Skip to main content
Glama

compare_species_images

Visualize two species' brain differences and homologies by generating three PNG images: a circular connectogram of exclusive and shared regions, plus interhemispheric schematics for each species.

Instructions

Tres imágenes PNG reales que comparan dos especies (decisión de la usuaria, 31/08/2026): (1) un connectograma circular con las regiones reales de las dos especies (todos sus atlas), coloreadas en tres categorías -- exclusiva de la especie A, exclusiva de la especie B, y homóloga/compartida (participa en al menos una homología real con la otra especie de esta comparación) -- con una cuerda real por cada homología y leyenda de las tres categorías; (2) y (3), un esquema interhemisférico real por especie (solo sus regiones homólogas con la otra), coloreado por hemisferio real. Nunca superpone las dos especies en un único cerebro 3D: cada una tiene su propia anatomía y su propio espacio de referencia (decisión 29), así que no tendría sentido dibujarlas juntas en una escena espacial. Lanza un error si alguna de las dos especies no existe, o si existen pero no comparten ninguna homología real.

structured_output=False (bug real encontrado al conectar esta herramienta, 31/08/2026, decisión 37): el SDK de MCP intenta generar un esquema pydantic de salida a partir del tipo de retorno anotado, y Image está especialcasada para un retorno suelto pero NO dentro de un list[...] -- sin este parámetro, registrar la herramienta lanzaba PydanticSchemaGenerationError en cuanto se importaba este módulo, antes incluso de poder llamarla.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
min_weightNo
species_a_idYes
species_b_idYes
connection_typeNostructural

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior5/5

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

With no annotations provided, the description fully carries the behavioral disclosure burden. It clearly states the output (three PNGs), error conditions (nonexistent species or no homology), and even documents a known bug workaround (structured_output=False). It also specifies that species are never overlaid, which is a critical behavioral trait. This is exceptionally transparent.

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

Conciseness2/5

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

The description is verbose, especially the extended bug note about pydantic schema generation and structured_output=False, which is tangential to the tool's purpose. While the opening does front-load the main purpose, the overall length and technical digression reduce conciseness. A tighter description would be more effective.

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 output format, error behavior, and a technical caveat, which is substantial. However, it omits explanation of min_weight and connection_type parameters, leaving a gap for those inputs. Given the tool's complexity (four params, image output, error cases), it is fairly complete but not fully comprehensive.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate and explain each parameter. It implicitly names species_a_id and species_b_id through 'two species', but does not explain min_weight or connection_type at all. These parameters remain unexplained, leaving agents guessing about their meaning and defaults.

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 states a specific verb (generate images comparing) and a precise resource (two species), and details the three output images, their content, and color coding. It distinguishes itself from siblings like render_brain or compare_species by emphasizing its non-overlay, image-based comparison approach, making it unmistakably unique.

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 visual comparison of two species is needed—but does not explicitly contrast it with alternatives or state conditions when to choose this over compare_species or render_network. It does mention it never overlays species in 3D, which hints at differences, but lacks direct guidance.

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