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ruminaider

NewRelic MCP Server

by ruminaider

list_related_entities

Find related entities by GUID to identify service dependencies, infrastructure relationships, and dashboard associations in NewRelic.

Instructions

Get entities that are related to a specific entity. Shows connections like service dependencies, infrastructure relationships, and dashboard associations.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
guidYesThe entity GUID to find relationships for
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves related entities but doesn't describe what 'related' means operationally (e.g., directionality, depth, or types of relationships), how results are formatted, whether it's paginated, or any rate limits or permissions required. This leaves significant gaps for an agent to understand the tool's behavior.

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 concise with two sentences: the first states the core purpose, and the second provides clarifying examples. It's front-loaded with the main action, and every sentence adds value by elaborating on relationship types. There's no wasted text, though it could be slightly more structured with explicit usage cues.

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 the tool's complexity (retrieving relationships, which can be nuanced), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what 'related' entails, the format or scope of results, or any behavioral constraints. For a tool that likely returns structured relationship data, more context is needed to guide an agent effectively.

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?

The description adds no parameter-specific information beyond what the input schema provides. The schema has 100% description coverage, with the single parameter 'guid' documented as 'The entity GUID to find relationships for'. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.

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's purpose with a specific verb ('Get') and resource ('entities that are related to a specific entity'), and provides examples of relationship types ('service dependencies, infrastructure relationships, and dashboard associations'). However, it doesn't explicitly distinguish this tool from potential siblings like 'get_entity' or 'search_entity_with_tag', which might also retrieve entity information but with different scopes.

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 provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, exclusions, or compare it to sibling tools like 'get_entity' (which might retrieve a single entity) or 'search_entity_with_tag' (which might find entities by tags). The agent must infer usage 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.

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