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graph_query

Query the knowledge graph to find entities connected to a given entity, revealing relationships and dependencies within specified depth.

Instructions

Query the knowledge graph to find entities connected to a given entity. USE THIS WHEN: you want to understand relationships between concepts, find dependencies, or explore how entities are connected. Returns connected entities and relationship types within the specified depth.

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": {
      "entity": "<entity>"
    },
    "name": "graph_query"
  }
}

Input Schema

Name	Required	Default
`depth`	No
`entity`	Yes
`direction`	No	both
`rel_types`	No
`min_weight`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Jun 24, 2026

TDQS

B3.3/5.0

Behavior3/5

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

No annotations are provided, so the description carries the burden of behavioral disclosure. It indicates the tool returns connected entities and relationship types within a depth, implying a read-only query. However, it does not disclose side effects, limits, or required permissions.

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 short, front-loaded with the core purpose, and includes a usage hint. Every sentence adds value, but it could be slightly more concise by integrating the usage hint into the main sentence.

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?

With 5 parameters, 0% schema coverage, and no annotation support, the description fails to provide adequate context for parameter usage. Although an output schema exists, the lack of parameter documentation makes the tool incomplete for an agent.

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 coverage is 0%, but the description provides no explanation for any of the 5 parameters (entity, depth, rel_types, direction, min_weight). The agent must infer meanings from parameter names alone, which is insufficient for correct invocation.

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 clearly states that the tool queries the knowledge graph to find connected entities, with a specific verb and resource. However, it does not explicitly differentiate from sibling tools like 'entity_map' or 'related', which also explore connections.

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

Usage Guidelines4/5

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

The description explicitly provides a 'USE THIS WHEN' condition, guiding the agent to use the tool for understanding relationships and dependencies. However, it does not mention when not to use it or suggest alternatives.

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