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ruminaider

NewRelic MCP Server

by ruminaider

list_recent_logs

Retrieve recent log entries from NewRelic to monitor activity, filter by severity level, or apply custom search conditions for troubleshooting.

Instructions

List recent logs from NewRelic. Useful for getting an overview of recent log activity, filtering by level, or searching with custom conditions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoNumber of logs to retrieve (default: 100, max: 2000)
sinceMinutesAgoNoTime range in minutes to look back (default: 60)
levelNoLog level filter (e.g., 'ERROR', 'WARN', 'INFO', 'DEBUG')
whereClauseNoAdditional NRQL WHERE clause conditions. Example: service.name = 'my-service'
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 mentions filtering and searching capabilities but fails to describe critical behaviors such as pagination, rate limits, authentication requirements, response format, or whether this is a read-only operation. For a log retrieval tool with zero annotation coverage, this is a significant gap in transparency.

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 two concise sentences that front-load the core purpose. Every sentence adds value by specifying the resource and use cases, with no redundant or wasted information. It could be slightly more structured by separating use cases, but it's efficient overall.

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 (4 parameters, no output schema, and no annotations), the description is incomplete. It lacks details on behavioral traits like response format, pagination, or error handling, and doesn't compensate for the absence of annotations. For a log retrieval tool in a server with many siblings, more contextual guidance is needed to ensure proper agent usage.

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 100%, so the schema already documents all four parameters thoroughly. The description adds marginal value by hinting at filtering by level and custom conditions, but doesn't provide additional syntax, examples, or meaning beyond what's in the schema. This meets the baseline score when schema does the heavy lifting.

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 ('List') and resource ('recent logs from NewRelic'), and mentions filtering capabilities. It distinguishes itself from siblings like 'query_logs' by emphasizing 'recent' activity and 'overview' rather than complex querying. However, it doesn't explicitly contrast with 'analyze_entity_logs' or other log-related tools, preventing a perfect score.

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 context ('useful for getting an overview of recent log activity, filtering by level, or searching with custom conditions'), suggesting it's for quick, filtered log retrieval. However, it lacks explicit guidance on when to use this tool versus alternatives like 'query_logs' or 'analyze_entity_logs', and doesn't mention prerequisites or exclusions, leaving some ambiguity for 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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