sentry
Fetch and analyze Sentry issues, events, transactions, and logs. Helps agents debug errors, find root causes, and understand what happened at specific times.
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes. Implements scientific method for debugging with root cause analysis.
debugging-memory
This skill should be used when the user asks to "debug this", "fix this bug", "why is this failing", "investigate error", "getting an error", "exception thrown", "crash", "not working", "what's causing this", "root cause", "diagnose this issue", or describes any software bug or error. Also activates when spawning subagents for debugging tasks, using Task tool for bug investigation, or coordinating multiple agents on a debugging problem. Provides memory-first debugging workflow that checks past incidents before investigating.
debug-lldb
Capture and analyze thread backtraces with LLDB/GDB to debug hangs, deadlocks, UI freezes, IPC stalls, or high-CPU loops across any language or project. Use when an app becomes unresponsive, switching contexts stalls, or you need thread stacks to locate lock inversion or blocking calls.
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior (including race conditions, deadlocks, concurrency issues) - four-phase framework (root cause investigation, pattern analysis, hypothesis testing, implementation) with specialized techniques for deep call stack tracing and concurrency debugging
instruction-improver
Search memex for user feedback patterns (frustration, corrections, praise, successful outcomes) to identify recurring mistakes and wins, then generate CLAUDE.md or AGENTS.md improvements.
thinking-framework
Use this when complex problem-solving, root cause analysis, strategic decision-making, or systematic thinking is needed. Applies 15 thinking methods with multi-agent orchestration and Clear-Thought MCP integration for enhanced analysis quality.
incident-triage
Faster on-call handoffs and better postmortems with triage SOPs
run-tests
Comprehensive pytest testing and debugging framework. Use when running tests, debugging failures, fixing broken tests, or investigating test errors. Includes systematic investigation workflow with external AI tool consultation and verification strategies.
claude-code-debug
Troubleshoot Claude Code extensions and behavior. Triggers on: debug, troubleshoot, not working, skill not loading, hook not running, agent not found.
bug-fix
Systematically diagnose and fix bugs by reproducing issues, identifying root causes, implementing fixes, and preventing regressions. Use when debugging errors, fixing issues, or troubleshooting problems.
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes - four-phase framework (root cause investigation, pattern analysis, hypothesis testing, implementation) that ensures understanding before attempting solutions
Root Cause Analysis Methodology
This skill should be used when the user asks to "perform root cause analysis", "investigate production issue", "analyze incident", "find root cause", "debug production error", "trace the cause", or mentions investigating production problems, alerts, or outages. Provides systematic RCA methodology and investigation workflows.
Prometheus Analysis
This skill should be used when the user asks to "query Prometheus", "analyze Prometheus metrics", "check Prometheus alerts", "write PromQL", "interpret Prometheus data", "fetch metrics", or mentions Prometheus querying, alerting, or metrics analysis. Provides guidance for querying and interpreting Prometheus metrics for root cause analysis.
root-cause-tracing
Use when errors occur deep in execution and you need to trace back to find the original trigger - systematically traces bugs backward through call stack, adding instrumentation when needed, to identify source of invalid data or incorrect behavior
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes - four-phase framework (root cause investigation, pattern analysis, hypothesis testing, implementation) that ensures understanding before attempting solutions
debug-like-expert
Deep analysis debugging mode for complex issues. Activates methodical investigation protocol with evidence gathering, hypothesis testing, and rigorous verification. Use when standard troubleshooting fails or when issues require systematic root cause analysis.
sequential-thinking
Structured problem-solving through iterative reasoning with revision and branching capabilities for complex problems. Use when tackling multi-step problems with uncertain scope, design planning, architecture decisions, or systematic decomposition. Auto-activates when user asks about breaking down epics, designing systems, assessing complexity, or performing root-cause analysis. Uses 6-step process: Initial assessment (rough estimate) → Iterative reasoning (learn progressively) → Dynamic scope adjustment (refine as understanding deepens) → Revision mechanism (update when assumptions change) → Branching for alternatives (explore multiple approaches) → Conclusion (synthesize findings). Supports explicit uncertainty acknowledgment within thoughts. Adjusts total thought count dynamically (e.g., "Thought 3/8" when initially estimated 5). Recommends binary search for intermittent issues and five-whys technique for root causes.
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