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hebbian-mind-enterprise

hebbian-mind-enterprise

by For-Sunny
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

get_related_nodes

Retrieve nodes connected to a specified node via Hebbian edges, filtering by minimum edge weight. Ideal for exploring associative memory graphs strengthened through use.

Instructions

Get nodes connected to a given node by Hebbian edges.

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": {
      "node": "<node>"
    },
    "name": "get_related_nodes"
  }
}

Input Schema

NameRequiredDescriptionDefault
nodeYesNode name to find related nodes for
min_weightNoMinimum edge weight (default: 0.1)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.3.2

TDQS

B3.3/5.0
Behavior2/5

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

No annotations are provided, so the description must fully disclose behavior. It only states the basic function without mentioning read-only nature, permissions, or any side effects.

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

Conciseness4/5

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

The description is a single short sentence, front-loaded with the key information. However, it is extremely terse and could include a bit more context without being verbose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description is thin; it does not explain the return format or what 'related' means. With no output schema, the agent lacks information on what to expect.

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 coverage is 100% with clear descriptions for both parameters. The tool description does not add any additional meaning beyond what the schema already 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?

Description clearly states the verb 'get', resource 'nodes', and the specific relationship 'Hebbian edges', which distinguishes it from sibling tools like 'list_nodes' that lists all nodes.

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 fetching related nodes but does not provide explicit when-to-use or when-not-to-use guidance, nor does it mention alternatives like 'faiss_search' for semantic similarity.

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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