Agent skill · data analytics · jeremylongshore
customerio-observability
Set up Customer.io monitoring and observability.
Why this skill is useful
Adds executable scripts for Prometheus metrics and structured logging specific to Customer.io integrations that aren't in public docs.
What it needs
Requires prom-client installed locally. Requires customerio account access. About 5k tokens when loaded. Last updated 2026-08-07. 2,604 stars on the source repository.
What this skill does
Customer.io Observability Output Bounded metrics and redacted traces for event acceptance, campaign delivery, errors, latency, and rate-limit headroom. An owned alert/runbook path for delivery, authentication, data-quality, and provider incidents. Examples Emit an aggregate counter for accepted events and failures by environment and endpoint, never by email address, customer ID, message body, API key, or full payload. Trigger a staging alert with a harmless test event, verify the on-call route, then restore the normal state and record the alert receipt. Overview Implement comprehensive observability for Customer.io integrations: Prometheus metrics (latency, error rates, delivery funnel), structured JSON logging with PII redaction, OpenTelemetry tracing, and Grafana dashboard definitions. Prerequisites Customer.io integration deployed Prometheus + Grafana (or compatible metrics stack) Structured logging system (pino recommended) Key Metrics to Track Metric Type Description Alert Threshold -------- ------ ------------- ---------------- cioapidurationms Histogram API call latency p99 > 5000ms cioapirequeststotal Counter Total API requests by operation N/A (rate) cioapierrorstotal Counter API errors by status code > 1% error rate cioemailsenttotal Counter Transactional + campaign emails N/A cioemailbouncedtotal Counter Bounce count > 5% of sends cioemailcomplainedtotal Counter Spam complaints > 0.1% of sends ciowebhookreceivedtotal Counter Webhook events by metric type N/A cioqueuedepth Gauge Pending items in event queue > 10K Instructions Step 1: Prometheus Metrics Step 2: Instrumented Client Step 3: Structured Logging with PII Redaction Step 4: Webhook Metrics Collection Step 5: Prometheus Metrics Endpoint Step 6: Grafana Dashboard (JSON Model) Step 7: Alerting Rules Error Handling Issue Solution ------- ---------- High cardinality metrics Don't use userId as a label — use operation + status only Log volume too high Set CUSTOMERIOLOGLEVEL=warn in production Missing me …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills jeremylongshore/customerio-observability