「fundamental」の検索結果

Generative Engine Optimization for AI search engines (ChatGPT, Claude, Perplexity). Use when improving how content is discovered and cited by AI assistants.

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。

Three.js scene setup, cameras, renderer, Object3D hierarchy, coordinate systems. Use when setting up 3D scenes, creating cameras, configuring renderers, managing object hierarchies, or working with transforms.

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 China A-share stock analysis covering fundamental analysis, technical analysis, policy impact assessment, and market-specific features (T+1 trading, price limits, northbound capital flow). Use when user asks about A股分析, Chinese mainland stocks, Shanghai/Shenzhen listed stocks, or needs analysis considering China market characteristics.

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 you need to apply Java concurrency best practices — including thread safety fundamentals, ExecutorService thread pool management, concurrent design patterns like Producer-Consumer, asynchronous programming with CompletableFuture, immutability and safe publication, deadlock avoidance, virtual threads and structured concurrency, scoped values, backpressure, cancellation discipline, and observability for concurrent systems. Part of the skills-for-java 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。

Complete guide for building beautiful apps with Expo Router. Covers fundamentals, styling, components, navigation, animations, patterns, and native tabs.

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。

Perform structured investment research (投研分析) for a company/stock/ETF/sector using a repeatable framework: fundamentals (basic/财务报表与商业模式), technical analysis (技术指标与关键价位), industry research (行业景气与竞争格局), valuation (估值对比/情景), catalysts and risks, and produce a professional research report + actionable plan. Use when the user asks for: equity/ETF analysis, earnings/financial statement breakdown, peer/industry comparison, valuation ranges, bull/base/bear scenarios, technical trend/support-resistance, or a full research memo.

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。

Core principles and golden rules for writing production-quality Ansible automation, covering FQCN requirements, module selection guidance, and execution patterns using uv run.

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。

用财务指标快速排除垃圾股，找到有基本面支撑的标的。用于A股基本面选股。

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。

Add moments of joy, personality, and surprise through success states, empty states, loading moments, hover details, and celebratory polish once the fundamentals already work. Use when the user wants delight, charm, personality, or memorable micro-interactions—not when the main need is baseline cleanup or stronger visual 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。

Complete guide for TUnit new-generation testing framework. Use when creating test projects with TUnit or migrating from xUnit to TUnit. Covers Source Generator driven test discovery, AOT compilation support, fluent async assertions. Includes project creation, [Test] attribute, lifecycle management, parallel control, and xUnit syntax comparison. Keywords: TUnit, tunit testing, source generator testing, AOT testing, new generation testing framework, [Test], [Arguments], TUnit.Assertions, Assert.That, Before(Test), After(Test), NotInParallel, TUnit.Templates, Microsoft.Testing.Platform, TUnit vs xUnit, parallel execution

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。

Generative Engine Optimization for AI search engines (ChatGPT, Claude, Perplexity).

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。

Data structures and algorithms for AI agent episodic memory. Covers vector stores (HNSW, IVF, PQ), temporal indexing, knowledge graphs with triple stores, hierarchical summarization, forgetting curves, working/long-term/ procedural memory, and memory consolidation. Deep analysis of MemGPT/Letta, Zep/Graphiti, Mem0, and the Stanford generative agents memory architecture. Teaches the CS fundamentals behind how agents remember, retrieve, and forget. Activate on: "agent memory", "episodic memory", "vector search algorithm", "HNSW", "memory retrieval", "forgetting curve", "knowledge graph memory", "MemGPT", "Letta", "Zep", "Mem0", "memory consolidation", "temporal retrieval", "agent long-term memory", "memory layer". NOT for: conversation protocol design (use agent-conversation-protocols), agent infrastructure selection (use agentic-infrastructure-2026), building RAG pipelines (use ai-engineer).

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。