Observability engineer

Skill IrfanSadiqRahat/constellation/agents/observability-engineer

200 role-specific AI agents across 20 teams with typed artifact pipelines, 14 methodology skills, and 15 pre-baked team formations. The virtual engineering org for Claude Code, Cursor, Codex CLI.

Install

npx -y skills add IrfanSadiqRahat/constellation --skill observability-engineer

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What its author says it does

Copied from the file, not written here

Metrics, logs, traces, dashboards, alerts, RUM, exemplars.

SKILL.md

1.5 KB, 366 tokens by cl100k_base, as published. Nobody here has run it

observability-engineer

The deliverable: `ObservabilityStack`

pillars:
  metrics: <prometheus/datadog/honeycomb>
  logs: <vector/fluentbit/loki>
  traces: <otel + backend>
  rum: <provider>
  profiles: <continuous profiling>
collection: otel
sampling: { traces: 1-10%, errors: 100%, head/tail policy }
cardinality_budget: <per-service caps>
dashboards:
  per_service: golden_signals_ladder
  per_user_journey: <slo-aligned>
alerts:
  symptom_based: yes
  page_vs_ticket: <rule>
on_call_dashboards: <links>
log_retention: { hot, cold }
exemplars: linked_trace_per_metric
cost_budget: <per month>

Operating principles

Three pillars, one trace id. Logs / metrics / traces correlated by request id.
Sample smart. 100% errors, sample successes by latency tail.
Cardinality is the enemy. Per-user dimensions kill metrics systems.
Golden signals first. Latency, traffic, errors, saturation.
User-journey dashboards beat per-service when you're paging.
Exemplars on every metric. "Show me one of these slow requests" is one click.
Logs without trace ids are noise.
Cost is observed. Observability over budget is a self-inflicted DoS.

Hand-off contract

sre-lead consumes for SLO computation. incident-commander uses dashboards as truth. appsec-engineer cross-correlates security telemetry.

Gives 0 of the 12 instructions most monitoring observability skills give in 366 tokens

Counted across 481 of the 483 authors here whose files we hold, read 2026-08-06

link every alert to a runbookin 43 of 481, across 35 files
use structured json loggingin 36 of 481, across 31 files
alert on user-facing symptomsin 20 of 481, across 15 files
emit structured JSON logs with stable event namesin 18 of 481, across 13 files
propagate trace context across boundariesin 16 of 481
use histograms for latency trackingin 14 of 481, across 9 files
use OpenTelemetry for distributed tracingin 13 of 481, across 8 files
include a correlation ID on every log linein 13 of 481, across 8 files
Define service level objectivesin 10 of 481, across 7 files
Call useAzureMonitor before importing other modulesin 9 of 481, across 2 files
stop and ask for clarification if inputs are missingin 9 of 481, across 2 files
define on-call questions before adding telemetryin 9 of 481, across 4 files

Said here and by no other author read

record all errors
sample successes by latency tail
cap metric cardinality per service
prioritize golden signals on dashboards
align user journey dashboards to service level objectives
base alerts on symptoms

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.