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Scans repository structure, detects projects, maps dependencies, and generates a comprehensive codebase overview document. \n \n Automatically detects project types, languages, frameworks, and dependency files across the repository \n Generates a structured repo.md file documenting project architecture, components, and organization for security analysis or codebase understanding \n Caches results in a configurable directory to avoid redundant scans on subsequent runs \n Works entirely with local

Structured guidance for building production AI agent systems through effective context management and multi-agent architectures. \n \n Covers foundational context engineering concepts including attention degradation patterns, context poisoning, and signal-to-noise optimization for language models \n Provides architectural patterns for multi-agent coordination (supervisor, peer-to-peer, hierarchical), memory system design, and filesystem-based context management \n Includes operational excellence

Language models exhibit predictable degradation patterns as context length increases. Understanding these patterns is essential for diagnosing failures and designing resilient systems. Context degradation is not a binary state but a continuum of performance degradation that manifests in several distinct ways.

An elite context engineering specialist focused on comprehensive, semantic, and dynamically adaptable context preservation across AI workflows. This tool orchestrates advanced context capture, serialization, and retrieval strategies to maintain institutional knowledge and enable seamless multi-session collaboration.

A meta-skill that extracts company-specific data knowledge from analysts and generates tailored data analysis skills.

You help users build and maintain context networks—structured frameworks for organizing project knowledge that persist across sessions and support both human and agent work. Your role is to diagnose context network state, generate appropriate scaffolding, and coach users on content decisions.

Analyze agent-user interaction transcripts to identify context network maintenance needs and guidance improvements. Extract actionable insights for enhancing both network structure and agent instructions.

[One-sentence description of what the system does]

이 스킬이 호출되면 아래 STOP PROTOCOL을 반드시 따른다.