「log」の検索結果

When the user requests information about academic benchmarks, datasets, or research papers, particularly in machine learning, deep learning, or logical reasoning domains. This skill enables systematic research of academic benchmarks by searching web sources, downloading and analyzing arXiv papers, extracting key metadata (number of tasks, training availability, difficulty levels), and compiling comparative summaries. It triggers on requests involving dataset comparisons, benchmark analysis, or academic paper research for table 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。

Master skill for Abaqus FEA scripting. Use for any finite element analysis, topology optimization, or Abaqus Python scripting task. Routes to appropriate specialized skills.

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。

Configure Tosca optimization. Use when user mentions design response, objective function, optimization constraint, or SIMP penalty. Base module for topology/shape optimization.

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 documentation with gaming-specific examples, retro styling, and 8-bit terminology. Apply when documenting gaming blocks, RPG components, or retro-styled UI elements.

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 pack 3D boxes into containers, optimize 3D space utilization, or solve container loading problems. Also use when the user mentions "3D packing," "container packing," "box packing," "3D bin packing problem," "cube packing," "three-dimensional packing," "cargo loading," or "space optimization." For pallet-specific loading, see pallet-loading. For container logistics, see container-loading-optimization.

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。

[31] ANALYZE. Universal deep thinking methodology for any situation requiring quality reasoning. Use when solving problems, debugging, making decisions, analyzing code, planning, reviewing, or anytime you need thorough thinking instead of surface-level responses. Triggers on "think deeply", "analyze thoroughly", "reason carefully", "deep thinking", "understand completely", or any task requiring careful thought.

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 and fix production errors from Sentry crash reports. Use when investigating AppHang, ANR, crashes, or production errors. Includes complete workflow from JSON analysis to bug fix implementation with evidence-based methodology. Triggers on sentry, crash, AppHang, ANR, error analysis, production error, bug analysis, crash report, freeze, hang, not responding, stacktrace, breadcrumbs, exception.

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。

[22] UNDERSTAND. Deep research from all sources — internal (code, git, logs) AND external (web, docs, best practices). Use when choosing libraries, investigating solutions, understanding legal/technical questions, comparing approaches, or anytime you need comprehensive knowledge from both project context and world knowledge. Triggers on "research", "investigate", "find best approach", "what do others do", "compare options", or complex questions requiring multiple sources.

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。

[21] UNDERSTAND. Deep research workflow for this project using 150% scope (100% core + 50% boundary), evidence-based reasoning, and structured investigation notes. Use when the task requires investigation, root-cause analysis, or mapping unknown areas. Always maintain a research log file that captures findings, hypotheses, and next branches; use web.run when external verification is needed.

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 12-Factor App compliance analysis on any codebase. Use when evaluating application architecture, auditing SaaS applications, or reviewing cloud-native applications against the original 12-Factor methodology.

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。

macOS アプリのクラッシュログ (.ips) を解析し、根本原因を特定するスキル。「クラッシュした」「crash」「.ips」「DiagnosticReports」「SIGSEGV / SIGABRT」で発火。**macOS 専用**（.ips の読み方が macOS の DiagnosticReports 前提。iOS の .ips は未対応）。解析は crash-analyzer subagent に委譲する。クラッシュログが存在しない一般のバグ調査・テスト失敗には使わない。

Conduct market research, competitive analysis, investor due diligence, and industry intelligence with source attribution and decision-oriented summaries. Use when the user wants market sizing, competitor comparisons, fund research, technology scans, or research that informs business 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。

Perl testing patterns using Test2::V0, Test::More, prove runner, mocking, coverage with Devel::Cover, and TDD methodology.

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。

Python testing strategies using pytest, TDD methodology, fixtures, mocking, parametrization, and coverage requirements.

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。

Spring Boot architecture patterns, REST API design, layered services, data access, caching, async processing, and logging. Use for Java Spring Boot backend work.

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。

Codified expertise for quality control, non-conformance investigation, root cause analysis, corrective action, and supplier quality management in regulated manufacturing. Informed by quality engineers with 15+ years experience across FDA, IATF 16949, and AS9100 environments. Includes NCR lifecycle management, CAPA systems, SPC interpretation, and audit methodology. Use when investigating non-conformances, performing root cause analysis, managing CAPAs, interpreting SPC data, or handling supplier quality issues.

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。

Kotlin testing patterns with Kotest, MockK, coroutine testing, property-based testing, and Kover coverage. Follows TDD methodology with idiomatic Kotlin 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。

AI-assisted video editing workflows for cutting, structuring, and augmenting real footage. Covers the full pipeline from raw capture through FFmpeg, Remotion, ElevenLabs, fal.ai, and final polish in Descript or CapCut. Use when the user wants to edit video, cut footage, create vlogs, or build video content.

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。

Suggests manual context compaction at logical intervals to preserve context through task phases rather than arbitrary auto-compaction.

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。

Cost optimization patterns for LLM API usage — model routing by task complexity, budget tracking, retry logic, and prompt caching.

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。

Go testing patterns including table-driven tests, subtests, benchmarks, fuzzing, and test coverage. Follows TDD methodology with idiomatic Go 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。

Turn a one-line objective into a step-by-step construction plan for multi-session, multi-agent engineering projects. Each step has a self-contained context brief so a fresh agent can execute it cold. Includes adversarial review gate, dependency graph, parallel step detection, anti-pattern catalog, and plan mutation protocol. TRIGGER when: user requests a plan, blueprint, or roadmap for a complex multi-PR task, or describes work that needs multiple sessions. DO NOT TRIGGER when: task is completable in a single PR or fewer than 3 tool calls, or user says "just do it".

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。

Codified expertise for customs documentation, tariff classification, duty optimization, restricted party screening, and regulatory compliance across multiple jurisdictions. Informed by trade compliance specialists with 15+ years experience. Includes HS classification logic, Incoterms application, FTA utilization, and penalty mitigation. Use when handling customs clearance, tariff classification, trade compliance, import/export documentation, or duty optimization.

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 articles, guides, blog posts, tutorials, newsletter issues, and other long-form content in a distinctive voice derived from supplied examples or brand guidance. Use when the user wants polished written content longer than a paragraph, especially when voice consistency, structure, and credibility matter.

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。