「pert」の検索結果

Expert interior designer with deep knowledge of space planning, color theory (Munsell, NCS), lighting design (IES standards), furniture proportions, and AI-assisted visualization. Use for room layout optimization, lighting calculations, color palette selection for interiors, furniture placement, style consultation. Activate on "interior design", "room layout", "lighting design", "furniture placement", "space planning", "Munsell color". NOT for exterior/landscape design, architectural structure, web/UI design (use web-design-expert), brand color theory (use color-theory-palette-harmony-expert), or building codes/permits.

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 in temporal event detection, spatio-temporal clustering (ST-DBSCAN), and photo context understanding. Use for detecting photo events, clustering by time/location, shareability prediction, place recognition, event significance scoring, and life event detection. Activate on 'event detection', 'temporal clustering', 'ST-DBSCAN', 'spatio-temporal', 'shareability prediction', 'place recognition', 'life events', 'photo events', 'temporal diversity'. NOT for individual photo aesthetic quality (use photo-composition-critic), color palette analysis (use color-theory-palette-harmony-expert), face recognition implementation (use photo-content-recognition-curation-expert), or basic EXIF timestamp extraction.

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。

Advanced CV for infrastructure inspection including forest fire detection, wildfire precondition assessment, roof inspection, hail damage analysis, thermal imaging, and 3D Gaussian Splatting reconstruction. Expert in multi-modal detection, insurance risk modeling, and reinsurance data pipelines. Activate on "fire detection", "wildfire risk", "roof inspection", "hail damage", "thermal analysis", "Gaussian Splatting", "3DGS", "insurance inspection", "defensible space", "property assessment", "catastrophe modeling", "NDVI", "fuel load". NOT for general drone flight control, SLAM, path planning, or sensor fusion (use drone-cv-expert), GPU shader development (use metal-shader-expert), or generic object detection without inspection context (use clip-aware-embeddings).

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。

Diagnose when intuitive judgment, agent confidence, or expert routing can be trusted by classifying environment validity, feedback quality, and task-boundary fit. Use for confidence calibration, agent routing, expertise audits, and escalation design. NOT for deterministic implementation tasks, pure syntax debugging, or domains with explicit verifiable answers.

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 orbital mechanics covering Keplerian orbits, orbital maneuvers, Hohmann transfers, rendezvous, interplanetary trajectories, and perturbations.

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 ceramics covering ceramic bonding, processing, mechanical properties, thermal properties, electronic ceramics, and ceramic applications in engineering.

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。

Determines whether a hypertensive patient should be screened for primary aldosteronism based on clinical features associated with higher PA prevalence. Triggered when a clinician asks 'Should I screen this hypertensive patient for PA?' or observes spontaneous hypokalemia, resistant hypertension, hypertension onset before age 40, adrenal tumor, young-onset stroke, or sleep apnea syndrome.

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。

Decide whether a kidney from a brain-dead deceased donor (DBD) with diabetes mellitus and/or hypertension is suitable for transplantation, using the ISOT 2025 Delphi consensus and Table 4 eligibility checklist. Trigger when a clinician asks "can I use a kidney from a diabetic deceased donor", "is this DBD with HTN/DM acceptable", "ECD donor with diabetes — accept or decline", "DBD eligibility for hypertensive donor", or shares a deceased donor with diabetes or hypertension and needs an accept/borderline/decline decision.

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。

4人の異なる専門家ペルソナ（20年ベテランエンジニア、TDDエキスパート、Clean Codeエキスパート、バグハンター）で ソースコードを批判的にレビューするスキル。設計判断、テスト容易性、可読性、バグ検出の観点から コードの問題を検出し、改善提案を行う。Python/JavaScriptに対しては追加のチェックポイントを適用。 バグハンターは状態遷移、例外パス、依存関係、非同期競合に特化し、本番環境での問題を事前に検出する。 Use when reviewing source code from multiple expert perspectives to find design flaws, testability issues, code quality problems, and runtime bugs. Triggers: "critical code review", "multi-persona code review", "expert code review", "code quality assessment", "find bugs".

Erstellt und verwendet einen anbieterneutralen semantischen Routing-Graphen aus Personas, koordinierenden Rollen, Experten und aktiven Skill-Endpunkten. Verwenden, wenn ein LLM eine Anfrage von einer Leitrolle über einen Experten zu einem Skill routen, aus einem vorhandenen Agentensystem einen portablen Persona-Router extrahieren, eine semantische Domänenkarte mit einer lexikalischen Skill-Registry kombinieren oder fehlende Verbindungen zwischen Rolle und Skill sichtbar machen soll, statt still auf einen Ersatz zurückzufallen. Auslöser sind unter anderem semantisches Persona-Routing, Persona-Umbrella, Rollen-Router, Boss-Agent-Experten-Skill-Routing, Agentenrollen-Export oder die Wiederverwendung von Personas über mehrere LLM-Anbieter hinweg.

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。

Guide for diagnosing and improving MSBuild project evaluation performance. Only activate in MSBuild/.NET build context. USE FOR: builds slow before any compilation starts, high evaluation time in binlog analysis, expensive glob patterns walking large directories (node_modules, .git, bin/obj), deep import chains (>20 levels), preprocessed output >10K lines indicating heavy evaluation, property functions with file I/O ($([System.IO.File]::ReadAllText(...))), multiple evaluations per project. Covers the 5 MSBuild evaluation phases, glob optimization via DefaultItemExcludes, import chain analysis with /pp preprocessing. DO NOT USE FOR: compilation-time slowness (use build-perf-diagnostics), incremental build issues (use incremental-build), non-MSBuild build systems. INVOKES: binlog MCP server tools (evaluations, evaluation_global_properties, evaluation_properties, imports, properties); falls back to dotnet msbuild -pp:full.xml for preprocessing, /clp:PerformanceSummary.

