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Found 389 Skills
Manage Alibaba Cloud Performance Testing Service (PTS) via OpenAPI/SDK. Use for scene lifecycle operations, test start/stop control, report retrieval, and metadata-driven API discovery before production changes.
Migrate a .NET application from the classic Elastic APM .NET agent to the EDOT .NET SDK. Use when switching from Elastic.Apm.* packages to Elastic.OpenTelemetry.
Migrate a Python application from the classic Elastic APM Python agent to the EDOT Python agent. Use when switching from elastic-apm to elastic-opentelemetry.
Analyzes Claude Code session transcripts (JSONL files) to reveal context window content, token usage patterns, and decision-making processes using view_session_context.py tool. Use when debugging Claude behavior, investigating token patterns, tracking agent delegation, or analyzing context exhaustion. Triggers on "why did Claude do X", "analyze session", "check session logs", "context window exhaustion", or "track agent delegation".
Parses OpenTelemetry-formatted logs to reconstruct execution traces, extract errors with call chains, and provide AI-powered root cause analysis. Use when investigating errors, checking logs, debugging issues, viewing traces, or analyzing execution flow. Triggers on "check the logs", "analyze errors", "what's failing", "debug this issue", "show me the traces", or "investigate the error".
OpenTelemetry, structured logging, distributed tracing, alerting, and dashboards
Structured JSON logging with correlation IDs, request context propagation across async boundaries, performance timing decorators, and worker metrics collection.
Expert SRE investigator for incidents and debugging. Uses hypothesis-driven methodology and systematic triage. Can query Axiom observability when available. Use for incident response, root cause analysis, production debugging, or log investigation.
Expert DevOps troubleshooter specializing in rapid incident response, advanced debugging, and modern observability. Masters log analysis, distributed tracing, Kubernetes debugging, performance optimization, and root cause analysis. Handles production outages, system reliability, and preventive monitoring. Use PROACTIVELY for debugging, incident response, or system troubleshooting.
Complete reference for the Portkey AI Gateway Python SDK with unified API access to 200+ LLMs, automatic fallbacks, caching, and full observability. Use when building Python applications that need LLM integration with production-grade reliability.
OpenInference semantic conventions and instrumentation for Phoenix AI observability. Use when implementing LLM tracing, creating custom spans, or deploying to production.
Create and manage production Grafana dashboards for real-time visualization of system and application metrics. Use when building monitoring dashboards, visualizing metrics, or creating operational observability interfaces.