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Found 221 Skills
Full Sentry SDK setup for browser JavaScript. Use when asked to "add Sentry to a website", "install @sentry/browser", or configure error monitoring, tracing, session replay, or logging for vanilla JavaScript, jQuery, static sites, or WordPress.
Full Sentry SDK setup for PHP. Use when asked to "add Sentry to PHP", "install sentry/sentry", "setup Sentry in PHP", or configure error monitoring, tracing, profiling, logging, metrics, or crons for PHP applications. Supports plain PHP, Laravel, and Symfony.
Full Sentry SDK setup for Go. Use when asked to "add Sentry to Go", "install sentry-go", "setup Sentry in Go", or configure error monitoring, tracing, logging, metrics, or crons for Go applications. Supports net/http, Gin, Echo, Fiber, FastHTTP, Iris, and Negroni.
Expert guidance for Django REST Framework class-based views using Classy DRF (https://www.cdrf.co). Use when selecting or debugging APIView, GenericAPIView, concrete generic views, mixin combinations, or ViewSet/GenericViewSet/ModelViewSet behavior; tracing method resolution order (MRO); understanding which method to override (`create` vs `perform_create`, `update` vs `perform_update`, `destroy` vs `perform_destroy`, `get_queryset`, `get_serializer_class`); and comparing behavior across DRF versions. Do not use for function-based views, GraphQL, FastAPI/Flask, frontend work, or non-DRF backend frameworks.
Troubleshoot Golang programs systematically - find and fix the root cause. Use when encountering bugs, crashes, deadlocks, or unexpected behavior in Go code. Covers debugging methodology, common Go pitfalls, test-driven debugging, pprof setup and capture, Delve debugger, race detection, GODEBUG tracing, and production debugging. Start here for any 'something is wrong' situation. Not for interpreting profiles or benchmarking (see golang-benchmark skill) or applying optimization patterns (see golang-performance skill).
Analyze MSBuild binary logs to diagnose build failures by replaying binlogs to searchable text logs. Only activate in MSBuild/.NET build context. USE FOR: build errors that are unclear from console output, diagnosing cascading failures across multi-project builds, tracing MSBuild target execution order, investigating common errors like CS0246 (type not found), MSB4019 (imported project not found), NU1605 (package downgrade), MSB3277 (version conflicts), and ResolveProjectReferences failures. Requires an existing .binlog file. DO NOT USE FOR: generating binlogs (use binlog-generation), build performance analysis (use build-perf-diagnostics), non-MSBuild build systems. INVOKES: dotnet msbuild binlog replay, grep, cat, head, tail for log analysis.
Investigate stuck runs and execution failures by tracing Symphony and Codex logs with issue/session identifiers; use when runs stall, retry repeatedly, or fail unexpectedly.
Java logging best practices with SLF4J, structured logging (JSON), and MDC for request tracing. Includes AI-friendly log formats for Claude Code debugging. Use when user asks about logging, debugging application flow, or analyzing logs.
Add LangWatch tracing and observability to your code. Use for both onboarding (instrument an entire codebase) and targeted operations (add tracing to a specific function or module). Supports Python and TypeScript with all major frameworks.
Instrument, trace, evaluate, and monitor LLM applications and AI agents with LangSmith. Use when setting up observability for LLM pipelines, running offline or online evaluations, managing prompts in the Prompt Hub, creating datasets for regression testing, or deploying agent servers. Triggers on: langsmith, langchain tracing, llm tracing, llm observability, llm evaluation, trace llm calls, @traceable, wrap_openai, langsmith evaluate, langsmith dataset, langsmith feedback, langsmith prompt hub, langsmith project, llm monitoring, llm debugging, llm quality, openevals, langsmith cli, langsmith experiment, annotate llm, llm judge.
Comprehensive Pal MCP toolkit for code analysis, debugging, planning, refactoring, code review, and execution tracing. Provides systematic workflows with expert validation for complex development tasks.
Operates as an on-chain forensics investigator using only public chain data and OSINT—tracing flows across chains, clustering addresses, reviewing contracts for risk patterns, detecting scam vectors, and producing evidence-backed reports. Use when the user asks for blockchain investigation, forensic tracing, scam or rug analysis from public data, transaction trail documentation, or structured intelligence reports without private keys or insider access.