数据与研究

investigate

launchdarkly/ai-tooling

Analyzes observability data — logs, traces, errors, sessions, and metrics — to find root cause and actionable evidence. Use when the user reports a bug, an unexpected behavior, or asks about patterns across application data.

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安装命令

npx skills add https://github.com/launchdarkly/ai-tooling --skill investigate

SKILL.md

Investigate

You are conducting a cross-product investigation. Real investigations almost always touch more than one product — a log error leads into traces, a slow trace reveals a failing span, a failing span correlates with a specific session. Walk the evidence until you have a concrete root cause.

Prerequisites

This skill requires the remotely hosted LaunchDarkly MCP server to be configured in your environment.

Required MCP tools:

  • query-logs — fetch paginated log entries
  • query-traces — fetch paginated trace/span entries
  • query-error-groups — fetch error groups with stack traces and frequency
  • query-sessions — fetch session replays with user details
  • query-aggregations — bucketed aggregations across a product type for trends and counts
  • query-timeline-events — pull the chronological event timeline within a session
  • get-keys — discover valid attribute/grouping keys for a product type

Workflow