Sentry plugins

Dynamically analyze and fix errors from stack traces, logs, and distributed tracing using specialized agents that perform root cause analysis, multi-agent code review, and monitoring setup, then implement fixes and configure error tracking and alerts.

Debug production errors by correlating stack traces, logs, and distributed tracing data across systems, performing root cause analysis, and implementing fixes with automated observability steps. Also sets up structured logging, alerts, and error tracking integrations for real-time monitoring. Includes agents that isolate test failures and search logs for anomalies.

Guides AI-assisted debugging from error triage through root cause analysis, collecting observability data and generating ranked hypotheses. Automates environment setup, optimizes workflows, and improves tooling and documentation for faster development.

Orchestrate production incident response with structured runbooks, multi-agent triage and debugging, blameless postmortems, and on-call shift handoffs. Automate detection, investigation, mitigation, and learning from incidents using SRE practices and observability tools.

Automate OSS maintenance workflows including changelog generation, conventional commits, branch naming, PR creation, code review, and documentation templates following Sentry engineering practices.

Set up comprehensive error rate monitoring with threshold-based alerting, error budget tracking, automated dashboards, and incident response guidelines across HTTP, database, external API, background jobs, and client-side errors.

Manage full Sentry lifecycle: configure SDKs, optimize costs, enforce security compliance, diagnose silent failures, set up CI/CD release tracking, and tune performance monitoring across Node.js, Python, and browser environments.

Guides building Node.js/Express/TypeScript microservices with layered architecture (routes→controllers→services→repositories), Prisma ORM, Sentry error tracking, Zod validation, and testing strategies.

Add Sentry v8 error tracking and performance monitoring to project services, enforcing that all errors are captured and instrumenting new controllers, cron jobs, and database performance monitoring

Build, debug, and audit Apple platform apps (iOS, macOS, watchOS, tvOS) with specialized skills for SwiftUI, Xcode, performance profiling, crash analysis, accessibility, App Store submission, and code quality — all from within Claude Code.

Access Sentry error tracking, performance monitoring, and issue management data to debug and monitor application health from within AI workflows.

Search, update, and triage Sentry exceptions and performance traces from Claude — investigate stack traces, analyze root causes with Seer AI, and manage issues, projects, and teams without switching context.

Investigate and manage Sentry errors, performance traces, and issues directly from Claude Code. Analyze stack traces, root causes with Seer AI, and manage projects/teams.

Access Sentry error reports, stack traces, and performance data directly from your development environment to debug production errors without switching contexts.

Use the Sentry CLI from Claude Code to authenticate, view organizations, projects, and issues, and make API calls to Sentry for error monitoring.

Audit, plan, and instrument mobile app observability across iOS, Android, React Native, and Flutter — covering crash reporting, performance monitoring, session replay, and distributed tracing with actionable gap analysis and vendor-agnostic rollout strategies.

Audit observability posture across your services: scan for RED metrics, SLOs, alerts, runbooks, tracing, and structured logging. Get a coverage matrix and identify critical gaps to ensure monitoring is sufficient before launch.

Treat vigil as a dedicated SRE engineer that instruments services with OpenTelemetry, configures SLO-based alerting and runbooks for Prometheus, Grafana, and Datadog, audits observability posture across your stack, and diagnoses production incidents by combining logs, metrics, and traces.

Inventory observability tools across services, map metrics, tracing, logging, and alerting coverage, and highlight monitoring blind spots

Monitor errors, performance, releases, and incidents in Sentry projects — identify slow transactions, investigate stack traces, triage alerts with root-cause analysis, and detect deployment regressions.

Accelerate TypeScript/JavaScript development with Bun runtime: debug with inspector and memory profiling, run tests, manage dependencies, publish npm packages, enforce code quality with Biome and Knip, and monitor production errors with Sentry.

Scan codebase to inventory existing analytics instrumentation, design a structured tracking plan, generate SDK-specific instrumentation code for 24 analytics tools, and monitor coverage as features change to keep product telemetry data-ready.

Enforce a structured AI-assisted development workflow from ticket creation through post-mortem, with quality gates at every stage: PRDs, TDD, parallel review swarms, verified completions, and retrospective analysis.

Orchestrate a full product lifecycle from research through release readiness with human-in-the-loop gates, artifact traceability, and automated spec-to-code verification across express, lite, standard, and V-model modes.

Deploy specialized AI agents for system architecture, database schema design, performance engineering, OpenTelemetry-based monitoring, and systematic web research within your SDLC workflow.

Accelerate Rails development with TDD workflow, automated security and Rails best-practice code reviews, and Linear issue integration. Includes parallel review agents, worktree management, and PR creation.

Build scalable full-stack applications using Next.js, Postgres, and Drizzle with recommended patterns for authentication, database queries, logging, analytics, error tracking, social preview images, syntax highlighting, URL state management, testing, and autonomous workflows.

Sends desktop and phone push notifications when AI coding agents (Claude Code, Codex, Gemini CLI, Cursor) complete tasks or require user input, with setup wizard, status checks, and configurable notification channels (toast, ntfy, webhook).

Cross-vendor reliability operations — compute error-budget burn rates, generate blameless postmortems from incident and observability data, and produce structured on-call handoff briefs across connected incident-management and monitoring tools.

Run static and semantic bug analysis on the current branch, synthesizing results into an actionable report with incremental analysis support.

Automate the full DevOps lifecycle: CI/CD pipelines, containerized deployments, Kubernetes orchestration, cloud infrastructure as code, and production monitoring. Includes specialized agents for AWS architecture, cost optimization, data engineering, and observability.

Monitor and analyze application error rates across HTTP, application, database, external API, background jobs, and client-side errors, with configurable alerting thresholds and integration with tools like Sentry and CloudWatch.

Orchestrates 10 agents to produce production-grade API integrations from OpenAPI/GraphQL specs: typed clients, auth flows, error handling with retries/circuit breakers, rate limiting, mock servers, and generated test suites.

Manage the full SDLC for Go API services: scaffold projects, generate code from PostgreSQL schemas, run Playwright browser tests, review GitLab MRs with multi-persona analysis, monitor production via Sentry/Prometheus/Grafana/Loki/Kibana, investigate incidents, and resolve YouTrack tasks with automated commits.

Analyze production errors from stack traces, logs, and distributed traces to perform root cause analysis, generate ranked hypotheses, and suggest fixes with observability tooling

Guide AI-assisted debugging from error triage through root cause analysis, leveraging observability data to generate ranked hypotheses. Automate environment setup and optimize workflows for faster, more enjoyable development.

Analyze errors from stack traces, logs, and distributed tracing data, perform root cause analysis, suggest fixes, and set up error tracking. Orchestrate multi-agent code reviews for code quality, security, architecture, and performance.

Respond to production incidents with structured runbooks, automated triage, and multi-agent debugging. Orchestrate incident response playbooks, perform deep root cause analysis via code tracing and git bisect, write blameless postmortems, and generate test suites for verified fixes.

Manage MCP server configurations in Claude Code: list, add, enable, and disable HTTP/stdio servers across local, project, and user scopes, with built-in setup examples for GitHub, Sentry, and PostgreSQL.

Manage Sentry error monitoring, performance tracing, release management, and alert configuration across JavaScript, Python, and Go stacks

Integrates Sentry error tracking, performance monitoring, and incident response into Claude Code, enabling investigation of errors and exceptions, analysis of performance metrics and release health, and management of alert-driven incident workflows.