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Found 904 Skills
Open-source AI observability platform for LLM tracing, evaluation, and monitoring. Use when debugging LLM applications with detailed traces, running evaluations on datasets, or monitoring production AI systems with real-time insights.
LLM observability platform for tracing, evaluation, and monitoring. Use when debugging LLM applications, evaluating model outputs against datasets, monitoring production systems, or building systematic testing pipelines for AI applications.
Turbopack expert guidance. Use when configuring the Next.js bundler, optimizing HMR, debugging build issues, or understanding the Turbopack vs Webpack differences.
This skill should be used for browser automation tasks using Chrome DevTools Protocol (CDP). Triggers when users need to launch Chrome with remote debugging, navigate pages, execute JavaScript in browser context, capture screenshots, or interactively select DOM elements. No MCP server required.
Schedule and execute background work on iOS using BGTaskScheduler. Use when registering BGAppRefreshTask for short background fetches, BGProcessingTask for long-running maintenance, BGContinuedProcessingTask (iOS 26+) for foreground-started work that continues in background, background URLSession downloads, or background push notifications. Covers Info.plist configuration, expiration handling, task completion, and debugging with simulated launches.
MUST READ before setting up observability for ADK agents or when analyzing production traffic, debugging agent behavior, or improving agent performance. ADK observability guide — Cloud Trace, prompt-response logging, BigQuery Agent Analytics, third-party integrations, and troubleshooting. Use when configuring monitoring, tracing, or logging for agents, or when understanding how a deployed agent handles real traffic.
Debug applications using the dbg CLI debugger. Supports Node.js (V8/CDP), Bun (WebKit/JSC), and native code via LLDB (DAP). Use when: (1) investigating runtime bugs by stepping through code, (2) inspecting variable values at specific execution points, (3) setting breakpoints and conditional breakpoints, (4) evaluating expressions in a paused context, (5) hot-patching code without restarting (JS/TS), (6) debugging test failures by attaching to a running process, (7) debugging C/C++/Rust/Swift with LLDB, (8) any task where understanding runtime behavior requires a debugger. Triggers: "debug this", "set a breakpoint", "step through", "inspect variables", "why is this value wrong", "trace execution", "attach debugger", "runtime error", "segfault", "core dump".
Web automation, debugging, and E2E testing with Playwright. Handles interactive (login, forms, reproduce bugs) and passive modes (network/console capture). Triggers on "e2e test", "browser test", "playwright", "screenshot", "debug UI", "debug frontend", "reproduce bug", "network trace", "console output", "verify fix", "test that", "verify change", "test the flow", "http://localhost", "open browser", "click button", "fill form", "submit form", "check page", "web scraping", "automation script", "headless browser", "browser automation", "selenium alternative", "puppeteer alternative", "page object", "web testing", "UI testing", "frontend testing", "visual regression", "capture network", "intercept requests", "mock API responses". PROACTIVE: Invoke for security verification, UI fix verification, testing forms/dropdowns, or multi-step UI flows. ON SESSION RESUME - check for pending UI verifications.
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.
Structured debugging session — reproduce, isolate, diagnose, and fix. Trigger with an error message or stack trace, "this works in staging but not prod", "something broke after the deploy", or when behavior diverges from expected and the cause isn't obvious.
Claudeception is a continuous learning system that extracts reusable knowledge from work sessions. Triggers: (1) /claudeception command to review session learnings, (2) "save this as a skill" or "extract a skill from this", (3) "what did we learn?", (4) After any task involving non-obvious debugging, workarounds, or trial-and-error discovery. Creates new Claude Code skills when valuable, reusable knowledge is identified.
Agent Skill for Swift architecture design and implementation patterns, with architecture-specific playbooks and review checklists. Use when designing new features, refactoring existing modules, reviewing pull requests, or debugging maintainability issues in SwiftUI/UIKit projects and you need concrete guidance for MVVM, MVI, TCA, Clean Architecture, VIPER, or Reactive patterns.