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Debug AOTInductor (AOTI) errors and crashes. Use when encountering AOTI segfaults, device mismatch errors, constant loading failures, or runtime errors from aot_compile, aot_load, aoti_compile_and_package, or aoti_load_package.

Create or modify API endpoints in IdeaForge backend. Triggers: new route, controller, service, repository, CRUD operation, Zod validation, API debugging. Pattern: Routes → Controller → Service → Repository.

Implement comprehensive API error handling with standardized error responses, logging, monitoring, and user-friendly messages. Use when building resilient APIs, debugging issues, or improving error reporting.

Instrument API requests with spans and distributed tracing. Use when tracking request latency or debugging API issues.

Expert lifecycle decisions for iOS/tvOS: when SwiftUI lifecycle vs SceneDelegate, background task strategies, state restoration trade-offs, and launch optimization. Use when managing app state transitions, handling background work, or debugging lifecycle issues. Trigger keywords: lifecycle, scenePhase, SceneDelegate, AppDelegate, background task, state restoration, launch time, didFinishLaunching, applicationWillTerminate, sceneDidBecomeActive

Implement structured logging across applications with log aggregation and centralized analysis. Use when setting up application logging, implementing ELK stack, or analyzing application behavior.

Comprehensive assistance with ar-io-build

Expert guidance for GabeDA v2.1 architecture (34 modules) - implementing models, features, debugging 4-case logic, and maintaining the /src codebase.

Build and debug ARKit features for visionOS, including ARKitSession setup, authorization, data providers (world tracking, plane detection, scene reconstruction, hand tracking), anchor processing, and RealityKit integration. Use when implementing ARKit workflows in immersive spaces or troubleshooting ARKit data access and provider behavior on visionOS.

Asks Claude CLI for coding assistance. Use for getting a second opinion, code generation, debugging, or delegating coding tasks.

Asks Codex CLI for coding assistance. Use for getting a second opinion, code generation, debugging, or delegating coding tasks.

This skill should be used when solving hard questions, complex architectural problems, or debugging issues that benefit from GPT-5 Pro or GPT-5.1 thinking models with large file context. Use when standard Claude analysis needs deeper reasoning or extended context windows.

Creates assessments with varied question types (MCQ, code-completion, debugging, projects) aligned to learning objectives. Use when educators design quizzes/exams, need questions at appropriate Bloom's cognitive levels, want balanced cognitive distribution (60%+ non-recall), or require rubrics for open-ended questions.

Use `astro:assets` for all images. This enables automatic optimization (resizing, WebP/AVIF conversion, lazy loading).

Set up observers for debugging and monitoring. Covers implementing actionObservers for dispatch logging, stateObserver for state change tracking, combining observers with globalWrapError, and using observers for analytics.

Establish cause-effect relationships between events or states. Use when analyzing root causes, mapping dependencies, tracing effects, or building causal models.

Automatically helps debug Web Audio API issues, audio playback problems, pitch preservation, and caching issues in the VSSK-shadecn music practice app

Analyze the WaveCap-SDR audio stream to assess tuning quality, detect silence, noise, proper audio, or distortion. Use when checking if SDR channels are properly configured or debugging audio issues.

Run a single-session engineering productivity audit on the codebase

Comprehensive audit logging for compliance and security. Track user actions, data changes, and system events with tamper-proof storage.

Comprehensive guide to implementing audit trails and logging for AI agents including tracing, observability, compliance, and debugging

Implementing comprehensive logging, tracking, and audit trails for AI systems to ensure compliance and enable debugging.

name: auto-debug

How the devbox automatically updates llm-agents (claude-code) via GitHub Actions and systemd timers. Use when debugging update failures or understanding the update flow.

- Standalone for Reminders; reuse `automating-mac-apps` for permissions, shell helpers, and ObjC debugging patterns.

Automates terminal sessions in tmux windows using MCP tools. Use when launching background processes, monitoring builds/servers, sending commands to debuggers (pdb/gdb), interacting with CLI prompts, using interactive commands or commands that require sudo, or orchestrating parallel tasks across multiple terminal sessions.

Expert automation platform error debugger for Power Automate, n8n, Make, Zapier and other workflow platforms. Analyzes JSON flow definitions with error messages, researches official documentation, and generates complete fixed JSON ready for copy-paste. Triggers when user provides error JSON files, workflow JSON with errors, error messages, debug requests, or failing automation content. Returns structured debug report with root cause analysis and working fixed JSON.

