「analysis」の検索結果

Expert-level biomechanics covering musculoskeletal mechanics, gait analysis, joint biomechanics, soft tissue mechanics, bone mechanics, and sports biomechanics.

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Expert-level complex analysis knowledge. Use when working with complex functions, holomorphic functions, Cauchy's theorem, contour integration, Laurent series, residues, conformal mappings, or analytic continuation. Also use when the user mentions 'holomorphic', 'analytic', 'Cauchy theorem', 'residue', 'contour integral', 'Laurent series', 'conformal map', 'Riemann mapping', 'Mobius transformation', 'harmonic function', 'entire function', or 'meromorphic'.

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-level analytical chemistry knowledge. Use when working with chromatography, spectroscopy, electroanalytical methods, sample preparation, quantitative analysis, calibration, statistics, or instrumental analysis. Also use when the user mentions 'HPLC', 'GC', 'mass spectrometry', 'atomic absorption', 'ICP', 'titration', 'calibration curve', 'detection limit', 'NMR', 'chromatography', 'electrochemistry', 'sample preparation', or 'method validation'.

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Audit datasets, joins, labels, and ground truth before analysis or modeling. Use when data meaning, row grain, time semantics, source-of-truth reliability, or label construction may invalidate conclusions; not for general model evaluation after the evidence base is already trusted.

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Package completed data analysis and ML work so an independent recipient can reproduce the claimed results, verify artifact lineage, and operate the handoff within its stated scope. Use when finalizing a project, study, model package, or review bundle; not for deploying to a live system.

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Validate trained models and analytical claims against their intended decision, independent evidence, and human-reviewed ground truth. Use when reviewing model performance, analysis conclusions, launch claims, or evaluation reports; use failure diagnosis instead when the main task is locating a known defect.

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。

Orchestrate an end-to-end data analysis or machine learning project from decision framing through reproducible handoff. Use when a request spans multiple lifecycle stages or an ambiguous modeling request must become a decision-ready result; use narrower audit or experiment-design skills for isolated reviews.

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 deep Laravel project analysis: boot flow, request lifecycle, container usage, Eloquent/data flow, async systems, and Laravel-specific failure 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。

Use for deep React analysis: component tree, state flow, props flow, hooks usage, rendering behavior, and React-specific failure 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。

Use for deep Symfony project analysis: kernel/bootstrap, container wiring, routing/request flow, Doctrine, security, Messenger, and Symfony-specific failure patterns.

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Raw discovery primitives — project discovery, version resolution, docs loading, architecture mapping, execution flow. Called by `universal-project-analysis`. Single-pass scan → `project-analyzer`.

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 deep Node.js / Express project analysis: boot flow, middleware order, async behavior, data layer, auth/security, and Node-specific runtime failure 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。

Use for deep Next.js analysis: server vs client boundaries, routing, data fetching, caching, rendering modes, and hydration/runtime 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。

Use for deep Zend Framework or Laminas project analysis: bootstrap, config merge order, service manager, MVC flow, data layer, and migration-specific risks.

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。

Performance audit — bottleneck profiling, N+1 query detection, hot-path analysis; explicit request only, not part of regular feature work.

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Use when the user wants to know what will break if they change something, or needs safety analysis before editing code. Examples: "Is it safe to change X?", "What depends on this?", "What will break?"

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[Research] Use when a workflow step or the user asks for market analysis: competitors, TAM/SAM/SOM, trends, SWOT and customer segments.

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Creates marketing analytics reports, KPI dashboards, ROI calculations, and performance summaries for SME marketing teams. Handles weekly/monthly reporting, campaign analysis, content performance reviews, and data-driven recommendations. Use when user asks about marketing metrics, reporting, KPIs, dashboards, ROI analysis, performance review, or data-driven marketing decisions.

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Use when you need CRAP score and coverage risk analysis to find high-risk code before refactoring or release. Keywords: CRAP score, risk hotspots, cyclomatic complexity, test coverage gaps, coverage threshold.

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Use when you need blast-radius analysis, dependency graphs, cross-repo impact, breaking-change diff, or architectural overview of .NET workspaces. Keywords: blast radius, dependency graph, impact analysis, cross-repo, call graph, endpoint map, EF Core lineage, breaking change, daemon, reindex.

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 know what will break if they change something, or needs safety analysis before editing code. Examples: "Is it safe to change X?", "What depends on this?", "What will break?"

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。

多格式需求文档分析与整合。自动解析 Markdown、Excel、Word、思维导图文件，智能去重和补充需求信息，生成标准化的 PRD.md 文档。大文件采用分层提取避免上下文溢出；支持用户指定子目录输出；支持完整版/业务摘要版模板。可选集成 pencil-designer 生成可视化原型。适用场景：用户有多个需求来源需要整合、需要从零梳理需求、需要将模糊想法转化为结构化 PRD、需要可视化原型。触发词：需求分析、分析需求、整理需求、PRD、需求文档、需求梳理、梳理需求、可视化原型、页面设计。

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 Lingzao creator-content tools for Xiaohongshu/XHS, Douyin, and WeChat official-account public content. Lingzao supports XHS SEO, Xiaohongshu account analysis, benchmark account discovery, viral note breakdown, keyword research, one-stop content packages from keyword/link/image/inspiration material, title and cover optimization, hand-drawn route-map cards, city food maps, travel itinerary maps, life checklist maps, workflow manual maps, creator content workflow, note search, creator search, profile lookup, recent posts, deep profile copy/subtitle analysis, note/article detail, post comments, article stats, related articles, short-video copy extraction, and prompt-based creator image generation.

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。

Pre-breach impact analysis: inventories sensitive data (PII, PHI, PCI-DSS, credentials), traces data flows, scores exposure vectors, and produces a regulatory blast radius report with fine ranges sourced verbatim from GDPR Art. 83, CCPA § 1798.155(a), and HIPAA 45 CFR § 160.404. Cost benchmarks from IBM Cost of a Data Breach Report (annually updated). All citations in references/SOURCES.md for verification. Use when asked: "assess breach impact", "what data could be exposed", "calculate blast radius", "data exposure analysis", "how bad would a breach be", "quantify data risk", "sensitive data inventory", "data flow security audit", "pre-breach assessment", "worst-case breach scenario", "breach readiness", "data risk report", "/data-breach-blast-radius". For any stack handling user data, health records, or financial information. Output labels law-sourced figures (exact) vs heuristic estimates (planning only). Does not replace legal counsel.

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。