Query distributed tracing spans with DataPrime syntax to locate latency and errors.
npx skills add https://github.com/coralogix/cx-cli --skill query-spans
Please help me install this Agent Skill. Skill: query-spans Source: https://github.com/coralogix/cx-cli/tree/main/skills/query-spans Command: npx skills add https://github.com/coralogix/cx-cli --skill query-spans
Query and analyze distributed tracing data to locate latency, slow operations, and errors across services.
Run a cx spans query for your target time window to retrieve matching spans and inspect results.
High-intent search queries and answers about installing and using this skill.
Diagnose latency by querying distributed tracing data to locate slow operations and errors across services. You can filter, group, and aggregate standard span fields like $m.duration and $l.serviceName to pinpoint performance hotspots.
Query spans using DataPrime syntax to investigate errors in production systems. By applying the cx spans command with time-range controls, you can retrieve matching spans and surface errors correlated with logs for incident response.
Filter traces for slow spans using standard span fields such as $m.timestamp, $m.duration, $l.serviceName, $l.operationName, and $d.traceID. These fields allow you to group and aggregate data to derive actionable insights.
You can reconstruct traces to debug cross-service calls by querying spans with DataPrime syntax. Filtering by $d.traceID allows you to retrieve and sequence the relevant spans to visualize the full request path.
DataPrime syntax is used in span analysis to query and filter distributed tracing data. It supports investigating traces and spans by applying deterministic queries across standard span fields to identify latency bottlenecks and errors.
Span queries require time-range controls including start, end, and limit parameters to function deterministically. You must define these parameters to properly retrieve and analyze matching spans within your target time window.
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