otel-collector

Expert guidance for configuring and deploying the OpenTelemetry Collector. Use when setting up a Collector pipeline, configuring receivers, exporters, or processors, deploying a Collector to Kubernetes or Docker, or forwarding telemetry to Dash0. Triggers on requests involving collector, pipeline, OTLP receiver, exporter, or Dash0 collector setup.

100

1.36x

Quality

100%

Does it follow best practices?

Impact

100%

1.36x

Average score across 3 eval scenarios

Securityby

Passed

No known issues

Evaluation results

100%

24%

Reliable Telemetry Forwarding for a Payments Microservices Platform

Production pipeline reliability and safety

Criteria

Without context

With context

memory_limiter first

100%

No batch processor

100%

sending_queue with file_storage

100%

No hardcoded token

100%

gzip compression

100%

No debug exporter

100%

Separate signal pipelines

100%

health_check extension

100%

0.0.0.0 bind address

100%

memory_limiter sizing

42%

100%

file_storage extension declared

100%

All declared components used

100%

Kubernetes Telemetry Enrichment for Multi-Cluster Observability

Kubernetes metadata enrichment across signals

Criteria

Without context

With context

Enrichment on all pipelines

100%

k8s.pod.uid first in pod_association

100%

Workload name and UID extracted

100%

resourcedetection override false

100%

resource processor for cluster attributes

100%

Processor ordering: enrichment after memory_limiter

100%

Processor ordering: resource after enrichment

100%

k8sattributes passthrough: false

100%

memory_limiter first

100%

k8s.cluster.uid kube-system reference

100%

No batch processor

100%

48%

SLO-Accurate RED Metrics Alongside Trace Volume Reduction

RED metrics from traces with tail sampling

Criteria

Without context

With context

signaltometrics not spanmetrics

100%

exponential_histogram used

100%

Connector before sampling in pipeline

50%

100%

Metrics pipeline uses connector as receiver

100%

Semconv metric names

100%

Semconv conditions used

62%

100%

service.name in resource attributes

50%

100%

AlwaysOn sampler recommendation

100%

Tail sampling policies include errors and latency

100%

memory_limiter first

55%

100%

No batch processor

100%

Repository: dash0hq/agent-skills
Commit: e73252a

Evaluated: 2 days ago
Agent: Claude Code
Model: Claude Sonnet 4.6

Table of Contents

Reliable Telemetry Forwarding for a Payments Microservices Platform Kubernetes Telemetry Enrichment for Multi-Cluster Observability SLO-Accurate RED Metrics Alongside Trace Volume Reduction

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.