Fast automation platform error resolver for Power Automate, n8n, Make, Zapier and other platforms. Handles common patterns like 401/403 auth errors, 429 throttling, and data format issues. Provides immediate fixes without deep research for well-known error patterns. Use when error matches common scenarios (status codes 401, 403, 404, 429, timeout, parse JSON failures). For complex or unknown errors, defer to automation-debugger skill. When the user outputs some code/json snippets and ask for a quick fix, this skill will provide immediate solutions.

Search, filter, and retrieve Claude/Codex history indexed by the automem CLI. Use when the user wants to index history, run lexical/semantic/hybrid search, fetch full transcripts, or produce LLM-friendly JSON output for RAG.

Comprehensive autonomous development strategies including milestone planning, incremental implementation, auto-debugging, and continuous quality assurance for full development lifecycle management

A structured framework for dynamic and reflective problem-solving through sequential thoughts. Use when tackling complex, multi-step problems that require careful analysis, revision of assumptions, or exploration of alternative approaches. Ideal for algorithm optimization, architectural decisions, debugging complex issues, or any task where initial understanding may need to evolve.

Debug AWS resource issues, check Lambda logs, and monitor deployed services. Use when investigating production issues, checking CloudWatch logs, or debugging deployment failures.

Use when integrating App Intents for Siri, Apple Intelligence, Shortcuts, Spotlight, or system experiences - covers AppIntent, AppEntity, parameter handling, entity queries, background execution, authentication, and debugging common integration issues for iOS 16+

Use when implementing App Shortcuts for instant Siri/Spotlight availability, configuring AppShortcutsProvider, adding suggested phrases, or debugging shortcuts not appearing - covers complete App Shortcuts API for iOS 16+

Use when:

Check dependencies BEFORE blaming code. **Core principle** 80% of persistent build failures are dependency resolution issues (CocoaPods, SPM, framework conflicts), not code bugs.

Use when debugging 'file not syncing', 'CloudKit error', 'sync conflict', 'iCloud upload failed', 'ubiquitous item error', 'data not appearing on other devices', 'CKError', 'quota exceeded' - systematic iCloud sync diagnostics for both CloudKit and iCloud Drive

Use when debugging Foundation Models issues — context exceeded, guardrail violations, slow generation, availability problems, unsupported language, or unexpected output. Systematic diagnostics with production crisis defense.

Use when implementing haptic feedback, Core Haptics patterns, audio-haptic synchronization, or debugging haptic issues - covers UIFeedbackGenerator, CHHapticEngine, AHAP patterns, and Apple's Causality-Harmony-Utility design principles from WWDC 2021

Use when implementing or debugging ANY network connection, API call, or socket. Covers URLSession, Network.framework, NetworkConnection, deprecated APIs, connection diagnostics, structured concurrency networking.

Use when you see memory warnings, 'retain cycle', app crashes from memory pressure, or when asking 'why is my app using so much memory', 'how do I find memory leaks', 'my deinit is never called', 'Instruments shows memory growth', 'app crashes after 10 minutes' - systematic memory leak detection and fixes for iOS/macOS

Use when debugging memory leaks from blocks, blocks assigned to self or properties, network callbacks, or crashes from deallocated objects - systematic weak-strong pattern diagnosis with mandatory diagnostic rules

Use when implementing SwiftUI animations, understanding VectorArithmetic, using @Animatable macro, zoom transitions, UIKit/AppKit animation bridging, choosing between spring and timing curve animations, or debugging animation behavior - comprehensive animation reference from iOS 13 through iOS 26

Use when SwiftUI view debugging requires systematic investigation - view updates not working after basic troubleshooting, intermittent UI issues, complex state dependencies, or when Self._printChanges() shows unexpected update patterns - systematic diagnostic workflows with Instruments integration

Use when implementing SwiftUI gestures (tap, drag, long press, magnification, rotation), composing gestures, managing gesture state, or debugging gesture conflicts - comprehensive patterns for gesture recognition, composition, accessibility, and cross-platform support

Use when debugging navigation not responding, unexpected pops, deep links showing wrong screen, state lost on tab switch or background, crashes in navigationDestination, or any SwiftUI navigation failure - systematic diagnostics with production crisis defense

Check build environment BEFORE debugging code. **Core principle** 80% of "mysterious" Xcode issues are environment problems (stale Derived Data, stuck simulators, zombie processes), not code bugs.

Expert guidance for fine-tuning LLMs with Axolotl - YAML configs, 100+ models, LoRA/QLoRA, DPO/KTO/ORPO/GRPO, multimodal support

View and debug B2C CLI configuration and understand where credentials come from. Use when authentication fails, connection errors occur, wrong instance is used, or you need to verify dw.json settings, environment variables (SFCC_*), or OAuth credentials are loaded correctly.