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Found 10 Skills
Use when auditing, trimming, or restructuring AI skill files to reduce context-window consumption. Trigger whenever a SKILL.md exceeds 120 lines, skills share duplicated content, AGENTS.md has large inline blocks, or the user asks to optimize, slim down, or reduce token usage of their skills.
Strategies for managing LLM context windows including summarization, trimming, routing, and avoiding context rot Use when: context window, token limit, context management, context engineering, long context.
Expert in managing the "Memory" of AI systems. Specializes in Vector Databases (RAG), Short/Long-term memory architectures, and Context Window optimization. Use when designing AI memory systems, optimizing context usage, or implementing conversation history management.
This skill should be used when the user asks to "offload context to files", "implement dynamic context discovery", "use filesystem for agent memory", "reduce context window bloat", or mentions file-based context management, tool output persistence, agent scratch pads, or just-in-time context loading.
tokenization과 context window를 중심으로 긴 입력 처리 한계와 실무 대응 방법(분할, 요약, 우선순위화)을 학습시키는 모듈.
Analyzes Claude Code session transcripts (JSONL files) to reveal context window content, token usage patterns, and decision-making processes using view_session_context.py tool. Use when debugging Claude behavior, investigating token patterns, tracking agent delegation, or analyzing context exhaustion. Triggers on "why did Claude do X", "analyze session", "check session logs", "context window exhaustion", or "track agent delegation".
Manages context window optimization, session state persistence, and token budget allocation for multi-agent workflows. Use when dealing with token budget management, context window limits, session handoff, state persistence across agents, or /clear strategies. Do NOT use for agent orchestration patterns (use moai-foundation-core instead).
CRITICAL - Guide for using Claudish CLI ONLY through sub-agents to run Claude Code with any AI model (OpenRouter, Gemini, OpenAI, local models). NEVER run Claudish directly in main context unless user explicitly requests it. Use when user mentions external AI models, Claudish, OpenRouter, Gemini, OpenAI, Ollama, or alternative models. Includes mandatory sub-agent delegation patterns, agent selection guide, file-based instructions, and strict rules to prevent context window pollution.
Full-codebase audit using 1M context window. Security, architecture, and dependency analysis in a single pass. Use when you need whole-project analysis.
Compressed communication using symbols and abbreviations. Use when context is limited or brevity is needed.