# Opentelemetry Observability > Opentelemetry Observability - Skill: `majiayu000/opentelemetry-observability` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds add majiayu000/opentelemetry-observability` - Raw SKILL.md: https://api.skillmd.com/api/skills/majiayu000/opentelemetry-observability/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - Author: majiayu000 (https://skillmd.com/u/majiayu000) - Updated: 2026-09-09 - Page: https://skillmd.com/skills/majiayu000/opentelemetry-observability --- /*============================================================================*/ /* OPENTELEMETRY-OBSERVABILITY SKILL :: VERILINGUA x VERIX EDITION */ /*============================================================================*/ --- name: opentelemetry-observability version: 1.0.0 description: | [assert|neutral] OpenTelemetry specialist for distributed tracing, metrics collection, log correlation, auto-instrumentation, custom spans, trace context propagation, and sampling strategies. Use when implementing obs [ground:given] [conf:0.95] [state:confirmed] category: Observability tags: - general author: system cognitive_frame: primary: aspectual goal_analysis: first_order: "Execute opentelemetry-observability workflow" second_order: "Ensure quality and consistency" third_order: "Enable systematic Observability processes" --- /*----------------------------------------------------------------------------*/ /* S0 META-IDENTITY */ /*----------------------------------------------------------------------------*/ [define|neutral] SKILL := { name: "opentelemetry-observability", category: "Observability", version: "1.0.0", layer: L1 } [ground:given] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S1 COGNITIVE FRAME */ /*----------------------------------------------------------------------------*/ [define|neutral] COGNITIVE_FRAME := { frame: "Aspectual", source: "Russian", force: "Complete or ongoing?" } [ground:cognitive-science] [conf:0.92] [state:confirmed] ## Kanitsal Cerceve (Evidential Frame Activation) Kaynak dogrulama modu etkin. /*----------------------------------------------------------------------------*/ /* S2 TRIGGER CONDITIONS */ /*----------------------------------------------------------------------------*/ [define|neutral] TRIGGER_POSITIVE := { keywords: ["opentelemetry-observability", "Observability", "workflow"], context: "user needs opentelemetry-observability capability" } [ground:given] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S3 CORE CONTENT */ /*----------------------------------------------------------------------------*/ # OpenTelemetry Observability Specialist ## Kanitsal Cerceve (Evidential Frame Activation) Kaynak dogrulama modu etkin. Expert distributed tracing, metrics, and logging with OpenTelemetry for production observability. ## Purpose Comprehensive OpenTelemetry expertise including auto-instrumentation, custom spans, metrics collection, log correlation, trace context propagation, and sampling. Ensures applications are fully observable with actionable telemetry data. ## When to Use - Implementing distributed tracing in microservices - Monitoring application performance (APM) - Debugging production issues across services - Setting up metrics collection and dashboards - Correlating logs with traces - Optimizing sampling strategies for cost/performance - Migrating from proprietary APM to OpenTelemetry ## Prerequisites **Required**: Understanding of distributed systems, HTTP, basic observability concepts **Agents**: `cicd-engineer`, `perf-analyzer`, `backend-dev`, `system-architect` ## Core Workflows ### Workflow 1: Node.js Auto-Instrumentation **Step 1: Install OpenTelemetry Packages** ```bash npm install @opentelemetry/sdk-node \ @opentelemetry/auto-instrumentations-node \ @opentelemetry/exporter-trace-otlp-http \ @opentelemetry/exporter-metrics-otlp-http ``` **Step 2: Initialize OpenTelemetry** ```javascript // instrumentation.js const { NodeSDK } = require('@opentelemetry/sdk-node'); const { getNodeAutoInstrumentations } = require('@opentelemetry/auto-instrumentations-node'); const { OTLPTraceExporter } = require('@opentelemetry/exporter-trace-otlp-http'); const { OTLPMetricExporter } = require('@opentelemetry/exporter-metrics-otlp-http'); const { Resource } = require('@opentelemetry/resources'); const { SemanticResourceAttributes } = require('@opentelemetry/semantic-conventions'); const sdk = new NodeSDK({ resource: new Resource({ [SemanticResourceAttributes.SERVICE_NAME]: 'my-service', [SemanticResourceAttributes.SERVICE_VERSION]: '1.0.0', [SemanticResourceAttributes.DEPLOYMENT_ENVIRONMENT]: 'production', }), traceExporter: new OTLPTraceExporter({ url: 'http://localhost:4318/v1/traces', }), metricReader: new PeriodicExportingMetricReader({ exporter: new OTLPMetricExporter({ url: 'http://localhost:4318/v1/metrics', }), exportIntervalMillis: 60000, }), instrumentations: [ getNodeAutoInstrumentations({ '@opentelemetry/instrumentation-http': { enabled: true }, '@opentelemetry/instrumentation-express': { enabled: true }, '@opentelemetry/instrumentation-pg': { enabled: true }, '@opentelemetry/instrumentation-redis': { enabled: true }, }), ], }); sdk.start(); process.on('SIGTERM', () => { sdk.shutdown().then( () => console.log('Tracing terminated'), (err) => console.log('Error terminating tracing', err) ); }); ``` **Step 3: Start Application with Instrumentation** ```bash node --require ./instrumentation.js app.js ``` ### Workflow 2: Custom Spans and Attributes ```javascript const { trace } = require('@opentelemetry/api'); const tracer = trace.getTracer('my-service', '1.0.0'); async function processOrder(orderId) { const span = tracer.startSpan('processOrder', { attributes: { 'order.id': orderId, 'order.priority': 'high', }, }); try { // Set span status span.setStatus({ code: SpanStatusCode.OK }); // Add event to span span.addEvent('order_validated', { 'validation.result': 'success', }); // Child span const childSpan = tracer.startSpan('calculateTotal', { parent: span, }); const total = await calculateTotal(orderId); childSpan.setAttribute('order.total', total); childSpan.end(); return total; } catch (error) { // Record exception span.recordException(error); span.setStatus({ code: SpanStatusCode.ERROR, message: error.message, }); throw error; } finally { span.end(); } } ``` ### Workfl /*----------------------------------------------------------------------------*/ /* S4 SUCCESS CRITERIA */ /*----------------------------------------------------------------------------*/ [define|neutral] SUCCESS_CRITERIA := { primary: "Skill execution completes successfully", quality: "Output meets quality thresholds", verification: "Results validated against requirements" } [ground:given] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S5 MCP INTEGRATION */ /*----------------------------------------------------------------------------*/ [define|neutral] MCP_INTEGRATION := { memory_mcp: "Store execution results and patterns", tools: ["mcp__memory-mcp__memory_store", "mcp__memory-mcp__vector_search"] } [ground:witnessed:mcp-config] [conf:0.95] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S6 MEMORY NAMESPACE */ /*----------------------------------------------------------------------------*/ [define|neutral] MEMORY_NAMESPACE := { pattern: "skills/Observability/opentelemetry-observability/{project}/{timestamp}", store: ["executions", "decisions", "patterns"], retrieve: ["similar_tasks", "proven_patterns"] } [ground:system-policy] [conf:1.0] [state:confirmed] [define|neutral] MEMORY_TAGGING := { WHO: "opentelemetry-observability-{session_id}", WHEN: "ISO8601_timestamp", PROJECT: "{project_name}", WHY: "skill-execution" } [ground:system-policy] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S7 SKILL COMPLETION VERIFICATION */ /*----------------------------------------------------------------------------*/ [direct|emphatic] COMPLETION_CHECKLIST := { agent_spawning: "Spawn agents via Task()", registry_validation: "Use registry agents only", todowrite_called: "Track progress with TodoWrite", work_delegation: "Delegate to specialized agents" } [ground:system-policy] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S8 ABSOLUTE RULES */ /*----------------------------------------------------------------------------*/ [direct|emphatic] RULE_NO_UNICODE := forall(output): NOT(unicode_outside_ascii) [ground:windows-compatibility] [conf:1.0] [state:confirmed] [direct|emphatic] RULE_EVIDENCE := forall(claim): has(ground) AND has(confidence) [ground:verix-spec] [conf:1.0] [state:confirmed] [direct|emphatic] RULE_REGISTRY := forall(agent): agent IN AGENT_REGISTRY [ground:system-policy] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* PROMISE */ /*----------------------------------------------------------------------------*/ [commit|confident] OPENTELEMETRY_OBSERVABILITY_VERILINGUA_VERIX_COMPLIANT [ground:self-validation] [conf:0.99] [state:confirmed]