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Found 67 Skills
Ultra-compressed communication mode. Cuts token usage ~75% by dropping filler, articles, and pleasantries while keeping full technical accuracy. Use when user says "caveman mode", "talk like caveman", "use caveman", "less tokens", "be brief", or invokes /caveman.
Modo cavernícola en español. Corta ~75% de tokens hablando como cavernícola técnico. Misma precisión técnica, menos palabrería. Niveles: lite, full (default), ultra. Usar cuando el usuario diga "modo cavernícola", "habla como cavernícola", "menos tokens", "sé breve", o invoque /caveman-es.
Triage and categorize GitHub issues with priority labels. Use when user says "triage issues", "check issues", "review open issues", or during regular maintenance of GitHub issue backlog.
Provides MoAI-ADK foundational principles including TRUST 5 quality framework, SPEC-First DDD methodology, delegation patterns, progressive disclosure, and agent catalog reference. Use when referencing TRUST 5 gates, SPEC workflow, EARS format, DDD methodology, agent delegation patterns, or MoAI orchestration rules. Do NOT use for context and token management (use moai-foundation-context instead) or strategic analysis (use moai-foundation-philosopher instead).
Review only changes since last commit using impact analysis. Token-efficient delta review with automatic blast-radius detection.
Use when compressing agent context, implementing conversation summarization, reducing token usage in long sessions, or asking about "context compression", "conversation history", "token optimization", "context limits", "summarization strategies"
Clear conversation context while preserving knowledge via context marker. Use when user says "clear context", "start fresh", "done with this task", or when approaching token limits.
Ultra-compressed communication mode (lite / full / ultra) that cuts token usage ~75% by speaking like caveman while keeping full technical accuracy. Use when the user requests "caveman mode", "less tokens", "be brief", or when output budget is tight.
Suggests manual context compaction at logical intervals to preserve context through task phases rather than arbitrary auto-compaction.
Compact, compress, or minify markdown files to use fewer tokens while preserving all information and meaning. Use this skill whenever the user wants to reduce the size of a markdown file, shrink a README, compress a SKILL.md or CLAUDE.md, minify documentation, or make any markdown more token-efficient. Trigger even if they just say "make this shorter" or "compress this" on a markdown file.
Use when working with *.excalidraw or *.excalidraw.json files, user mentions diagrams/flowcharts, or requests architecture visualization - delegates all Excalidraw operations to subagents to prevent context exhaustion from verbose JSON (single files: 4k-22k tokens, can exceed read limits)
Master context engineering for AI agent systems. Use when designing agent architectures, debugging context failures, optimizing token usage, implementing memory systems, building multi-agent coordination, evaluating agent performance, or developing LLM-powered pipelines. Covers context fundamentals, degradation patterns, optimization techniques (compaction, masking, caching), compression strategies, memory architectures, multi-agent patterns, LLM-as-Judge evaluation, tool design, and project development.