monitoring-observability
Skill1 starsChanged 5 days agoMITView on GitHub
Monitoring and observability patterns for Prometheus metrics, Grafana dashboards, Langfuse v4 LLM tracing (as_type, score_current_span, should_export_span, LangfuseMedia), and drift detection. Use when adding logging, metrics, distributed tracing, LLM cost tracking, or quality drift monitoring. Only invoke via the orcinus router.
6 other projects use a version of this.
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- valentinesamuel/claude-skillstheir own version, first seen Nov 8, 2026
- komluk/scaffoldingtheir own version, first seen Nov 7, 2026
- mawero83/google-sre-skillstheir own version, first seen Nov 1, 2026
- eliabdevweb-svg/opencode-skills-MCPtheir own version, first seen Oct 9, 2026
- 2867203296/hermes-agenttheir own version, first seen Aug 19, 2026
- travisjneuman/.claudetheir own version, first seen Feb 25, 2026
Other versions6 projects use a version of this.
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Wrote their own version · 6
- travisjneuman/.claude★ 106same name
- mawero83/google-sre-skills★ 18same name
- komluk/scaffolding★ 16same name
- valentinesamuel/claude-skills★ 1same name
- 2867203296/hermes-agent★ 0same name
- eliabdevweb-svg/opencode-skills-MCP★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
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The file
Files
Monitoring & Observability
A wrap around Prometheus, Grafana, OpenTelemetry and Langfuse, not a re-teaching of them. This
skill carries OrchestKit's delta (version floors, house decisions, scars) and points at the
vendor for everything else. Start at references/ork-delta.md.
Upstream coverage (do not restate)
These topics are fully covered first-party. Read the source, do not add a local copy.
| Topic | First-party source |
| Prometheus metric types, RED method, cardinality, PromQL | https://prometheus.io/docs/practices/ |
| Alertmanager grouping, inhibition, escalation, runbooks | https://prometheus.io/docs/alerting/latest/configuration/ |
| Grafana dashboards, Loki and LogQL, Promtail | https://grafana.com/docs/ |
| OpenTelemetry spans, sampling, context propagation | https://opentelemetry.io/docs/ |
Langfuse Python SDK (@observe, as_type, score_current_span, should_export_span, LangfuseMedia) | https://langfuse.com/docs/sdk/python |
| Langfuse v2 to v4 Python and v3 to v5 JS migration paths | https://langfuse.com/docs/sdk/python/v4-migration |
| Langfuse self-hosting (ClickHouse, Redis, S3, Helm) | https://langfuse.com/docs/deployment/self-host |
| Langfuse cost tracking, model pricing, Metrics API v2 | https://langfuse.com/docs/model-usage-and-cost |
| Langfuse scores, online evaluators, annotation queues, prompt management | https://langfuse.com/docs/scores/overview |
| Langfuse framework integrations (LangChain, LangGraph, CrewAI, Pydantic AI, Bedrock, LiveKit) | https://langfuse.com/docs/integrations |
| Agent Graphs, observation types, rendered tool calls | https://langfuse.com/docs/tracing-features/agent-graphs |
| PSI, KS test, KL and JS divergence, Wasserstein, embedding drift | https://www.evidentlyai.com/blog/data-drift-detection-large-datasets |
| EWMA control charts | https://www.itl.nist.gov/div898/handbook/pmc/section3/pmc324.htm |
| structlog, Winston, correlation IDs, log sampling | https://www.structlog.org/en/stable/ |
Quick Reference
| Category | Rules | Impact | When to Use |
| Infrastructure Monitoring | 1 | CRITICAL | Grafana dashboards, Golden Signals, SLO/SLI |
| LLM Observability | 1 | HIGH | Langfuse tracing, observation types, agent graphs |
| Silent Failures | 3 | HIGH | Tool skipping, quality degradation, loop/token spike alerting |
Total: 5 rules across 3 categories. Drift detection, cost tracking, eval scoring, Prometheus instrumentation and alert-rule authoring moved to the upstream sources listed above.
