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neuroverse

neuroverse

by joshua400
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

High-Performance Reason

neuroverse_reason
Read-onlyIdempotent

Execute complex reasoning tasks using high-performance models for analytical responses.

Instructions

Execute a complex reasoning task using specialized high-performance models (e.g. OpenRouter Reasoning). Returns the model's analytical response.

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": {
      "prompt": "<prompt>"
    },
    "name": "neuroverse_reason"
  }
}

Input Schema

NameRequiredDescriptionDefault
promptYesThe complex prompt requiring high-performance reasoning

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4/5.0
Behavior4/5

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

Annotations (readOnlyHint, idempotentHint) are present and consistent, covering safety aspects. The description adds value by specifying the model type and return nature, but does not disclose potential latency or cost implications.

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?

Single sentence, directly informative, no superfluous words. It earns its place.

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?

Despite no output schema, the description mentions the return type ('analytical response'). Parameter is fully described in schema, and annotations cover behavior. Minor gap: could specify output format.

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?

With 100% schema description coverage, the parameter 'prompt' is already well-documented in the schema. The tool description adds no additional semantic detail beyond what the schema provides.

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 clearly states the operation ('Execute a complex reasoning task'), the resource ('specialized high-performance models'), and the output ('analytical response'). It distinguishes itself from siblings like neuroverse_synthesize and neuroverse_recall by specifying high-performance reasoning.

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 usage for complex reasoning tasks but does not explicitly state when to use this tool versus alternatives. No exclusion criteria or when-not-to-use guidance is provided.

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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