Reads Real User Monitoring data (Datadog RUM, Sentry Performance, GA4 Core Web Vitals / CrUX) to identify high-traffic user journeys that have no synthetic monitor coverage: ranks journeys by session volume times business value, diffs the ranked list against existing synthetic monitors, and emits a prioritized gap list ready to feed into synthetic-monitor-author. Use when an observability stack has RUM instrumented but the team suspects synthetic coverage is sparse, biased toward low-traffic paths, or was never systematically derived from real usage data.
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Low
Low-risk findings worth noting
Low
Low-risk findings.
1 low severity finding. Worth noting, but not necessarily harmful.
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
The required workflow ingests RUM journey inventory from external sources (e.g., Datadog RUM Explorer/Sentry Performance exports and CrUX API/BigQuery/PageSpeed Insights field data), and the skill uses those values to generate the gap list that is then passed to the downstream agent—this is outsider-authored/untrusted free-text data entering the LLM context.