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Monitoring AIops

topn

Read-only

Rank SolarWinds nodes by CPU, memory, latency, or packet loss, returning N nodes sorted by metric to identify performance issues.

Instructions

[READ] Top-N SolarWinds nodes by a health metric.

Returns {"nodes": [...], "returned": N, "metric": str, "error": str | None}. A non-null "error" means the SWQL query failed — the opposite finding from "no nodes are under load", so never report one as the other.

Args: metric: One of cpu, memory, latency, packetloss. n: How many nodes to return (default 10). target: SolarWinds target name from config; omit for the default.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nNo
metricNocpu
targetNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.9.0

TDQS

A4.1/5.0
Behavior4/5

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

With readOnlyHint already covering the safety profile, the description adds genuinely useful behavior: it discloses the return envelope and warns that a non-null error means the SWQL query failed, explicitly contrasting it with a 'no nodes under load' result. That is a real interpretation hazard the schema and annotations do not surface. It stops short of describing pagination, ordering direction, or how ties are handled.

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?

Front-loaded with a [READ] tag and the one-line purpose, followed by return shape, the error caveat, and a compact Args block. The Args section duplicates what a well-documented schema would carry and runs slightly long, but every line is informative and nothing is padded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, so the description appropriately documents the return shape inline and flags the error-vs-empty-result ambiguity that matters most for correct reporting. For a 3-parameter read tool this is close to complete; only ordering/tie-breaking and target-name format remain unstated.

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

Parameters4/5

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

Schema description coverage is 0%, so the description carries the full parameter burden and largely does: metric enumerates the four valid values (an enum the schema itself lacks), n explains the default-10 count semantics, and target explains config-name resolution plus the omit-for-default behavior. Values are documented but format for target (exact config key string) could be sharper.

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 operation ('Top-N ... nodes by a health metric') with the resource (SolarWinds nodes) and the ranking dimension, which distinguishes it from the flat listing siblings like nodes_list and node_status. An agent can tell what it produces (a ranked subset, not a full inventory) without opening the schema.

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?

Usage is implied by the ranking concept rather than stated – the agent must infer that this is the tool for 'which nodes are most loaded' versus nodes_list for enumeration. It does mention that omitting target uses the default, a small contextual hint, but there is no explicit when-to-use or when-not-to-use guidance and no sibling named.

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