Generate educational practice questions from lecture notes to test student understanding. Use when users request practice questions, exam preparation materials, study guides, or assessment items based on lecture content.

Analyze weekly marketing campaign performance data across channels. Use when analyzing multi-channel digital marketing data to calculate funnel metrics (CTR, CVR) and compare to benchmarks, compute cost and revenue efficiency metrics (ROAS, CPA, Net Profit), or get budget reallocation recommendations based on performance rules.

Multi-agent swarm coordination via the ClawTeam CLI. Use when the user wants to create agent teams, spawn multiple agents to work in parallel, coordinate tasks with dependencies, broadcast messages between agents, monitor progress via kanban board, or launch pre-built team templates (hedge-fund, code-review, research-paper). ClawTeam uses git worktree isolation + tmux + filesystem-based messaging. Trigger phrases: team, swarm, multi-agent, clawteam, spawn agents, parallel agents, agent team.

Multi-agent swarm orchestration. USE THIS (not delegate_task) when the user says team/swarm/multi-agent/clawteam/parallel-agents/agent-team, or asks for multi-perspective analysis (stocks, research, code review, strategy). Spawns N Hermes workers in tmux windows with git worktree isolation, file-based inboxes, and a kanban board. Four built-in templates: hedge-fund (7 analyst agents), research-paper, code-review, strategy-room.

Use this skill when working inside the ClawTeam repository itself: local development, debugging, reviewing, testing, validating multi-agent flows, or checking whether a code change actually works end-to-end. Use the repository bootstrap scripts to standardize the local `clawteam` command and to wire project-local `.agents` and `.claude` skills back to this repository. This skill is repository-development oriented, not a general end-user usage guide.

通用学习器 - 从任何领域的Prompt中自动提取可复用元素，持续学习和积累知识

提示词分析与洞察 - 查看Prompt详情、对比差异、推荐相似提示词、元素库统计

智能提示词生成器 v2.0 - 支持人像/跨domain/设计三种模式，语义理解、常识推理、一致性检查

Converts an arxiv paper into a minimal, citation-anchored Python implementation. Trigger when user runs /paper2code with an arxiv URL or paper ID, says "implement this paper", or pastes an arxiv link asking for implementation. Flags all ambiguities honestly. Never invents implementation details not stated in the paper.

Get a new developer up and running with the Chops codebase — prerequisites, build, architecture, and common tasks.

Determine the next version, update the marketing site, and run the full release pipeline.

Use when the user explicitly wants to create, edit, validate, sync, or troubleshoot n8n workflows, asks about n8n nodes or automation, or wants to use n8n-as-code in the current context root.

Use when the user explicitly wants to create, edit, validate, sync, or troubleshoot n8n workflows, asks about n8n nodes or automation, or wants to use n8n-as-code in the current context root.

Expert guidance on get_it service locator and dependency injection for Flutter/Dart. Covers registration (singleton, factory, lazy, async), scopes with shadowing, async initialization with init() pattern, retrieval, testing with scope-based mocking, and production patterns. Use when working with get_it, dependency injection, service registration, scopes, or async initialization.

Architecture guidance for Flutter apps using the flutter_it construction set (get_it, watch_it, command_it, listen_it). Covers Pragmatic Flutter Architecture (PFA) with Services/Managers/Views, feature-based project structure, manager pattern, proxy pattern with optimistic updates and override fields, DataRepository with reference counting, scoped services, widget granularity, testing, and best practices. Use when designing app architecture, structuring Flutter projects, implementing managers or proxies, or planning feature organization.

倪海厦（1954-2012）台湾中医师，经方派代表人物，汉唐中医创始人。 核心心智模型：六经辨证、阳气论、经典至上、经方为主。 决策启发式：先辨六经再选方、阳气不足先扶阳、经典原方最可靠。 触发词：「倪海厦」「海厦视角」「中医倪海厦」「经方思维」「倪海厦会怎么看」「倪师」。 知识库覆盖：伤寒论129条全+金匮23篇+黄帝内经18篇+针灸教程+神农本草经345种+天纪+849医案（按疾病分类6个模块）+梁冬对话+口述表达DNA+六经辨证诊断公式（8个公式+快速诊断流程图+脉舌速查+合病并病速查+真寒假热鉴别+七步走思维模式）。 基于一手素材：梁冬对话录音稿、人纪班闭门课记录、医案集、神农本草经视频讲义。版本：2026-05-23 StableV2026.5.23+Bencao。

Parameter-efficient fine-tuning for LLMs using LoRA, QLoRA, and 25+ methods. Use when fine-tuning large models (7B-70B) with limited GPU memory, when you need to train <1% of parameters with minimal accuracy loss, or for multi-adapter serving. HuggingFace's official library integrated with transformers ecosystem.

Battle-tested PyTorch training recipes for all domains — LLMs, vision, diffusion, medical imaging, protein/drug discovery, spatial omics, genomics. Covers training loops, optimizer selection (AdamW, Muon), LR scheduling, mixed precision, debugging, and systematic experimentation. Use when training or fine-tuning neural networks, debugging loss spikes or OOM, choosing architectures, or optimizing GPU throughput.

Write publication-ready ML/AI/Systems papers for NeurIPS, ICML, ICLR, ACL, AAAI, COLM, OSDI, NSDI, ASPLOS, SOSP. Use when drafting papers from research repos, structuring arguments, verifying citations, or preparing camera-ready submissions. Includes LaTeX templates, reviewer guidelines, and citation verification workflows.

Generates publication-quality figures for ML papers from research context. Given a paper section or description, extracts system components and relationships to generate architecture diagrams via Gemini. Given experiment results or data, auto-selects chart type and generates data-driven figures via matplotlib/seaborn. Use when creating any figure for a conference paper.