claudecodex

sparklogs

Query and analyze SparkLogs: system and application logs plus device health and state over time, one host or the fleet.

0 on GitHubby IT Lightning, LLCv1.12.8Apache-2.0updated 7 days agoobservability
/

Plugin sparklogs from marketplace sparklogs-ai-plugins in itlightning/sparklogs-ai-plugins. Commands read from the repo's manifest — 6 days ago.

What it installs

Skills (4)

  • sparklogs-analyze-cause

    From a prior SparkLogs investigation summary, derive candidate cause hypotheses with confirm/refute steps and confidence. Use when the engineer wants cause analysis after findings exist.

  • sparklogs-ask

    Query SparkLogs logs and device health/state over time to answer what happened on a host or across a fleet. Counts, timelines, disk, CPU, patches, Windows events, other system and application log events, installed software, collection health. Conversational answers from SparkLogs telemetry.

  • sparklogs-feedback

    Send feedback to SparkLogs about this session (positive, negative, neutral, a bug, or an idea), after the user picks how much detail to include and approves the exact text. Use when the user asks to send feedback. Offer feedback once per session if the user is frustrated or did not get a good result

  • sparklogs-investigate

    Cited SparkLogs investigation: gather logs and device health/state into a structured system-condition summary with query URLs, confidence, and what was not checked. Use when the engineer needs a thorough ticket write-up or a full investigation report.

Slash commands (2)

  • /sparklogs:sparklogs-explain

    Walk a SparkLogs finding or claim back to the evidence behind it.

  • /sparklogs:sparklogs-summary

    Re-render an existing SparkLogs investigation summary for a ticket update.

Subagents (3)

  • sparklogs-cluster-interpreter

    Interprets clustered event-context results and returns concise structured cluster descriptions.

  • sparklogs-log-summarizer

    Reads bulk SparkLogs log events or device-health result-set rows and returns structured findings for the orchestrator.

  • sparklogs-pattern-enumerator

    Enumerates high-volume pattern groups and maps them to likely meanings without drawing final conclusions.

MCP servers (1)

  • sparklogs

    connects to: https://mcp.sparklogs.app/mcp

View source on GitHub sparklogs.com

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