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Python
Remote

get_aria_node_resources

Read-onlyIdempotent

Check Aria Operations node memory, swap, heap, and watchdog restarts to pinpoint resource starvation when services error or respond slowly.

Instructions

[READ] Memory, swap, heap and watchdog restarts of the Aria Operations node(s) themselves.

When: get_aria_health shows a service in ERROR, or the Aria UI/API is slow — this reads Aria's self-monitoring objects (vC-Ops-Node, vC-Ops-Watchdog) to show whether the node is starved of memory. For data that stopped arriving from vCenter or another source, use list_adapters instead.

What: per node — memory (mem|total, mem|used, mem|free, mem|actualFree, mem|actualUsed), swap (swap|total, swap|used, swap|free), heap (heap|MaxHeapSize, heap|CurrentHeapSize, heap|CommittedMemory, heap|NodeHeapMemoryRemaining), heap_components (committed heap per component: Analytics, SuiteAPI, Collector, ...) and watchdog_restarts per service. Each value has latest, latest_time_ms, unit (from Aria's own statkey definitions, on 8.18.7: GB for mem/swap, MB for the heap sizes and heap_components, % for heap|NodeHeapMemoryRemaining; null when undefined) and window {min, avg, max, points} over window_hours of 5-minute averages. memory_pressure.level is an indicator, not a diagnosis: HIGH when actual free memory is below 10% of total, ELEVATED below 20%, NORMAL at 20% or more, UNKNOWN when the readings do not settle it; basis shows the numbers.

Gotchas: a key with no value is in the node's missing list (reason not_reported, no_data or undetermined) and is never shown as zero. watchdog_restarts null means unknown (see watchdog_note), not zero restarts. nodes null with nodes_error means the node objects were not recognised. units_error, latest_error, window_error and watchdog_error name reads that failed; when set, the affected values are unknown.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
targetNoAria target name from config; default when omitted.
window_hoursNoHours of history for window min/avg/max, 1-720 (default 24). Latest values are read regardless.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.15.0

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the annotations (readOnlyHint, openWorldHint, idempotentHint, destructiveHint), the description discloses critical behaviors: missing values appear in a missing list rather than as zeros, null watchdog_restarts means unknown (not zero), nodes null with nodes_error means unrecognized objects, and error fields (units_error, latest_error, etc.) flag failed reads. It also clarifies memory_pressure.level is an indicator, not a diagnosis. No contradictions with annotations.

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?

The description is well-structured with clear sections: a one-line summary, 'When' guidance, 'What' output details, and 'Gotchas'. It is front-loaded with the core purpose and uses bullet-like formatting for readability. Every sentence earns its place, providing necessary details without fluff.

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

Completeness5/5

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

Given the complexity of the tool (multiple metrics, units, per-node data, memory_pressure levels, error handling) and the absence of an output schema, the description is exceptionally thorough. It explains what each value includes (latest, latest_time_ms, unit, window stats), defines units per metric type, and covers edge cases and error conditions. An agent has enough context to call it correctly and interpret results.

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 already documents both parameters (target and window_hours) with 100% coverage, including default values and valid ranges. The tool description adds no new parameter-level meaning beyond what the schema provides, so it meets the baseline of 3 for full schema coverage. It does not mention the parameters explicitly beyond referring to window_hours in the output context, but that is not additional parameter semantics.

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?

The description opens with a specific verb-resource pair: '[READ] Memory, swap, heap and watchdog restarts of the Aria Operations node(s) themselves.' It clearly distinguishes from siblings by naming get_aria_health and list_adapters as alternatives. An agent can immediately tell what this tool does and how it differs.

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?

Explicitly provides when to use this tool: 'When get_aria_health shows a service in ERROR, or the Aria UI/API is slow'. It also gives an exclusion: 'For data that stopped arriving from vCenter or another source, use list_adapters instead.' This leaves no ambiguity about tool selection.

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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