Systematic decomposition of complex user requests into manageable, executable sub-tasks. Teaches how to break down multi-faceted requests, create execution plans, track progress, and handle dependencies between sub-tasks. Use when the user's request involves multiple steps, spans different domains, requires coordinating multiple tools, or when the scope is too large to complete in a single response.
Systematic quality verification checklist applied before delivering any output to the user. Ensures factual accuracy, completeness, format compliance, and absence of hallucinations. Use before completing any task that involves factual claims, generated code, document creation, data analysis, or multi-step research. Also use when the model is uncertain about output quality.
Docker container使用规范。当需要执行命令、操作文件、运行代码或进行任何可能受环境影响的任务时，必须使用container而非直接操作本地环境。明确沙盒隔离边界、与本地工具的交互规范、 文件路径约定以及多工具协作流程。执行命令、文件操作、代码执行时使用，或者任何应在隔离的 Docker container中运行的环境依赖任务. docker命令的工具以container为前缀，后续提及的工具名默认带上container前缀
当用户咨询夫妻/伴侣之间的矛盾、争吵、沟通问题、情感冲突、关系修复、婚姻危机或亲密关系改善时使用。涵盖沟通技巧、情绪管理、冲突调解、信任重建等场景。
Ultra-compressed communication mode. Cuts token usage ~75% by speaking like caveman while keeping full technical accuracy. Supports intensity levels: lite, full (default), ultra, wenyan-lite, wenyan-full, wenyan-ultra. Use when user says "caveman mode", "talk like caveman", "use caveman", "less tokens", "be brief", or invokes /caveman. Also auto-triggers when token efficiency is requested.
企业级时间感知搜索技能。当用户询问包含时间敏感性词汇的问题时（如"最近"、"近年来"、"最新"、"新闻"、"今年"、"上月"等）， 自动调用时间工具获取当前准确时间，校准认知后，再调用搜索工具核实信息，防止模型仅依赖训练数据的过时信息导致认知偏差和答非所问。 适用场景： - 用户询问时效性信息（新闻、政策、股价、天气等） - 用户问题包含相对时间词汇（最近、最新、当前、现在等） - 需要确保回答基于最新数据而非训练数据截止时间的场景 核心流程： 1. 检测时间敏感关键词 2. 获取当前准确时间（DateTimeTool）