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Found 253 Skills
Set up Apollo.io monitoring and observability. Use when implementing logging, metrics, tracing, and alerting for Apollo integrations. Trigger with phrases like "apollo monitoring", "apollo metrics", "apollo observability", "apollo logging", "apollo alerts".
Project analysis tool designed to analyze the system architecture and inter-module data flow of codebases. This skill applies when you need to understand project structure, generate architecture diagrams, analyze data flow between modules, or create sequence diagrams. It supports outputting visual charts using Mermaid syntax. Use cases: (1) Project architecture organization (2) Module dependency analysis (3) Data flow tracing (4) New team member project onboarding (5) Technical document generation
Zig debugging skill. Use when debugging Zig programs with GDB or LLDB, interpreting Zig runtime panics, using std.debug.print for tracing, configuring debug builds, or debugging Zig programs in VS Code. Activates on queries about debugging Zig, Zig panics, zig gdb, zig lldb, std.debug.print, Zig stack traces, or Zig error return traces.
Observability patterns for metrics, logging, distributed tracing, and error tracking. Trigger: When setting up monitoring, when implementing logging, when adding error tracking, when configuring distributed tracing, when building health checks, when creating dashboards.
Full Sentry SDK setup for Apple platforms (iOS, macOS, tvOS, watchOS, visionOS). Use when asked to "add Sentry to iOS", "add Sentry to Swift", "install sentry-cocoa", or configure error monitoring, tracing, profiling, session replay, or logging for Apple applications. Supports SwiftUI and UIKit.
Instrument a Java application with the Elastic Distribution of OpenTelemetry (EDOT) Java agent for automatic tracing, metrics, and logs. Use when adding observability to a Java service that has no existing APM agent.
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes - four-phase framework with built-in backward tracing for deep-stack failures, ensuring root-cause understanding before implementation
Master dispatcher for all MLflow workflows. Use this skill when the user wants to do anything with MLflow — tracing, evaluating, debugging, or improving an agent. Routes to the right MLflow sub-skill automatically. Triggers on: "use mlflow", "help with mlflow", "mlflow agent", "add mlflow to my project", "trace my agent", "evaluate my agent", or any MLflow task without a specific skill in mind.
Maps high-level crypto crime categories, safe and ethical OSINT plus on-chain investigation workflow, and victim reporting posture. Use when the user asks about scam types, pig butchering, rug pulls, tracing stolen funds ethically, compliance-adjacent investigation, or how to document cases for authorities.
Set up orq.ai observability for LLM applications. Use when setting up tracing, adding the AI Router proxy, integrating OpenTelemetry, auditing existing instrumentation, or enriching traces with metadata.
Comprehensive logging and observability patterns for production systems including structured logging, distributed tracing, metrics collection, log aggregation, and alerting. Triggers for this skill - log, logging, logs, trace, tracing, traces, metrics, observability, OpenTelemetry, OTEL, Jaeger, Zipkin, structured logging, log level, debug, info, warn, error, fatal, correlation ID, span, spans, ELK, Elasticsearch, Loki, Datadog, Prometheus, Grafana, distributed tracing, log aggregation, alerting, monitoring, JSON logs, telemetry.
Instrument applications with OpenTelemetry SDK and validate telemetry using Kopai. Use when setting up observability, adding tracing/logging/metrics, testing instrumentation, or debugging missing telemetry data.