Quick Start
# Langfuse v4 LLM tracing: semantic as_type plus inline scoring
from langfuse import observe, get_client
@observe(as_type="generation", name="analyze_content")
async def analyze_content(content: str):
get_client().update_current_trace(
user_id="user_123", session_id="session_abc",
tags=["production", "orchestkit"],
)
result = await llm.generate(content)
get_client().score_current_span(name="response_quality", value=0.85)
return result# Prometheus RED method, wired the way this repo expects (bounded labels only)
from prometheus_client import Counter, Histogram
http_requests = Counter('http_requests_total', 'Total requests', ['method', 'endpoint', 'status'])
http_duration = Histogram('http_request_duration_seconds', 'Request latency',
buckets=[0.01, 0.05, 0.1, 0.5, 1, 2, 5])Infrastructure Monitoring
Dashboard and health-check patterns. Metric instrumentation and alert-rule syntax are upstream.
| Rule | File | Key Pattern |
| Grafana Dashboards | rules/monitoring-grafana.md | Golden Signals, SLO/SLI, health checks |
CC 2.1.161 — OTEL resource attributes as metric labels:
OTEL_RESOURCE_ATTRIBUTESvalues are now attached as labels on metric datapoints, so usage metrics can be sliced by custom dimensions (team, repo, environment). Add label selectors to dashboards for multi-tenant / per-team cost and usage tracking.
LLM Observability
Langfuse-based tracing for LLM applications. Cost tracking, scoring and drift statistics are upstream; what stays here is how this repo wires traces.
| Rule | File | Key Pattern |
| Langfuse Traces | rules/llm-langfuse-traces.md | @observe decorator, OTEL spans, agent graphs |
Silent Failures
Detection and alerting for silent failures in LLM agents.
| Rule | File | Key Pattern |
| Tool Skipping | rules/silent-tool-skipping.md | Expected vs actual tool calls, Langfuse traces |
| Quality Degradation | rules/silent-degraded-quality.md | Heuristics + LLM-as-judge, z-score baselines |
| Silent Alerting | rules/silent-alerting.md | Loop detection, token spikes, escalation workflow |
CC 2.1.169 — OTEL client-cert paths require trust: untrusted project settings can no longer set OTEL client-certificate paths without a trust confirmation. If your OTEL exporter uses client certs configured in project
.claude/settings.json, expect a one-time trust prompt on first use in an untrusted project — telemetry silently not flowing after 2.1.169 is usually this gate, not the collector.
Key Decisions
| Decision | Recommendation | Rationale |
| Metric methodology | RED method (Rate, Errors, Duration) | Industry standard, covers essential service health |
| Log format | Structured JSON | Machine-parseable, supports log aggregation |
| Tracing | OpenTelemetry | Vendor-neutral, auto-instrumentation, broad ecosystem |
| LLM observability | Langfuse (not LangSmith) | Open-source, self-hosted, built-in prompt management |
| LLM tracing API | @observe(as_type=...) + score_current_span() | v4: semantic types, inline scoring, span filtering |
| Langfuse APIs | Observations API v2 + Metrics API v2 | v4 (Mar 2026): faster querying, aggregations at scale |
| Hook telemetry transport | JSONL under ~/.claude/analytics/, never an SDK in-process | Hooks are per-event processes; SDK init would be paid on every spawn (references/ork-delta.md) |
Detailed Documentation
| Resource | Description |
references/ork-delta.md | Start here. Floors, house decisions and scars that upstream docs do not carry |
references/langfuse-js-v5.md | JS/TS SDK v5 delta from Python 4.x: package map, phantom packages, SpanProcessor vs exporter. Read before writing any JS Langfuse code |
references/experiments-api.md | Langfuse experiments and dataset runs as this repo uses them |
references/evaluation-scores.md | Score shapes and scoring pipeline wiring |
references/session-tracking.md | Session and user grouping across multi-step workflows |
references/metrics-collection.md | Claude Code OTEL metric inventory and collector-side joins |
references/dashboards.md | Dashboard layout conventions |
references/structured-logging.md | Structured log field conventions |
references/dev-agent-lens.md | LiteLLM proxy layer (or Bifrost) for API-boundary observability |
examples/orchestkit-monitoring-dashboard.md | Worked monitoring dashboard example |
scripts/ | Templates: Prometheus, OpenTelemetry, health checks, Langfuse |
Related Skills
<!-- ORCINUS change notice (2026-11-08, round 7, N5): upstream
listed five OrchestKit siblings here (defense-in-depth,
devops-deployment, resilience-patterns, llm-evaluation, caching);
none of them exists in ORCINUS, so the links pointed nowhere in
every install. Replaced with the in-repo sibling `monitoring`.
See ATTRIBUTION.md. -->monitoring- The outside view of a shipped service: uptime probes, SLO burn-rate alerts, on-call escalation. The complement of this skill — this skill instruments from the inside (what the app emits: logs, metrics, traces),monitoringdetects from the outside (is it alive, is it fast). The router routes "Health / monitoring" tomonitoringand "Telemetry / instrumentation" here.
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