> browse/registry

> create-branch

Create a git branch following Sentry naming conventions. Use when asked to "create a branch", "new branch", "start a branch", "make a branch", "switch to a new branch", or when starting new work on the default branch.

> create-pr

Alias for sentry-skills:pr-writer. Use when users explicitly ask for "create-pr" or reference the legacy skill name. Redirects to the canonical PR writing workflow.

> blog-writing-guide

Write, review, and improve blog posts for the Sentry engineering blog following Sentry's specific writing standards, voice, and quality bar. Use this skill whenever someone asks to write a blog post, draft a technical article, review blog content, improve a draft, write a product announcement, create an engineering deep-dive, or produce any written content destined for the Sentry blog or developer audience. Also trigger when the user mentions "blog post," "blog draft," "write-up," "announcement

> brand-guidelines

Write copy following Sentry brand guidelines. Use when writing UI text, error messages, empty states, onboarding flows, 404 pages, documentation, marketing copy, or any user-facing content. Covers both Plain Speech (default) and Sentry Voice tones.

> code-review

Perform code reviews following Sentry engineering practices. Use when reviewing pull requests, examining code changes, or providing feedback on code quality. Covers security, performance, testing, and design review.

> presentation-creator

Create data-driven presentation slides using React, Vite, and Recharts with Sentry branding. Use when asked to "create a presentation", "build slides", "make a deck", "create a data presentation", "build a Sentry presentation". Scaffolds a complete slide-based app with charts, animations, and single-file HTML output.

> skill-creator

Alias for sentry-skills:skill-writer. Use when users explicitly ask for "skill-creator" or reference the legacy skill name. Redirects to the canonical skill authoring workflow.

> 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

> 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

> 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

> 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.

> 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

> azure-mgmt-arizeaiobservabilityeval-dotnet

Azure Resource Manager SDK for Arize AI Observability and Evaluation (.NET). Use when managing Arize AI organizations on Azure via Azure Marketplace, creating/updating/deleting Arize resources, or integrating Arize ML observability into .NET applications. Triggers: "Arize AI", "ML observability", "ArizeAIObservabilityEval", "Arize organization".

> 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.