Log Analyzer
Diagnose production incidents by correlating logs across services
by myriadprotocolTechnology & SoftwareEngineeringSite Reliability Engineer (standalone)Incident ManagementWhat You Can Do
You can rapidly diagnose production incidents by uploading logs from multiple sources—application servers, databases, network infrastructure—and Claude will identify error patterns, correlate events across services to establish causality, extract key metrics and anomalies, and produce a structured timeline of what went wrong. This transforms raw log data into actionable incident reports with clear root cause identification and remediation priorities.
Features
automatically identifies error signatures and clusters related events from application, system, database, and network logs
establishes causality by correlating events across services with timestamps to show which failure triggered downstream impact
groups similar errors and anomalies to reveal the true scope and frequency of issues
visualizes how failures cascade through microservices and dependent systems
identifies threshold violations, performance degradation, and resource utilization spikes
produces structured chronological narrative with evidence links showing exactly what happened and when
synthesizes log patterns to pinpoint the triggering event and contributing factors
recommends fixes ranked by impact and urgency
Example Output
Example 1: API Service Outage
INCIDENT TIMELINE
09:15:23 — Database connection pool exhausted (PostgreSQL logs)
09:15:45 — API timeout errors spike to 87% (application logs)
09:16:12 — Load balancer marks all API instances unhealthy (infrastructure logs)
09:18:00 — Cache layer shows 0 hits, all requests hitting database (cache logs)
ROOT CAUSE: Deployment at 09:14:58 introduced N+1 query bug. Combined with cache flush during deployment, DB connection pool saturated within 90 seconds.
MITIGATION: Revert deployment, repopulate cache, monitor connection pool.
Example 2: Intermittent Payment Processing Failures
ERROR PATTERN ANALYSIS
Error Type: "timeout connecting to payment gateway"
Frequency: 8.3% of transactions between 09:00–11:30 UTC
Correlated Events: Network latency spike to payment provider (50ms → 2.5s) + circuit breaker opening after 3 consecutive timeouts
SERVICE IMPACT MAP
Payment Service → Retry Queue → Notification Service → Customer Alerts
ACTION ITEMS
1. Increase circuit breaker timeout threshold (1s → 3s)
2. Investigate network path to payment provider
3. Implement exponential backoff on retries
What's Included
- log-analyzer SKILL.md: Core instruction file with pattern recognition algorithms and analysis frameworks
- Multi-source log parsing template: Structure for ingesting logs from application servers, databases, containers, and infrastructure
- Incident timeline reconstruction checklist: Step-by-step format for establishing event causality and impact mapping
- Error pattern clustering worksheet: Framework for grouping similar failures and extracting root causes
- Service dependency impact worksheet: Template for visualizing how failures cascade across microservices
Who It's For
- DevOps Engineers — diagnosing production incidents and post-incident root cause analysis
- SRE/Platform Engineers — systematic troubleshooting and incident timeline reconstruction
- Backend Engineers — understanding application failure modes during active incidents
- On-call responders — rapid triage and diagnosis during incident response
- Infrastructure/Systems Engineers — correlating infrastructure events with application failures
Best For
- Active incident diagnosis — application errors, service failures, or performance degradation requiring rapid root cause identification
- Post-incident analysis — understanding what happened, when, and why after a resolved outage
- Cross-service failures — issues spanning multiple microservices requiring event correlation
- Error spike investigation — sudden increases in error rate with unknown cause
- Performance degradation troubleshooting — response time increases, throughput drops, or resource exhaustion without obvious triggers
You might also like
You'll develop systematic approaches to injectable formulation design, from API selection through sterilization strategy. Claude helps you troubleshoot failed batches by analyzing root causes, recommends regulatory pathways (505(b)(2), ANDA, NDA), and provides science-backed solutions for stability, compatibility, and manufacturability challenges.
This skill helps you systematically assess integration needs across your systems, design architecture patterns that scale with your organization, and identify technical and operational risks before implementation. You'll receive architecture recommendations aligned to your business constraints, clear integration roadmaps, and risk mitigation strategies that reduce deployment surprises. Get structured decision records suitable for architecture review boards and engineering teams.
Claude analyzes your code diffs and generates standardized commit messages that follow the Conventional Commits specification. The skill automatically determines the correct commit type, scope, and description based on the changes you've made, ensuring your messages are parseable by automation tools while remaining human-readable for code reviewers.
You can transform raw text into structured, labeled datasets for machine learning, analysis, and research. This skill performs named entity recognition, sentiment classification, part-of-speech tagging, and dependency parsing—generating consistent, validated annotations at scale. Use it to prepare corpora, extract entities, classify documents, or perform linguistic analysis without manual annotation.
This skill helps you systematically analyze service mesh architectures, identify inter-service communication failures, and design optimal routing and security policies. You'll receive step-by-step troubleshooting guidance tailored to your mesh platform (Istio, Linkerd, Consul), configuration validation reports, and architectural recommendations that reduce latency, improve observability, and tighten security posture.
This skill automates the creation of production-ready deployment validation checklists, infrastructure-as-code templates, and incident response runbooks tailored to your ML stack. You get comprehensive pre-deployment checks covering model validation, data pipeline integrity, infrastructure readiness, and monitoring setup—all customized for your specific models and cloud provider. The skill generates executable runbooks that teams can follow during incidents, including rollback procedures, failover strategies, and diagnostic commands.
Build scalable internal developer platform architectures that reduce cognitive load and standardize workflows for your development organization. Document golden paths that guide developers through common tasks like onboarding, deployment, and troubleshooting. Map platform capabilities, integrations, and service topology to align with your engineering scale and technical strategy.
Rapidly analyze firmware logs and diagnose hardware issues that cause device failures, connectivity problems, and performance degradation. You'll identify root causes from stack traces, crash dumps, and sensor data, then generate specific optimization recommendations. This skill transforms raw device logs into actionable debugging plans that reduce time-to-resolution from hours to minutes.