Loading...
Loading...
Found 127 Skills
Persistent research knowledge base that accumulates papers, ideas, experiments, claims, and their relationships across the entire research lifecycle. Inspired by Karpathy's LLM Wiki pattern. Use when user says "知识库", "research wiki", "add paper", "wiki query", "查知识库", or wants to build/query a persistent field map.
Conduct a targeted code exploration of the repository, and document the process of "Ask Questions → Read Code → Draw Conclusions" as searchable evidence for direct reuse when similar questions arise next time. There are three types: question (investigate code around a specific question and provide conclusions), module-overview (sort out the structure, boundaries, entry points, and dependencies of a module), and spike (conduct lightweight technical exploration of multiple possible directions without making final decisions). Trigger scenarios: Users say "Let's explore first", "How is X implemented in this repository", "Quickly get familiar with this module", "Archive the exploration results". Refer to `codestable/reference/system-overview.md` for how to distinguish it from learning / tricks / decisions.
Documents the results of a completed experiment or A/B test with statistical analysis, learnings, and recommendations. Use after experiments conclude to communicate findings, inform decisions, and build organizational knowledge.
Cross-session learning system that extracts insights from session transcripts and injects relevant past learnings at session start. Uses simple keyword matching for relevance. Complements DISCOVERIES.md/PATTERNS.md with structured YAML storage.
Inject relevant knowledge into session context from .agents/ artifacts. Triggers: "inject knowledge", "recall context", SessionStart hook.
Extracts valuable learnings, patterns, and workflows from conversations and persists them as reusable skill files. This skill should be used when a complex problem was solved, a valuable workflow was discovered, or the user explicitly requests to capture knowledge as a skill.
Store user preferences, learnings from tasks, and procedure outcomes. Use to remember what works and recall context before new tasks. (user)
An agent that helps relationship managers prepare for upcoming client meetings by synthesizing a tailored Point of View and detailed Speaker Notes from multiple information sources.
Generate comprehensive monthly knowledge management reports by analyzing team Yuque activity data including group stats, member contributions, knowledge base health, and document trends. For team use — requires team Token with statistic:read permission.
Set up and maintain a persistent, LLM-managed knowledge base for a digital health project — turning clinical observations, papers, interviews, and planning docs into a compounding, interlinked wiki.
Progressive Domain Crystallization (PDC) — a skill for building and maintaining a living domain knowledge base for any custom business application. Use this skill whenever the user is developing a business application and wants the AI to accumulate understanding of internal terminology, entities, relationships, and business rules over time — especially when that knowledge is not fully defined upfront and grows across sessions. Trigger on any of: "remember how our system works", "learn our domain", "track business entities", "build domain knowledge", "understand our terminology", "grow AI context over time", "domain model", "business rules documentation", or whenever a user says the AI doesn't understand their business-specific language or data model. Also use at the start of any session where a DOMAIN.md file exists in the project — always read it before doing any work.
MindOS is the user's local knowledge assistant and shared knowledge base. It keeps decisions, meeting notes, SOPs, debugging lessons, architecture choices, research findings, and preferences available across sessions and agents. 更新笔记, 搜索知识库, 整理文件, 执行SOP/工作流, 复盘, 追加CSV, 跨Agent交接, 路由非结构化输入到对应文件, 提炼经验, 同步关联文档. NOT for editing app source, project docs, or paths outside the KB. Core concepts: Space, Instruction (INSTRUCTION.md), Skill (SKILL.md); notes can embody both. Trigger on: save or record anything, search for prior notes or context, update or edit a file, organize notes, run a workflow or SOP, capture decisions, append rows to a table or CSV, hand off context to another agent, check if something was discussed before, look up a past decision, distill lessons learned, prepare context for a meeting, quick-capture to staging area, organize inbox, check knowledge health, detect conflicts or contradictions, find stale content. Chinese triggers: 帮我记下来, 搜一下笔记, 更新知识库, 整理文件, 复盘, 提炼经验, 保存, 记录, 交接, 查一下之前的, 有没有相关笔记, 把这个存起来, 放到暂存台, 整理暂存台, 知识健康检查, 检测知识冲突. Proactive behavior — do not wait for the user to mention MindOS: (1) When user's question implies stored context may exist (past decisions, previous discussions, meeting records) → search MindOS first, even if they don't explicitly mention it. (2) After completing valuable work (bug fixed, decision made, lesson learned, architecture chosen, meeting summarized) → offer to save it to MindOS for future reference. (3) After a long or multi-topic conversation → suggest persisting key decisions and context.