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nks1097

Splunk Enterprise MCP Server

by nks1097

splunk_diagnose_ingestion

Diagnose Splunk ingestion pipeline health by evaluating queue sizes, drop rates, and bottlenecks to pinpoint performance issues.

Instructions

Composite diagnostic: evaluate overall pipeline health, queue sizes, drop rates, and bottlenecks.

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
dataNoOutput payload or results
errorNoError message if execution failed
successNoWhether the tool execution succeeded
metadataNoExecution timing, pagination and environment details
warningsNoOperational warnings or notices
request_idNoCorrelation ID for audit trail and observability

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the behavioral burden. It discloses that this is a composite evaluation of several ingestion-health signals, which is useful, but it does not explicitly state that it is read-only, whether it runs heavy queries, or what permissions/timeouts apply.

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 a single front-loaded sentence with no wasted text. It efficiently names the tool type and the specific health dimensions being evaluated.

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?

With no parameters and an output schema present, the description is complete enough to invoke safely, and it indicates the scope of the diagnostic. However, in a large ecosystem of ingestion-specific siblings, it does not fully explain when this composite tool is preferable to the granular alternatives.

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?

The tool has zero parameters, so the baseline is 4. The description does not need to explain input semantics, and the empty schema is consistent with a no-argument diagnostic.

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 states a specific verb (evaluate) and resource (overall pipeline health) and lists concrete diagnostic aspects: queue sizes, drop rates, and bottlenecks. The word 'composite' signals it is an aggregate diagnostic rather than a granular metric fetch, though it does not explicitly name the sibling tools it replaces.

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

Usage Guidelines2/5

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

There is no explicit when-to-use or when-not-to-use guidance, and no alternatives are named. 'Composite diagnostic' implies a broad overview, but the description never tells the agent to choose this over granular siblings such as splunk_get_ingestion_metrics, splunk_get_ingestion_lag, or splunk_get_parsing_errors.

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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