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概要と使いどころ
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.
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Scalable data processing for ML workloads. Streaming execution across CPU/GPU, supports Parquet/CSV/JSON/images. Integrates with Ray Train, PyTorch, TensorFlow. Scales from single machine to 100s of nodes. Use for batch inference, data preprocessing, multi-modal data loading, or distributed ETL pipelines.
日本語の概要は準備中です。原文の説明を表示しています。
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.
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Clean Architecture patterns for Android and Kotlin Multiplatform projects — module structure, dependency rules, UseCases, Repositories, and data layer patterns.
日本語の概要は準備中です。原文の説明を表示しています。
ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.
日本語の概要は準備中です。原文の説明を表示しています。
成本感知 LLM 管道，根据任务复杂度选择合适模型， 管理上下文预算，避免在长会话末尾做大型重构。
日本語の概要は準備中です。原文の説明を表示しています。
Look up vehicle data by Year, Make, and Model using the CarsXE YMM API. Use this when a user doesn't have a VIN but knows the year, make, and model of a vehicle and wants specs, trims, or features.
日本語の概要は準備中です。原文の説明を表示しています。
Use for VidSeeds MCP analytics and research - YouTube analytics, channel intelligence, video autopsy, outliers, competitors, trending/breakout discovery, keyword research, comment sentiment, and best-practices tools. Outcomes only; not internal scoring details.
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交互式 AI Agent 开发工作坊：通过 6 阶段深度协作对话，引导用户完成 Agent 需求分析、架构设计、 工具定义、Prompt 与编排设计、代码生成、验证迭代，产出可直接运行的 Agent 项目。 框架无关设计优先，支持 LangChain / EINO / AutoGen / AgentScope / CrewAI 等 ADK 框架。
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AI Agent 架构模式目录。提供 ReAct、Multi-Agent Conversation、Multi-Agent Workflow、 RAG Agent、Tool-Use Agent、Autonomous Agent 六种核心模式的参考架构、组件拓扑、 数据流、设计决策和框架无关的最佳实践。供 agent-dev-workshop Phase 2 调用。
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Draft or lint a bounded long-running goal prompt with a finish line and hard limits. Use when: selected by name; one change goes to Plan.
日本語の概要は準備中です。原文の説明を表示しています。
Run one prompt through headless Claude with scoped permissions and a time bound. Use when: scripting or automating a `claude -p` call, even a simple one.
日本語の概要は準備中です。原文の説明を表示しています。
Use when the user wants to translate a Bethesda Game Studios plugin (.esp/.esm/.esl) with bgs-translator/xtl, create or inspect a translation project, run LLM batch translation, generate prompt previews, or export SST/XML for xTranslator. Triggers - "translate this mod", "汉化这个 mod", "localize plugin", "build SST", "use xtl", "bgs-translator".
日本語の概要は準備中です。原文の説明を表示しています。
Investigate AI traces, observations, exceptions, latency, sessions, prompts, datasets, annotation queues, and scores through Langfuse MCP. Use when the request names Langfuse or asks to diagnose recorded AI behavior.
日本語の概要は準備中です。原文の説明を表示しています。
Personal-data-protection compliance reference for engineers building applications subject to Singapore PDPA, Indonesia UU PDP, Thailand PDPA, Malaysia PDPA, Philippines DPA (RA 10173), or Vietnam PDPL (91/2025/QH15). Use when reviewing or modifying code that touches personal data — signup/auth/consent, data export, account deletion, retention/purging, admin access to personal-data stores, third-party processors, breach response, or privacy/T&C documents.
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Install and use GrayMatter as an OpenClaw skill that provides primary durable memory, shared object-graph state, and authenticated access to the live api-docs schema via api-0. Use when the agent should persist durable memory, inspect organizational data models, and operate inside the business domain through RBAC-scoped API access.
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Set up Talivia revenue-first website analytics with MCP, then verify live traffic and revenue attribution.
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Analyze KiCad projects and PDF schematics: schematics, PCB layouts, Gerbers, footprints, symbols, netlists, and design rules. Reviews designs for bugs, traces nets, cross-references schematic to PCB, extracts BOM data, checks DRC/ERC, DFM, power trees, and regulator circuits. Every finding carries a confidence label and evidence source with trust_summary rollup. Analyzes PDF schematics from dev boards, reference designs, eval kits, and datasheets. Supports KiCad 5–10. Use whenever the user mentions .kicad_sch, .kicad_pcb, .kicad_pro, PCB design review, schematic analysis, PDF schematics, reference designs, Gerber files, DRC/ERC, netlist issues, BOM extraction, signal tracing, power budget, DFM, or wants to understand, debug, compare, or review any hardware design. Also for "check my board", "review before fab", "what's wrong with my schematic", "is this ready to order", "check my power supply", "verify this circuit", OSHWA certification readiness, or any electronics/PCB design question.
日本語の概要は準備中です。原文の説明を表示しています。
Reads existing brand DNA, keywords.csv, and prompts.csv, then produces a plan.csv — a strictly-schema'd content architecture telling the next pipeline step which pages to create, for which keyword/prompt clusters, and in what build order.
日本語の概要は準備中です。原文の説明を表示しています。
Creates data visualizations (charts, graphs, tables) optimized for AI engine parsing and citation. Produces inline SVG/HTML with text summaries, data tables, and JSON-LD so AI engines can quote the data.
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Adds a new LLM provider implementing LLMProvider interface with call() and stream() methods. Integrates with provider factory in src/llm/index.ts, config detection in src/llm/config.ts, and error handling via tracking and recovery. Use when adding a new model backend, integrating a third-party LLM API, or extending LLM platform support. Do NOT use for fixing bugs in existing providers, modifying existing provider behavior, or changing the LLMProvider interface.
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Apply integrations to existing projects with tanstack add, including add-on id resolution, dependency chains, option prompts, and .cta.json project metadata preconditions.
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Run the AI Search Hub browser automation scripts for Yuanbao, LongCat, Doubao, Qwen, Gemini, Grok, and MiniMax. Use this skill when the user wants to ask one of those sites a prompt, auto-start or attach to a Chrome DevTools session on port 9222, seed an isolated debug browser profile from the user's local browser data, detect whether login is required, wait for the user to finish logging in if needed, and then continue automatically.
日本語の概要は準備中です。原文の説明を表示しています。
INVOKE THIS SKILL when building ANY retrieval-augmented generation (RAG) system. Covers document loaders, RecursiveCharacterTextSplitter, embeddings (OpenAI), and vector stores (Chroma, FAISS, Pinecone).
日本語の概要は準備中です。原文の説明を表示しています。