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hebbian-mind-enterprise

hebbian-mind-enterprise

by For-Sunny
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

analyze_content

Preview which concepts would activate by analyzing content against concept nodes without saving results.

Instructions

Analyze content against concept nodes without saving. Preview which concepts would activate.

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": {
      "content": "<content>"
    },
    "name": "analyze_content"
  }
}

Input Schema

NameRequiredDescriptionDefault
contentYesContent to analyze
thresholdNoActivation threshold 0-1 (default: configured threshold)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.3.2

TDQS

A3.7/5.0
Behavior3/5

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

The description discloses that no saving occurs, which is helpful, but lacks other behavioral details such as whether content is stored temporarily, authorization requirements, or 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.

Conciseness5/5

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

The description is two brief sentences with no extraneous words, efficiently conveying purpose and key behavioral trait.

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?

For a low-complexity tool with no output schema, the description could be more complete by explaining what 'preview' means (e.g., returns list of node IDs) or providing usage context relative to siblings.

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 description coverage is 100% for both parameters; the description adds no additional meaning beyond the schema, so baseline score of 3 is appropriate.

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 tool's action (analyze content against concept nodes) and the output (preview which concepts would activate), distinguishing it from siblings like save_to_mind (which saves) and query_mind (which queries).

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 dry-run usage with 'without saving' but does not explicitly state when to use this tool versus alternatives like save_to_mind or get_related_nodes.

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

Deploy Server

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