6,452 件 ・ 関連度順
概要と使いどころ
Reviews SwiftData code for model design, queries, concurrency, and migrations. Use when reviewing .swift files with import SwiftData, @Model, @Query, @ModelActor, or VersionedSchema.
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。
Geospatial risk modeling including catastrophe models, exposure analysis, and underwriting. Use when assessing spatial risk, building catastrophe models, analyzing exposure/hazard/vulnerability, or computing portfolio risk metrics.
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。
Analyze agricultural climate risk systems for weather impact modeling, crop insurance, drought/flood prediction, soil moisture, and carbon tracking. Use when: 'assess crop climate risk', 'evaluate weather yield models', 'review crop insurance integration', 'audit drought prediction', 'check carbon sequestration tracking', 'analyze farm adaptation planning', 'evaluate DSSAT or APSIM models'.
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。
Design a model training pipeline — algorithm selection, cross-validation, and serialization. Use when asked to "train a model for this", "design a training pipeline", or "which algorithm should we use".
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。
Design and configure model serving infrastructure — endpoint scaling, batching, GPU allocation. Use when asked to "serve this model", "design an inference endpoint", or "size GPU allocation for serving".
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。
Expert guide for late-2026 frontier AI models — Google Gemini 4 Pro & Project Astra, Anthropic Claude 5.1 (Fable/Mythos), and Enterprise Frontier Safeguards (EFS) / Panduan ahli model AI frontier akhir-2026 — Google Gemini 4 Pro & Project Astra, Anthropic Claude 5.1 (Fable/Mythos), dan Enterprise Frontier Safeguards (EFS).
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。
Expert guide for intelligent model cascading and routing — complexity-scored task routing from Flash/Haiku to Sonnet/Opus/Astra, dynamic escalation with quality gates, 40-60% token cost reduction while maintaining output quality / Panduan ahli untuk kaskade dan routing model cerdas — routing tugas berbasis skor kompleksitas dari Flash/Haiku ke Sonnet/Opus/Astra, eskalasi dinamis dengan gerbang kualitas, pengurangan biaya token 40-60% dengan kualitas output terjaga.
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。
Bias detection and mitigation, fairness metrics, privacy frameworks, consent models, transparency requirements, and accountability structures for data science practice. Covers algorithmic bias sources, disparate impact testing, differential privacy, GDPR principles, model cards, datasheets for datasets, responsible AI frameworks, and the organizational governance needed to make ethics actionable. Use when auditing models for bias, designing privacy-preserving systems, establishing governance processes, or evaluating the social impact of data-driven decisions.
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。
多模型镜头提示词适配：把一份分镜表改写成适合不同视频生成模型的提示词（中/英、首帧/首尾帧/纯文生视频、运镜词表、负面约束），模型中立、不编造价格或参数。Use when the user wants the same shot list adapted for Seedance, 可灵 Kling, Veo, Runway, Hailuo/海螺, Wan/通义万相, Sora, Pika or 'any video model', asks 怎么写视频提示词, camera movement terms, or a model returns deformed products.
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。
Reviews LLM integration, prompt templates, model selection, token/cost budgets, evaluation harnesses, structured outputs, retries, and streaming. Checks trust boundaries and task evidence against the selected provider/model contract rather than prescribing universal model tiers or sampling settings.
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。
When the user wants to apply psychological principles, mental models, or behavioral science to marketing. Also use when the user mentions 'psychology,' 'mental models,' 'cognitive bias,' 'persuasion,' 'behavioral science,' 'why people buy,' 'decision-making,' or 'consumer behavior.' This skill provides 70+ mental models organized for marketing application.
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。
Quantitative strategy frameworks: pairs trading/cointegration, volatility regime strategies, seasonality/calendar effects, multi-factor models (IC/IR), factor research and screening, correlation analysis, statistical methods (ADF/GARCH), strategy optimization, execution modeling, hedging, and ML-based prediction (sklearn). Also provides CLI access to run indicator scripts against K-line data. Triggers: "量化", "因子", "配对交易", "协整", "波动率策略", "季节性", "多因子", "IC", "机器学习", "对冲", "量化策略", "協整", "波動率策略", "季節性", "多因子", "對沖", "quant", "pairs trading", "cointegration", "volatility strategy", "seasonality", "multi-factor", "factor model", "IC IR", "machine learning", "hedging", "walk-forward", "配對交易", "機器學習", "因子選股"
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。
Comprehensive AI/ML development guide for LangChain, LangGraph, and ML model integration in FastAPI. Use when building LLM applications, agents, RAG systems, sentiment analysis, aspect-based analysis, chain orchestration, prompt engineering, vector stores, embeddings, or integrating ML models with FastAPI endpoints. Covers LangChain patterns, LangGraph state machines, model deployment, API integration, streaming, error handling, and best practices.
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。
Guidance for selecting appropriate AI model (sonnet vs haiku) based on task complexity, reasoning requirements, and performance needs. Use when implementing agents or justifying model selection.
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。
Add a new AI model to a provider (anthropic, openai, groq, cerebras). Use when a new model is announced and needs to be supported in aico.
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。
Helps users set up and run MobiZen-GUI to perform mobile-use tasks — automating Android phone operations via natural language. Use when the user wants to control a phone, execute mobile-use tasks, install/configure MobiZen-GUI, deploy MobiZen-GUI-4B model, or customize the agent's input/output. Triggers on keywords like phone task, mobile-use, mobile automation, Android control, MobiZen, ADB, deploy model, run agent, configure model.
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。
Model selection strategy and routing. Use when choosing between models for different task types, subagent configurations, or optimizing token cost vs quality tradeoffs.
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。
Builds currency hedging models with rolling forward programs, option-based strategies, and cross-hedge analysis for international portfolios. Use when designing hedge programs, analyzing hedge ratios, or evaluating FX protection costs.
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。
Calculates potential future exposure and CVA with simulation-based approaches and netting agreement analysis. Use when modeling counterparty exposure, calculating CVA/DVA, or assessing counterparty risk.
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。
Analyzes construction risk with EPC contract review, delay and cost overrun scenarios, and completion guarantee structures. Use when modeling construction risk, evaluating EPC terms, or stress testing project timelines.
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。
Analyzes structural interest rate exposure with fixed/floating mismatch, basis risk, and cap/floor adequacy assessment. Use when modeling structural rate risk, analyzing basis risk, or evaluating interest rate hedging needs.
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。
Designs rebalancing triggers with calendar-based, threshold-based, and hybrid approaches with tax and cost optimization. Use when designing rebalancing rules, optimizing rebalancing frequency, or modeling turnover impact.
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。
Builds economic profit (EVA) models with capital charge calculation, value spread analysis, and long-term value creation measurement. Use when calculating economic profit, analyzing EVA trends, or measuring value creation.
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。
Assesses energy transition investments with battery storage, grid modernization, EV charging, and hydrogen infrastructure analysis. Use when modeling energy transition assets, evaluating storage economics, or analyzing grid infrastructure.
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。