> browse/registry

> 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

> observability-monitoring-monitor-setup

You are a monitoring and observability expert specializing in implementing comprehensive monitoring solutions. Set up metrics collection, distributed tracing, log aggregation, and create insightful da

> clawsec-suite

ClawSec suite manager with embedded advisory-feed monitoring, cryptographic signature verification, approval-gated malicious-skill response, and guided setup for additional security skills.

> monitoring-error-rates

This skill enables Claude to monitor and analyze application error rates to improve reliability. It is used when the user needs to track and understand errors occurring in their application, including HTTP errors, application exceptions, database errors, external API errors, background job errors, and client-side errors. Use this skill when the user asks to "monitor errors", "analyze error rates", "track application errors", or requests help with "error monitoring". It sets up comprehensive erro

> 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)

> robot-bringup

Patterns and best practices for bringing up a complete ROS2-based robotics system on a robot's onboard computer, including systemd services, launch file composition, ordered startup, and production monitoring. Use this skill when configuring a robot to start ROS2 nodes on boot, writing systemd unit files for ROS2 launch, composing layered launch files for full robot stacks, setting up watchdog monitoring, configuring udev rules for deterministic device naming, or debugging boot-time race conditi

> axiom-core-location

Use for Core Location implementation patterns - authorization strategy, monitoring strategy, accuracy selection, background location

> axiom-energy-ref

Complete energy optimization API reference - Power Profiler workflows, timer/network/location/background APIs, iOS 26 BGContinuedProcessingTask, MetricKit monitoring, with all WWDC code examples

> enterprise-agent-ops

Operate long-lived agent workloads with observability, security boundaries, and lifecycle management.

> observability-monitoring-slo-implement

You are an SLO (Service Level Objective) expert specializing in implementing reliability standards and error budget-based practices. Design SLO frameworks, define SLIs, and build monitoring that balances reliability with delivery velocity.

> convex-cron-jobs

Scheduled function patterns for background tasks including interval scheduling, cron expressions, job monitoring, retry strategies, and best practices for long-running tasks

> 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.

> 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.

> managing-database-replication

This skill enables Claude to manage database replication, failover, and high availability configurations using the database-replication-manager plugin. It is designed to assist with tasks such as setting up master-slave replication, configuring automatic failover, monitoring replication lag, and implementing read scaling. Use this skill when the user requests help with "database replication", "failover configuration", "high availability", "replication lag", or "read scaling" for databases like P

> 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.

> implementing-database-audit-logging

This skill helps implement database audit logging for tracking changes and ensuring compliance. It is triggered when the user requests to "implement database audit logging", "add audit trails", "track database changes", or mentions "audit_log" in relation to a database. The skill provides options for trigger-based auditing, application-level logging, Change Data Capture (CDC), and parsing database logs. It generates a basic audit table schema and guides the user through selecting the appropriate

> 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.

> setting-up-experiment-tracking

This skill automates the setup of machine learning experiment tracking using tools like MLflow or Weights & Biases (W&B). It is triggered when the user requests to "track experiments", "setup experiment tracking", "initialize MLflow", or "integrate W&B". The skill configures the necessary environment, initializes the tracking server (if needed), and provides code snippets for logging experiment parameters, metrics, and artifacts. It helps ensure reproducibility and simplifies the comparison of d