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welingtoncassis

newrelic-mcp-nerdgraph

summarize_log_errors

Read-onlyIdempotent

Groups error logs by message pattern to reveal the most frequent failures, helping identify what is broken rather than investigating a specific request.

Instructions

Group error logs by message pattern to show what is failing most.

Prefer this over search_logs when the question is "what is broken" rather than "show me this specific request".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
sinceNo1 HOUR AGO
account_idsNo
service_nameNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is covered. The description adds the aggregation-by-pattern behavior, which is genuinely useful, but says nothing about the default 1-hour window, result cap, or how grouping/counting is performed. With annotations carrying the safety burden, a 3 fits.

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?

Two short sentences, zero waste, and the core behavior is front-loaded ahead of the disambiguation rule. Nothing here is padding.

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?

An output schema exists, so return values need not be explained, and the routing rule is complete. However, the four undocumented parameters and their defaults (1 HOUR AGO, limit 20) leave the caller guessing about scope, which matters for a log-aggregation tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% across four parameters, so the schema contributes nothing about what since, limit, account_ids, or service_name mean or their defaults. The description mentions no parameters at all, so it fails to compensate for the coverage gap. An agent cannot learn the time-window or scoping semantics from either source.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Group error logs by message pattern') plus the outcome it produces ('show what is failing most'). This is clearly distinguishable from the sibling search_logs, which it names explicitly.

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

Usage Guidelines5/5

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

Gives an explicit routing rule: use this over search_logs when the question is 'what is broken' rather than 'show me this specific request'. The alternative and the condition that selects it are both stated, leaving nothing to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.