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Check capture node health

arkime_node_stats
Read-only

Assess Arkime capture node health—drops, disk, memory, queues—to confirm missing traffic is genuine, not a capture gap. Verify data trustworthiness before analysis.

Instructions

Report each Arkime capture node's health: drops, disk, memory, queues.

    Use this to decide whether the data can be trusted before concluding
    anything from an absence: a node dropping packets or out of disk has
    gaps that look exactly like "no such traffic". For whether the Malcolm
    services are up at all use malcolm_service_status, and for OpenSearch
    cluster state use cluster_health — this one is about the capture side.

    `packets_dropped` is a running total, not a rate, so a non-zero one is
    history rather than a live fault; `dropped_per_sec` is the rate over
    Arkime's last stats interval, and the `warning` key marks a node losing
    packets right now. Per-node fields are in the output schema.
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nodeNoSubstring of a node name to narrow the list, e.g. "spark". Empty = every node.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, and the description adds valuable interpretation beyond that: packets_dropped is a cumulative counter not a rate, dropped_per_sec is the interval rate, and the warning key marks active loss. No contradiction 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 appropriately sized and front-loaded: the first sentence gives the core purpose, the second provides usage guidance, and the third clarifies field semantics. Every sentence earns its place without redundancy.

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?

For a simple health-check tool with one parameter and an output schema, the description covers purpose, usage, field interpretation, and points to the schema for per-node details. It fully addresses the decision context and sibling differentiation.

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 only parameter 'node' is already fully described in the input schema (substring matching, default empty meaning every node). With 100% schema description coverage, the description adds no additional parameter semantics, so baseline 3 is appropriate.

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 states a specific verb+resource: 'Report each Arkime capture node's health: drops, disk, memory, queues.' It clearly distinguishes from siblings by explicitly noting the capture-side scope and naming alternatives like malcolm_service_status and cluster_health.

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: 'Use this to decide whether the data can be trusted before concluding anything from an absence,' and gives clear alternatives: 'For whether the Malcolm services are up at all use malcolm_service_status, and for OpenSearch cluster state use cluster_health.' This fully covers usage guidance and exclusions.

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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