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angrysky56
by angrysky56

explore_connections

Discover non-obvious connections and patterns in a knowledge graph by traversing relationships from any entity, with adjustable depth and relationship filters.

Instructions

Explore connections and relationships around a specific entity in the knowledge graph.

This tool implements the graph traversal capabilities for discovering non-obvious connections and patterns.

Args: entity: Entity name to explore from depth: How many relationship hops to explore (1-5) connection_types: Specific relationship types to follow

Returns: Visual representation of connections and discovered patterns

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
depthNo
entityYes
connection_typesNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior2/5

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

No annotations are provided, and the description does not explicitly state whether the operation is read-only, has side effects, or requires special permissions. While exploring graph connections implies a non-destructive action, the lack of any transparency about potential rate limits or data access restrictions leaves the agent uncertain.

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 concise and well-structured, with a brief overview followed by a purpose statement and parameter list. The only minor redundancy is the second sentence repeating the concept of 'exploring' from the first, but it adds value by specifying 'non-obvious connections'.

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?

The description covers the core functionality, parameter meanings, and a general note on returns (visual representation of connections). It does not detail the output schema, but the context indicates one exists, and the tool's moderate complexity makes this absence acceptable. Alternative tools and behavioral details are not addressed, slightly reducing completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

All three parameters are thoroughly explained in the Args section: entity is the starting point, depth specifies the relationship hops with a range, and connection_types allows filtering by relationship type. This fully compensates for the schema lacking inline descriptions, giving the agent clear semantic meaning for each parameter.

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 the tool explores connections and relationships around a specific entity in the knowledge graph, using a specific verb and resource. It distinguishes itself from sibling tools like query_knowledge or wiki_search by focusing on graph traversal and discovering non-obvious patterns, though it could be more explicit about the output format.

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?

The description does not provide any guidance on when to use this tool versus alternatives. It fails to mention conditions like 'use this when you need to find relationships' or exclude cases where query_knowledge might be more appropriate, leaving the agent to infer applicability from the purpose alone.

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