences, returning ranked models by AIC/AICc/BIC with the winner's margin and agreement between criteria.

Instructions

Compare substitution models and report how much the winner won by.

A single model name reads as a finding. The ranking, the delta to the next model, and whether AIC/AICc/BIC agree are what make it one.

Args: fasta: Aligned sequences in FASTA, nucleotide or protein as declared by sequence_type. criterion: "AIC", "AICc" or "BIC". BIC penalises parameters more heavily. seed: Fixes the engine's search. top_n: How many ranked models to return. sequence_type: "dna" (default) or "protein". Ranks within that molecule type's model set — nucleotide and protein models are not comparable.

Input Schema

TableJSON Schema

Name	Required	Default
`seed`	No
`fasta`	Yes
`top_n`	No
`criterion`	No	AIC
`sequence_type`	No	dna

Output Schema

TableJSON Schema

Name	Required	Description	Default
`seed`	Yes
`ranking`	Yes
`warnings`	Yes
`alignment`	Yes
`criterion`	Yes
`best_model`	Yes
`criteria_agree`	Yes
`best_by_criterion`	Yes
`n_models_compared`	Yes
`indistinguishable_from_best`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedv0.3.0Aug 2, 2026

addedInput schema / properties / sequence_type

Added value: +{
+  "default": "dna",
+  "title": "Sequence Type",
+  "type": "string"
+}

First observedv0.1.0Jul 30, 2026

TDQS

A4.4/5.0

Behavior4/5

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

Annotations already indicate readOnlyHint and idempotentHint, and the description adds valuable context beyond those: the finding requires ranking plus delta and agreement among criteria, BIC penalizes parameters more heavily, seed fixes the search, and rankings are confined to the declared sequence_type's model set. No contradiction with annotations exists.

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?

The description is front-loaded with a clear one-sentence summary, followed by a compact but necessary Args block that compensates for the schema's lack of descriptions. Every sentence adds value, and there is no filler or repetition of annotation data.

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 moderate complexity, the presence of an output schema, and read-only/idempotent annotations, the description covers what an agent needs: input requirements, parameter options, behavioral expectations, and the cross-molecule-type limitation. No critical invocation information is missing.

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?

Schema description coverage is 0%, so the description carries the full burden, and it delivers. It explains all five parameters: fasta as aligned sequences, criterion with its three options and BIC's heavier penalty, seed as a search fix, top_n as the count of ranked models, and sequence_type with the important DNA/protein comparability caveat.

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 opens with a specific verb and resource: 'Compare substitution models and report how much the winner won by.' It clearly differentiates this tool from siblings like compare_trees and infer_tree by focusing on substitution-model ranking rather than tree comparison or inference. The title reinforces the same purpose without ambiguity.

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 through its purpose and includes meaningful guidance such as the need to report the delta and whether AIC/AICc/BIC agree, plus the warning that nucleotide and protein models are not comparable. However, it never explicitly states when to prefer this tool over alternatives like infer_tree, compare_trees, or align_sequences, nor does it provide exclusions such as 'use this only when...'.

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

Deploy Server