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AsiaOstrichAsiaOstrich/EngramGraph/.agents/skills/observability-assistant/SKILL.md

observability

Skill4 starsChanged 29 days agoMITView on GitHub

Guide observability setup, metrics design, and alerting configuration. Use when: new service instrumentation, SLO definition, alert design, maturity assessment. Not for: setting numeric targets and Error Budget policy — use /slo; log format and levels — use /logging-guide. Keywords: observability, metrics, traces, golden signals, alerting, SLO.

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The file

We split this skill into the rules it gives an agent

1 rule. 0 are common, 1 is distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 70 edited versions we read keep these.

  • 1

    Distinctive

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Before deploying a service to production:

    line 103

“Common” is measured: kept by at least 6 in 10 of the 70 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Observability Assistant | 可觀測性助手

Language: English | 繁體中文

Version: 1.0.0 Last Updated: 2026-06-19 Applicability: Claude Code Skills

Core Standard: This skill implements Observability Standards. For the authoritative methodology (full Metrics/Traces detail, sampling, OTel integration), refer to the core standard.

Guide observability implementation across the three pillars: Logs, Metrics, and Traces.

引導三支柱可觀測性實作:Logs、Metrics、Traces。

Capabilities | 功能

CapabilityDescription說明
Instrumentation CheckPre-launch observability checklist上線前可觀測性檢查表
Maturity AssessmentL0-L4 maturity self-evaluationL0-L4 成熟度自評
Metric DesignHelp design metrics (type, naming, labels)協助設計 Metrics
Alert DesignDesign SLO-based alerts with noise reduction設計 SLO-based 告警
Golden SignalsVerify 4 golden signals coverage驗證四大黃金信號覆蓋

Usage | 使用方式

/observability                        # Show observability guide
/observability --checklist            # Run instrumentation checklist
/observability --maturity             # Maturity assessment (L0-L4)
/observability --alerting             # Alert design guide
/observability "payment-service"      # Guide for specific service

Three Pillars Framework | 三支柱框架

Each pillar gives a different lens; their power is in correlation.

PillarWhat It CapturesWhen to UseGranularity
LogsDiscrete events with contextDebugging, audit trails, error detailsHigh (per-event)
MetricsNumerical measurements over timeDashboards, alerting, capacity planningLow (aggregated)
TracesRequest flow across servicesLatency analysis, dependency mappingMedium (per-request)

Correlation fields: trace_id links Logs ↔ Traces ↔ Metrics (via Exemplars); service.name filters all three pillars. Workflow: metric anomaly → exemplar → trace → trace_id in logs.

Golden Signals | 四大黃金信號

Based on Google SRE. Every service SHOULD monitor all four before production.

SignalMeasureExample MetricAlert (SLO-based)
LatencyP50/P95/P99 via Histogram, split success/errorhttp.server.request.duration.secondsP99 > X ms for 5 min
TrafficRequests/sec, by route/methodhttp.server.request.total (rate)drop > 50% or spike > 200%
Errorserrors / total requests...request.total{status=~"5.."} ÷ totalerror rate > X% for 5 min
SaturationCPU/mem/pool/disk utilizationsystem.cpu.utilization (Gauge)resource > 80% for 10 min

Metric Types | Metric 型別

TypeBehaviorUse When
CounterOnly goes up (resets on restart)request count, error count, bytes sent
GaugePoint-in-time, up/downqueue depth, active connections, memory
HistogramDistribution across bucketsrequest duration, response size
SummaryClient-computed percentileslegacy, no server-side aggregation

Naming: <domain>.<entity>.<action>.<unit> in snake_case (e.g. db.client.query.duration.seconds). Label cardinality: keep labels under ~1000 unique values — never use user_id / request_id / raw url / ip as labels; record those in Logs or Traces instead.

Maturity Model (L0–L4) | 成熟度模型

LevelNameCharacteristicsUpgrade Action
L0No Observabilityonly stdout/stderr; debug via SSH + tail -fstructured logging; centralize collection
L1Basic Loggingstructured JSON logs, centralized, searchableadd business metrics; first dashboard
L2Metrics-DrivenLogs + Metrics, dashboards, threshold alertsenable tracing; SLO-based alerting
L3Full Observabilitythree pillars + correlation + SLO alerts + Golden Signalsanomaly detection; auto-remediation
L4IntelligentAIOps anomaly detection, predictive alerts, auto-remediationmaintain, optimize, share learnings

Self-check: find logs for one request across services (L1+) → dashboards of error rate & latency (L2+) → trace request ingress→DB→back (L3+) → auto-detect anomalies before users report (L4).

Instrumentation Checklist | 上線前檢查表

Before deploying a service to production:

  • Structured logging — JSON with trace_id correlation
  • HTTP/gRPC entry metrics — request count, duration histogram, error rate per endpoint
  • Business operation metrics — key events tracked (orders, payments)
  • Distributed tracing — span propagation, sampling rate, W3C Trace Context headers
  • Health checks — liveness (running?) and readiness (can serve?) probes
  • Golden Signals dashboard — Latency, Traffic, Errors, Saturation visualized
  • Alert rules — at minimum SLO burn-rate alerts
  • Log retention — policies set per log level
  • Sensitive data excluded — no passwords, tokens, or PII in logs/traces

Next Steps Guidance | 下一步引導

可觀測性引導完成。建議下一步:

  • 執行 /slo 定義 SLI/SLO/Error Budget ⭐ 推薦
  • 執行 /incident 設定事故回應流程
  • 執行 /checkin 提交變更

Reference | 參考

  • Detailed guide: guide.md — the three pillars (logs, metrics, traces) in depth. Read it when setting up monitoring, choosing metric types, implementing tracing, or assessing maturity.
  • Core standard: observability-standards.md
  • Core standard: alerting-standards.md
  • Core standard: slo-standards.md

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