データ分析、機械学習、LLMアプリ、プロンプト設計（9,095 件）
从学生上传的课件/大纲/老师勾的重点/真题，一键初始化并验证备考工作区：解析 PDF、DOCX、PPTX、 XLSX、常见独立图片与 txt/md，建立分章节 LLM Wiki、标准题库、结构化接管队列与进度状态；仅在 Python 确实无法运行时 明确降级为手动写盘。当工作区尚未建立、资料发生变化、或建库 readiness 被阻断时使用。
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。
Andrej Karpathy的思维框架与表达方式。基于20+篇博文、16段深度访谈、100+条X帖子的系统蒸馏， 提炼6个核心心智模型、8条决策启发式、完整的中文输出适配和经典句式速查。 用途：作为思维顾问，用Karpathy的视角分析AI技术可靠性、学习方法、行业趋势、产品设计。 当用户提到「用Karpathy的视角」「Karpathy会怎么看」「卡帕西」「karpathy模式」时使用。 也适用于：Software 2.0/3.0讨论、vibe coding话题、神经网络训练、AI炒作判断、LLM能力边界。 即使用户只是说「从工程现实主义角度」「march of nines」「构建即理解」「锯齿状智能」也可触发。 不在用户只是普通问AI相关问题时触发——只在明确想要Karpathy式思维框架时激活。
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。
Financial trading CLIs — spot and perp trading on Hyperliquid, Binance, Coinbase, OKX. Prediction markets on Polymarket. Deposit and withdraw across chains. LLM-enriched price quotes with trend analysis. News and SEC filings. Historical backtesting with forward PnL analysis. Use when: user asks about stock/crypto prices, wants to trade, deposit, withdraw, check portfolio, or backtest a strategy.
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 finding literature, datasets, domain facts, citation details or licensed figure references.
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 adding, editing or reviewing skills, role prompts or skill metadata.
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。
Agnes AI API 接入支持与问题排查 Skill。帮助新用户完成 Agnes AI API 的接入配置， 诊断和解决接入过程中遇到的认证、参数、响应、图像生成、视频生成等各类问题。 涵盖 Thinking 模式开启、视频长度调节、流式输出、工具调用等高级功能指导。 兼容 OpenClaw、Claude Code、Hermes、Codex 等工具链。 thinking、stream、tool calling、模型选择、Base URL、响应格式、timeout、超时、轮询、 FAQ、问题排查、调试、免费调用、RPM、video_id、task_id、Prompt 模板、提示词、 生图、生视频、图生图、文生图、图生视频、文生视频、灰度自检、1M 上下文、4K 图片、4K 图、4K、灰度、自检、反馈、Bug、issue、问题反馈、功能建议。
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。
Write model-native Seedance 2.0 video prompts from text, images, video, or audio references. Use for text/image generation, multimodal reference, video editing, extension, track fill, or combined tasks that need stable subjects, explicit asset roles, coherent event order, camera, sound, visible text, and a 4–15 second feasibility check.
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。
Create a Seedance 2.0 prompt for a rough hand-drawn luminous entity that physically contacts a live-action space, continuously transforms while remaining traceable, escapes through adjacent geography, and is followed by a slightly delayed handheld camera. Use for playful 4–15 second mixed-media clips; not for horror, polished CG, unrelated cuts, or simple visual filters.
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 writing, changing or reviewing code that touches the house contract for Jetpack Compose and Compose Multiplatform apps: module graph, MVI/BaseViewModel, error tiers, state ownership, naming, Koin DI, Navigation 3 and coroutines. The compose skill is the entry point. Do NOT use for Gradle-only work (compose-project), new screens (compose-feature), composable-only work (compose-ui), repositories or persistence (compose-data), or expect/actual splits (compose-platform).
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。
Owns project and build-level work for Compose and Compose Multiplatform apps: bootstrapping a new project, adopting the kit in an existing project, adding or extracting a module, convention plugins in build-logic, the version catalog, and CI plus agent hooks. Use when starting a Compose Multiplatform app, adding a module, or editing settings.gradle.kts, build.gradle.kts, build-logic, libs.versions.toml, or packaging. Do NOT use for routing and architecture choices (compose-architecture), feature code (compose-feature), repositories and persistence (compose-data), composables or resources (compose-ui), or commonMain vs platform code (compose-platform).
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。
Owns platform splits for Compose Multiplatform apps: places declarations in commonMain, chooses expect/actual vs interface plus DI, wires host adapters and ports, and validates iOS/Swift interop, desktop and web targets, and platform lifecycle. Use when touching commonMain, expect, actual, iosMain, Swift, SKIE, Flow to Swift, desktop, wasm, web target, or platform-specific code. Do NOT use for routing or architecture (compose-architecture), feature slices (compose-feature), composables or resources (compose-ui), repositories or persistence (compose-data), or Gradle target setup (compose-project).
