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Error analysis, trace debugging, and multi-agent problem diagnosis
npx claudepluginhub ai-foundry-core/ril-agents --plugin error-debuggingYou are an expert error analysis specialist with deep expertise in debugging distributed systems, analyzing production incidents, and implementing comprehensive observability solutions.
You are an error tracking and observability expert specializing in implementing comprehensive error monitoring solutions. Set up error tracking systems, configure alerts, implement structured logging, and ensure teams can quickly identify and resolve production issues.
A sophisticated AI-powered code review system designed to provide comprehensive, multi-perspective analysis of software artifacts through intelligent agent coordination and specialized domain expertise.
Debugging specialist for errors, test failures, and unexpected behavior. Use proactively when encountering any issues.
Search logs and codebases for error patterns, stack traces, and anomalies. Correlates errors across systems and identifies root causes. Use PROACTIVELY when debugging issues, analyzing logs, or investigating production errors.
Uses power tools
Uses Bash, Write, or Edit tools
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Based on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
Systematic debugging, root cause analysis, log analysis, profiling, binary search debugging, and postmortem analysis.
Debug issues systematically with root cause analysis and execution tracing
Debugging specialist for errors, test failures, and unexpected behavior. Use proactively when encountering any issues.
Four-phase debugging framework that ensures root cause investigation before attempting fixes. Never jump to solutions. Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
Systematic debugging and root cause analysis framework - four-phase investigation process ensuring understanding before fixes
Universal expert problem-solving agent specializing in complex debugging, mysterious runtime behavior, integration issues, and multi-layered technical challenges across any technology stack or project type. Uses advanced research methodologies including GitHub issues mining, Perplexity deep research, community solutions validation, browser automation testing, and multi-source documentation analysis. Proactively use for intricate bugs, cryptic error messages, performance anomalies, framework integration problems, legacy system compatibility issues, and any technical challenges requiring deep investigation across multiple knowledge sources. Project-agnostic and universally applicable.
Test-driven development methodology with red-green-refactor cycles and code review
Code cleanup, refactoring automation, and technical debt management with context restoration
Multi-agent system optimization, agent improvement workflows, and context management
Pre-deployment checks, configuration validation, and deployment readiness assessment
Team workflows, issue management, standup automation, and developer experience optimization
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