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MohamedSawahZC

newrelic-mcp

get_golden_signals

Fetch throughput, error rate, latency, and saturation for an APM app to monitor performance health.

Instructions

Get golden signals for an APM app: throughput, error rate, latency, saturation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sinceNoNRQL time range (default: "30 minutes ago"). Examples: "1 hour ago", "3 hours ago", "1 day ago"30 minutes ago
app_nameYesThe application name as it appears in New Relic.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

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 full burden of behavioral disclosure. It only states what the tool does (fetch signals) and gives no information about side effects, required permissions, data recency, or any limitations. For a read-only operation this is minimally acceptable, but the absence of any behavioral context makes it insufficient.

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

Conciseness5/5

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

A single, compact sentence that front-loads the purpose and enumerates the returned signals. Every word contributes value, and it is easy to scan quickly.

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?

The tool is simple, parameters are fully documented in the schema, and an output schema exists. The description covers the core purpose, but it omits usage context (e.g., when to prefer this over other tools) and any behavioral caveats. For a basic read tool this is adequate but not comprehensive.

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 schema provides 100% coverage with descriptions for both parameters (app_name, since) and a default for since. The description adds no further meaning beyond restating the resource ('App' and 'golden signals'), so it does not enhance parameter understanding. Baseline 3 is appropriate given the high schema coverage.

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 ('Get') and the resource ('golden signals for an APM app'), listing the four signal types. It is specific enough to distinguish from general query tools like nrql_query, though it does not explicitly differentiate from siblings like get_throughput_timeseries, so it misses the top score.

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 is provided on when to use this tool versus alternatives. It does not mention that this tool provides a consolidated summary of the four golden signals in one call, nor does it suggest when one might use get_throughput_timeseries for a specific metric. The description leaves usage decisions entirely to the agent.

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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