> browse/registry

> error-monitoring

Analyze application error logs and monitoring platform exports (Sentry, Datadog, Rollbar) to identify error patterns, duplicates, and severity. Use when someone asks to "audit errors", "analyze exceptions", "find noisy alerts", "deduplicate error groups", or "triage production errors". Parses JSON/CSV error exports and produces categorized reports with root cause analysis.

> hedgefundmonitor

Query the OFR (Office of Financial Research) Hedge Fund Monitor API for hedge fund data including SEC Form PF aggregated statistics, CFTC Traders in Financial Futures, FICC Sponsored Repo volumes, and FRB SCOOS dealer financing terms. Access time series data on hedge fund size, leverage, counterparties, liquidity, complexity, and risk management. No API key or registration required. Use when working with hedge fund data, systemic risk monitoring, financial stability research, hedge fund leverage

> pytorch-lightning

Deep learning framework (PyTorch Lightning). Organize PyTorch code into LightningModules, configure Trainers for multi-GPU/TPU, implement data pipelines, callbacks, logging (W&B, TensorBoard), distributed training (DDP, FSDP, DeepSpeed), for scalable neural network training.

> x-tweet-fetcher

Fetch tweets, replies, and user timelines from X/Twitter without login or API keys. Also supports Chinese platforms (Weibo, Bilibili, CSDN, WeChat). Includes camofox_search() for zero-cost Google search without API keys. Basic tweet fetching: zero dependencies. Replies/timelines/search: requires Camofox. NEW: X-Tracker for tweet growth monitoring with burst detection.

> spring-boot-observability

Standards for Micrometer, Distributed Tracing, and Structured Logging. Use when adding Micrometer metrics, distributed tracing, or structured logging to Spring Boot. (triggers: logback-spring.xml, application.properties, micrometer, tracing, correlation-id, mdc)

> common-observability

Standards for structured logging, distributed tracing, and metrics. (triggers: **/*.service.ts, **/*.handler.ts, **/*.middleware.ts, **/*.interceptor.ts, **/*.go, **/*.java, **/*.kt, **/*.py, logging, tracing, metrics, opentelemetry, observability, slo)

> golang-logging

Standards for structured logging and observability in Golang. Use when adding structured logging or tracing to Go services. (triggers: go.mod, pkg/logger/**, logging, slog, structured logging, zap)

> Debugging Expert

Systematic troubleshooting using the Scientific Method. Use when debugging crashes, tracing errors, diagnosing unexpected behavior, or investigating exceptions.

> common-debugging

Systematic troubleshooting using the Scientific Method. Use when debugging crashes, tracing errors, diagnosing unexpected behavior, or investigating exceptions. (triggers: debug, fix bug, crash, error, exception, troubleshooting)

> nestjs-observability

Structured logging (Pino) and Prometheus metrics. Use when adding structured logging with Pino or Prometheus metrics to NestJS services. (triggers: main.ts, **/*.module.ts, nestjs-pino, Prometheus, Logger, reqId)

> alphaear-signal-tracker

Track finance investment signal evolution and update logic based on new finance market information. Use when monitoring finance signals and determining if they are strengthened, weakened, or falsified.

> cloudwatch

AWS CloudWatch monitoring for logs, metrics, alarms, and dashboards. Use when setting up monitoring, creating alarms, querying logs with Insights, configuring metric filters, building dashboards, or troubleshooting application issues.

> android-emulator-skill

Production-ready scripts for Android app testing, building, and automation. Provides semantic UI navigation, build automation, log monitoring, and emulator lifecycle management. Optimized for AI agents with minimal token output.

> dashboard-creator

Create HTML dashboards with KPI metric cards, bar/pie/line charts, progress indicators, and data visualizations. Use when users request dashboards, metrics displays, KPI visualizations, data charts, or monitoring interfaces.

> sentry

Use when the user asks to inspect Sentry issues or events, summarize recent production errors, or pull basic Sentry health data via the Sentry API; perform read-only queries with the bundled script and require `SENTRY_AUTH_TOKEN`.

> metrics-dashboard

Define and design a product metrics dashboard with key metrics, data sources, visualization types, and alert thresholds. Use when creating a metrics dashboard, defining KPIs, setting up product analytics, or building a data monitoring plan.

> devops-infrastructure

Guides Docker, CI/CD pipelines, deployment strategies, infrastructure as code, and observability setup. Use when writing Dockerfiles, configuring GitHub Actions, planning deployments, setting up monitoring, or when asked about containers, pipelines, Terraform, or production infrastructure.

> error-handling

Implements error handling patterns, structured logging, retry strategies, circuit breakers, and graceful degradation. Use when designing error handling, setting up logging, implementing retries, adding error tracking, or when asked about error boundaries, log aggregation, alerting, or resilience patterns.

> sentry

Inspect Sentry issues, summarize production errors, and pull health data via the Sentry API (read-only). Use when user says "check Sentry", "what errors in production?", "summarize Sentry issues", "recent crashes", or "production error report". Requires SENTRY_AUTH_TOKEN. Do NOT use for setting up Sentry SDK, configuring alerts, or non-Sentry error monitoring.

> collecting-infrastructure-metrics

This skill enables Claude to collect comprehensive infrastructure performance metrics across compute, storage, network, containers, load balancers, and databases. It is triggered when the user requests "collect infrastructure metrics", "monitor server performance", "set up performance dashboards", or needs to analyze system resource utilization. The skill configures metrics collection, sets up aggregation, and helps create infrastructure dashboards for health monitoring and capacity tracking. It