VISEON for Web

query_relationships

Find entities connected to a subject: one row per property value, with object_type 'uri' for links to other entities and 'literal' for values. Optionally filter by predicate.

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": "<subject>"
    },
    "name": "query_relationships"
  }
}

Input Schema

Name	Required	Description	Default
`subject`	Yes
`predicate`	No

Output Schema

Name	Required	Description	Default
`count`	Yes
`items`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedSep 28, 2026

TDQS

B3.2/5.0

Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It usefully discloses the output semantics ('one row per property value', object_type 'uri' vs 'literal'), but says nothing about permissions, result limits, or whether traversal is recursive, and an output schema already covers the return shape.

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?

Two compact clauses with no filler; the core behavior and the optional filter are front-loaded. Slightly compressed, but nothing is wasted.

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 2-parameter query tool with an output schema, the description covers the essentials of what is returned and the optional filter, but it leaves parameter formats and sibling disambiguation unaddressed. Adequate but with clear gaps.

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 0%, so the description must compensate. It clarifies that predicate is an optional filter, but subject is only implied to be the starting entity and no value format (IRI vs label) is given for either 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?

States a specific verb and resource ('Find entities connected to a subject') and even clarifies the result shape (one row per property value, uri vs literal). It is clear on its own, but it never differentiates itself from siblings like get_entity or find_by_type, so an agent must infer which is appropriate.

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 only usage cue is that predicate is an optional filter; there is no statement of when to reach for this tool versus find_by_type, get_entity, fuzzy_find_and_traverse, or search_content. No prerequisites or exclusions are given.

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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