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jarvis-orb

jarvis-orb

by TheStack-ai
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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entity_relate

Establishes a predicate-based relationship between two entities, enabling structured semantic connections in persistent memory.

Instructions

Create a relationship between two entities.

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": {
      "subject_id": "<subject_id>",
      "predicate": "<predicate>",
      "object_id": "<object_id>"
    },
    "name": "entity_relate"
  }
}

Input Schema

NameRequiredDescriptionDefault
object_idYes
predicateYes
subject_idYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.4/5.0
Behavior2/5

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

No annotations are provided, so the description must carry the burden. It fails to disclose behavioral traits such as whether relationships can be overwritten, permissions needed, or handling of non-existent entities. The output schema exists but content is unknown.

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

Conciseness2/5

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

The description is too sparse (one sentence) and lacks important information. While concise, it sacrifices completeness.

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?

Given 3 required parameters, no annotations, and an output schema with unknown content, the description is incomplete. It does not explain return values, side effects, or edge cases.

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

Parameters1/5

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

The schema has 0% description coverage for parameters, and the tool description adds no meaning to 'subject_id', 'predicate', or 'object_id'. The agent gets no help understanding what valid predicates are or expected ID formats.

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 action (create) and resource (relationship between two entities). It distinguishes from siblings like entity_create (which creates entities) and memory_save (saves contexts). However, it could be more specific about the nature of the relationship.

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?

No guidance on when to use this tool versus alternatives. The description does not mention prerequisites, conditions for use, or when not to use it.

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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