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。

Nest.js framework expert specializing in module architecture, dependency injection, middleware, guards, interceptors, testing with Jest/Supertest, TypeORM/Mongoose integration, and Passport.js authentication. Use PROACTIVELY for any Nest.js application issues including architecture decisions, testing strategies, performance optimization, or debugging complex dependency injection problems. If a specialized expert is a better fit, I will recommend switching and stop.

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。

Train Mixture of Experts (MoE) models using DeepSpeed or HuggingFace. Use when training large-scale models with limited compute (5× cost reduction vs dense models), implementing sparse architectures like Mixtral 8x7B or DeepSeek-V3, or scaling model capacity without proportional compute increase. Covers MoE architectures, routing mechanisms, load balancing, expert parallelism, and inference 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。

MCP server for scraping Italian rental/sale property listings from multiple real estate portals (Immobiliare.it, Casa.it, and extensible to others) using Camoufox (anti-detection browser) and BeautifulSoup. Plugin architecture — each site is a self-contained adapter with its own URL templates, query param mappings, and CSS selector chains. Use this skill whenever the user wants to search for apartments, houses, or properties in Italy, scrape real estate listings, compare rental prices across Italian cities, or extract property data from Italian portals. Triggers on mentions of immobiliare, casa.it, Italian rentals, affitto, vendita, apartment hunting in Italy, or property scraping.

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 in temporal event detection, spatio-temporal clustering (ST-DBSCAN), and photo context understanding. Use for detecting photo events, clustering by time/location, shareability prediction, place recognition, event significance scoring, and life event detection. Activate on 'event detection', 'temporal clustering', 'ST-DBSCAN', 'spatio-temporal', 'shareability prediction', 'place recognition', 'life events', 'photo events', 'temporal diversity'. NOT for individual photo aesthetic quality (use photo-composition-critic), color palette analysis (use color-theory-palette-harmony-expert), face recognition implementation (use photo-content-recognition-curation-expert), or basic EXIF timestamp extraction.

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。

Advanced CV for infrastructure inspection including forest fire detection, wildfire precondition assessment, roof inspection, hail damage analysis, thermal imaging, and 3D Gaussian Splatting reconstruction. Expert in multi-modal detection, insurance risk modeling, and reinsurance data pipelines. Activate on "fire detection", "wildfire risk", "roof inspection", "hail damage", "thermal analysis", "Gaussian Splatting", "3DGS", "insurance inspection", "defensible space", "property assessment", "catastrophe modeling", "NDVI", "fuel load". NOT for general drone flight control, SLAM, path planning, or sensor fusion (use drone-cv-expert), GPU shader development (use metal-shader-expert), or generic object detection without inspection context (use clip-aware-embeddings).

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。

Diagnose when intuitive judgment, agent confidence, or expert routing can be trusted by classifying environment validity, feedback quality, and task-boundary fit. Use for confidence calibration, agent routing, expertise audits, and escalation design. NOT for deterministic implementation tasks, pure syntax debugging, or domains with explicit verifiable answers.

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。

Runs an iterative, conversational product-discovery process with a founder/stakeholder: structured interview, live low-fi wireframing, a linked feature/page node-graph built up as you go, a founder-confirmed lock-in checkpoint, then a generated PRD, a Mermaid-rendered sitemap, and a mockup with a full design system (palette, typography, dark mode). Use when building or operating an AI product-discovery chatbot, or when running founder/stakeholder discovery by hand and you need the structure (interview script, node-graph schema, PRD template, design-system handoff order). NOT for implementing the spec'd product once locked — hand off to feature-specific skills (ideal-web-app-builder, tailwind-v4-expert, color-theory-palette-harmony-expert, typography-expert, dark-mode-design-expert) for that. NOT for one-shot PRD generation without an interview loop — if the founder already has a written spec, this process is unnecessary overhead.

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。

Diagnose when intuitive judgment, agent confidence, or expert routing can be trusted by classifying environment validity, feedback quality, and task-boundary fit. Use for confidence calibration, agent routing, expertise audits, and escalation design. NOT for deterministic implementation tasks, pure syntax debugging, or domains with explicit verifiable answers.

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。

Obsidianの公式CLIでノートを検索・作成・編集し、日々の記録やタスク、リンク、プロパティも扱います。ノート保管庫を指定した操作にも対応します。

• 会議メモやプロジェクト記録を探したいとき
• 日次ノートに記録を追加したいとき
• 未完了タスクを確認・完了したいとき

公開データベースで化合物の活性や分子の性質、薬の相互作用を調べます。経口薬の候補としての特徴や遺伝子と疾患の関連を整理し、創薬研究の調査を支援します。

• 作用対象に合う活性化合物を探す
• 経口薬候補の分子特性を評価
• 相互作用と有害事象報告の調査

Use when implementing animated gradients, complex CSS transitions that involve custom property values, or building a typed design token system where custom property misuse should produce visible errors.

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 expert to the Remotion experts page

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。

Manages Google Analytics account and property settings, enables the Analytics Admin API via the Cloud CLI, lists accounts and properties, and manages data streams, custom dimensions, conversion events, and integrations. Use when you need to programmatically configure Google Analytics accounts, provision properties, manage data retention, configure Measurement Protocol secrets, or manage Firebase and Google Ads links.

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。