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nks1097

Splunk Enterprise MCP Server

by nks1097

splunk_search_data_gaps

Detect time gaps in ingested data streams where expected events are missing. Analyze Splunk indexes by time buckets to pinpoint missing event windows.

Instructions

Detect time gaps in ingested data streams where expected events are missing.

Args: index: Index to analyze. sourcetype: Optional sourcetype filter. time_span: Bucket duration for binning (e.g. '15m', '1h'). earliest_time: Earliest search window.

Input Schema

NameRequiredDescriptionDefault
indexYes
time_spanNo1h
sourcetypeNo
earliest_timeNo-24h@h

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

B3.1/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. It implies a read-style search over an index and mentions time-span binning, but does not disclose permissions, search cost/performance implications, whether the operation is read-only, or how the search is executed.

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 front-loaded with the core purpose and then uses a compact Args block to attach parameter-specific context. There is no filler, and every sentence or argument note contributes to understanding the tool.

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 the description need not explain return values. However, for a search tool with no annotations, the definition is incomplete regarding when to use it versus alternatives, search cost/permissions, and full parameter formats. It is adequate but leaves meaningful gaps.

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?

Schema description coverage is 0%, so the description must compensate. It partially does: 'sourcetype' is marked optional and 'time_span' includes useful examples like '15m' and '1h'. However, 'index: Index to analyze' is near-tautological, and 'earliest_time: Earliest search window' omits format and default details such as '-24h@h'.

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 uses a specific verb and resource: 'Detect time gaps in ingested data streams where expected events are missing.' This clearly identifies the tool as a gap-detection search rather than a general search or ingestion-health check, but it does not explicitly differentiate itself from related siblings such as splunk_check_source_coverage or splunk_get_data_freshness.

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?

The description states the tool's purpose but provides no explicit guidance on when to use it versus alternatives, no prerequisites, and no exclusions. The Args section lists parameters only, leaving the agent to infer the operational context.

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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