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neurograph

neurograph

by InsideProxy
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
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render_network

Render a real PNG circular connectogram from an atlas, colored by functional network, with chords above a weight threshold, providing an actual image for visualizing brain connectivity.

Instructions

Imagen PNG real: connectograma circular de un atlas, con los nodos coloreados por red funcional real (leyenda incluida) y una cuerda gris por cada conexión real por encima de min_weight. Nunca un descriptor de escena -- una imagen real, igual que pidió la usuaria (31/08/2026). Lanza un error si el atlas no tiene ninguna región real cargada.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "atlas_id": "<atlas_id>"
    },
    "name": "render_network"
  }
}

Input Schema

NameRequiredDescriptionDefault
atlas_idYes
min_weightNo
connection_typeNostructural

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior4/5

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

With no annotations, the description carries the transparency burden and does disclose key runtime behavior: real PNG output, included legend, gray chord per connection above min_weight, and an error when no real regions are loaded. It stops short of stating side effects or permissions, but for a render-style operation the provided behavior is unusually specific.

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

Conciseness3/5

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

The core sentence is dense and informative, and details are front-loaded. However, the second sentence repeats 'real image' and adds a user-request date that does not help an agent invoke the tool, so not every sentence earns its place.

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?

The definition covers output type and one error condition but leaves out the return delivery format (PNG bytes, URL, etc.), valid connection_type semantics, and guidance for choosing this tool over render_brain. Given no output schema and no annotations, this is minimally acceptable but not complete.

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?

Since schema descriptions cover 0% of parameters, the tool description must explain them. It clarifies min_weight as the connection threshold and indirectly identifies atlas_id as the atlas source, but connection_type is never explained, and with no enums listed the agent cannot know valid values or how it affects the connectogram.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a concrete deliverable: a real PNG circular connectogram of an atlas, with node coloring and thresholded chords. It also stresses that it is not a scene descriptor, which gives some differentiation, but it never names a sibling like render_brain, so the distinction is not explicit.

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

Usage Guidelines2/5

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

There is no statement about when to prefer render_network over render_brain or other siblings. The 'never a scene descriptor' remark is an output guarantee, not a routing rule, and no alternative tool is suggested or excluded.

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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