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r3 (Recall)

by n3wth
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TypeScript
Hybrid

find_connections

Read-onlyIdempotent

Discover relationship paths between entities in a knowledge graph using BFS traversal. Find how two entities are connected by exposing the chain of edges linking them.

Instructions

Discover relationship paths between entities in the knowledge graph. Uses BFS traversal to find how entities connect. Useful for answering 'how is X related to Y?' questions. Requires enhanced mode. Read-only. Returns: {from, to, max_depth, paths_found, paths[]} where each path is array of {from, to, type} edges.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
max_depthNoMaximum relationship hops to traverse. Range: 1-5. Higher values exponentially increase results. Default: 2.
to_entityNoTarget entity name. If omitted, returns all reachable entities up to max_depth.
from_entityYesStarting entity name for path search. Must match an entity in the knowledge graph exactly.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changedv1.3.2
    • changedInput schema / properties / from_entity / description
      Previous value: -"Starting entity name"New value: +"Starting entity name for path search. Must match an entity in the knowledge graph exactly."
    • removedInput schema / properties / max_depth / default
      Removed value: -2
    • changedInput schema / properties / max_depth / description
      Previous value: -"Maximum relationship depth to traverse"New value: +"Maximum relationship hops to traverse. Range: 1-5. Higher values exponentially increase results. Default: 2."
    • changedInput schema / properties / to_entity / description
      Previous value: -"Target entity name (optional - finds all if not specified)"New value: +"Target entity name. If omitted, returns all reachable entities up to max_depth."
  2. First observedv1.3.1

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already provide readOnly, idempotent, and non-destructive hints. The description adds meaningful behavior: BFS traversal, the enhanced-mode requirement, and the return payload structure. This exceeds what the annotations alone convey.

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 appropriately sized and front-loaded with the core purpose. The sentence on return format is useful, but 'Read-only' is redundant with annotations and some phrasing is slightly repetitive.

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

Completeness5/5

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

For a 3-parameter tool with no output schema, the description covers the key behavioral detail, the return shape, the required mode, and the primary use case. No critical information needed to invoke or interpret the tool appears to be missing.

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?

Input schema coverage is 100%, and each parameter already has a descriptive definition. The tool description does not add material parameter meaning beyond the schema, so the baseline of 3 applies.

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 states a specific verb and resource ('Discover relationship paths between entities in the knowledge graph') and clarifies the goal with a concrete use case ('how is X related to Y?'). It clearly differentiates from siblings like get_knowledge_graph by focusing on paths rather than the whole graph.

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?

It gives a clear context for use ('answering how is X related to Y') and a prerequisite ('Requires enhanced mode'). It does not explicitly name alternatives or state when not to use this tool, but the purpose is specific enough to guide selection.

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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