Loading...
Loading...
Found 168 Skills
This skill should be used when the user asks to "design multi-agent system", "implement supervisor pattern", "create swarm architecture", "coordinate multiple agents", or mentions multi-agent patterns, context isolation, agent handoffs, sub-agents, or parallel agent execution. Part of the context engineering skill suite — also activates when the user mentions "context engineering" or "context-engineering" in the context of orchestrating context across multiple agents.
Guides implementation of agent memory systems, compares production frameworks (Mem0, Zep/Graphiti, Letta, LangMem, Cognee), and designs persistence architectures for cross-session knowledge retention. Use when the user asks to "implement agent memory", "persist state across sessions", "build knowledge graph for agents", "track entities over time", "add long-term memory", "choose a memory framework", or mentions temporal knowledge graphs, vector stores, entity memory, adaptive memory, dynamic memory, or memory benchmarks (LoCoMo, LongMemEval). A core context engineering skill — also activates when the user mentions "context engineering" or "context-engineering" in the context of durable agent knowledge and cross-session persistence.
Understand the components, mechanics, and constraints of context in agent systems. Use when designing agent architectures, debugging context-related failures, or optimizing context usage.
Creates educational Teams channel posts for internal knowledge sharing about Claude Code features, tools, and best practices. Applies when writing posts, announcements, or documentation to teach colleagues effective Claude Code usage, announce new features, share productivity tips, or document lessons learned. Provides templates, writing guidelines, and structured approaches emphasizing concrete examples, underlying principles, and connections to best practices like context engineering. Activates for content involving Teams posts, channel announcements, feature documentation, or tip sharing.
This skill should be used when the user asks to "diagnose context problems", "fix lost-in-middle issues", "debug agent failures", "understand context poisoning", or mentions context degradation, attention patterns, context clash, context confusion, or agent performance degradation. Provides patterns for recognizing and mitigating context failures.
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.
Build evaluation frameworks for agent systems. Use when testing agent performance, validating context engineering choices, or measuring improvements over time.
프롬프트를 실증 기반 기법으로 분석하고 개선합니다. Few-shot, CoT, XML 구조화, Context Engineering 등 검증된 기법을 적용하여 프롬프트 품질을 높입니다. 프롬프트 개선, prompt 리뷰, 프롬프트 최적화, 프롬프팅 개선 요청 시 사용.
This skill should be used when the user asks to "optimize CLAUDE.md", "create a new skill", "write a custom agent", "configure hooks", "manage context window", "set up MCP servers", "scaffold a skill package", "analyze token budget", "create subagents", "configure permissions", "set up worktrees", or "integrate Claude Code with editors". Use for Claude Code CLI mastery, skill authoring, context engineering, hooks automation, subagent creation, and development workflow optimization.
Optimize and structure context for agents and LLMs by reducing noise, prioritizing relevance, organizing memory, defining constraints, and managing token budgets.
Create, review, and update Prompt and agents and workflows. Covers 5 workflow patterns, agent delegation, Handoffs, Context Engineering. Use for any .agent.md file work or multi-agent system design. Triggers on 'agent workflow', 'create agent', 'ワークフロー設計'.
Repository structure methodology for maximum AI agent effectiveness. Three pillars — context engineering (repo as knowledge product), architectural constraints (deterministic enforcement), garbage collection (active entropy fighting). Use when setting up repos for AI development, diagnosing repeated agent failures, writing AGENTS.md, or designing CI gates and structural tests.