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NewRelic MCP Server

by ruminaider

analyze_golden_metrics

Retrieve key performance indicators for a NewRelic entity, including metric names and NRQL queries to monitor essential metrics for APM applications, hosts, and other entity types.

Instructions

Get the golden metrics defined for a NewRelic entity. Golden metrics are the key performance indicators that NewRelic recommends monitoring for each entity type (APM applications, hosts, etc.). Returns metric names, titles, and the NRQL queries used to calculate them. Use these queries to understand what metrics are important for an entity.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
guidYesThe entity GUID to analyze golden metrics for
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool returns metric names, titles, and NRQL queries, which covers output behavior. However, it doesn't mention whether this is a read-only operation, potential rate limits, authentication requirements, error conditions, or if the data is cached/live. For a tool with zero annotation coverage, this leaves significant behavioral gaps.

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 with three sentences that each add value: defining golden metrics, specifying the return data, and providing usage context. It's front-loaded with the core purpose and avoids redundancy. While efficient, it could be slightly more structured by separating definition from usage guidance.

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?

Given the tool has one parameter with full schema coverage but no annotations and no output schema, the description provides adequate context for a read operation by explaining what golden metrics are and what data is returned. However, it lacks details on output format (e.g., structure of returned data), error handling, or dependencies, making it minimally complete but with room for improvement.

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 input schema has 100% description coverage, with the 'guid' parameter fully documented in the schema. The description doesn't add any parameter-specific information beyond what the schema provides, such as explaining entity GUID format or where to obtain it. With high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but doesn't need to heavily.

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 retrieves golden metrics for a NewRelic entity, specifying what golden metrics are and what information is returned (metric names, titles, NRQL queries). It distinguishes from siblings by focusing on recommended key performance indicators rather than logs, transactions, dashboards, or other entity data. However, it doesn't explicitly contrast with tools like 'get_entity' which might provide broader entity information.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage when you need to understand important metrics for an entity, as indicated by 'Use these queries to understand what metrics are important for an entity.' It doesn't provide explicit when-not-to-use guidance or name specific alternatives among siblings like 'get_entity' or 'list_entity_types', leaving usage context somewhat inferred rather than clearly defined.

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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