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。
Owns repositories, data sources and mapping for Compose and Compose Multiplatform apps: DTO to domain to UiModel boundaries, Ktor clients and bearer auth, WebSocket and SSE, Room, DataStore, Paging 3, offline-first and data-layer tests. Use when writing or reviewing a repository, data source, DTO, mapper, HttpClient, bearer token, WebSocket, SSE, Room DAO, migration, DataStore, PagingSource, RemoteMediator, offline cache or MockEngine test. Do NOT use for ViewModel or UI wiring (compose-feature), composables (compose-ui), the MVI contract or error tiers (compose-architecture), Gradle modules (compose-project), or commonMain vs platform splits (compose-platform).
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。
CUMCM 国赛、MCM/ICM 美赛与电工杯数学建模竞赛的端到端协作工作流。Use when a user explicitly works on one of these modeling contests or asks to run/review a modeling-competition paper from problem selection through modeling, solving, robustness, writing, compliance, and final submission review. Provides 10 stages, persistent decision state, competition-specific rules/templates, deterministic scoring helpers, numbered decisions, and Codex/Claude Code handoff. Do not trigger for generic model selection, ordinary data analysis, or non-competition paper review.
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。
Plugin shim for the mathmodel-skill competition workflow. Use when Codex invokes this plugin for a CUMCM, MCM/ICM, or Diangong Cup modeling-contest task, including problem selection, modeling, robustness, contest-paper writing, compliance, or final submission review. Do not use for generic data analysis or non-competition paper review.
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。
优化实际模型推理链路，将正确性对齐、分段 profiling、显存与数据搬运、TensorRT/ONNX/PyTorch 后端、attention/kernel、FP8/compile、缓存与少步采样、质量回归、GPU 成本和服务验收串成同一实验闭环。当用户要求推理提速、降低显存或 GPU 成本、复现模型效果、定位 GPU 利用率低、优化图像/视频/扩散模型或自托管 LLM 时使用，提供 model inference performance optimization 的脱敏案例。纯 API 调用、提示词或 token 用量优化，以及电脑卡顿，不进入本技能的模型推理实验流程。
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 claudraband CLI to control Claude Code sessions programmatically. Use when running, scripting, or automating Claude Code via the claudraband CLI — sending prompts, listing/resuming sessions, or working in interactive REPL mode. Triggers on any mention of claudraband, claudraband-cli, npx claudraband, bunx claudraband, or automating Claude Code sessions. Used when you need to ask yourself (Claude) a 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。
Use claudraband CLI and daemon workflows programmatically to send prompts, resume sessions, inspect status, and manage live session state. Use when running, scripting, or automating Claude Code via claudraband/`cband`, including startup prompt handling, `--connect` daemon mode, and ACP sessions.
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。
Interpret YouTube Analytics, TikTok Analytics, and video performance data. Identifies trends, explains metrics, and provides actionable recommendations for growth. Use when analyzing video performance, understanding metrics, or optimizing channel strategy.
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。
PostHog analytics, event tracking, feature flags, dashboards
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。
Generate images using Google's Nano Banana Pro (gemini-3-pro-image-preview). Accepts text prompts and optionally images (for editing/transformation) as INPUT. Returns generated IMAGES as OUTPUT. Use when user asks to create, generate, edit, or draw images, infographics, visualizations, diagrams, charts, or illustrations. Excellent for data-accurate infographics and text rendering.
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。
Filter and screen stocks by financial metrics like P/E ratio, market cap, dividend yield, and growth rates. Analyze and compare stocks from CSV data.
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。
n8n workflow automation knowledge base. Provides n8n node information, node functionality details, workflow patterns, and configuration examples. Covers triggers, data transformation, data input/output, AI integration, covering 10 nodes. Keywords: n8n, workflow, automation, node, trigger, webhook, http request, database, ai agent.
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。
Evaluates market bubble risk through quantitative data-driven analysis using the revised Minsky/Kindleberger framework v2.1. Prioritizes objective metrics (Put/Call, VIX, margin debt, breadth, IPO data) over subjective impressions. Features strict qualitative adjustment criteria with confirmation bias prevention. Supports practical investment decisions with mandatory data collection and mechanical scoring. Use when user asks about bubble risk, valuation concerns, or profit-taking timing.
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。
This skill should be used when analyzing weekly price charts for stocks, stock indices, cryptocurrencies, or forex pairs. Use this skill when the user provides chart images and requests technical analysis, trend identification, support/resistance levels, scenario planning, or probability assessments based purely on chart data without consideration of news or fundamental factors.
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。