「expert」の検索結果

Think and work like an expert Algorithms Researcher. Use when a task calls for Algorithms Researcher judgment. Reasons from separating problem, model, and cost model (comparison, word-RAM, arithmetic, online) through exchange/matroid greedy proofs, subproblem-DAG dynamic programming, max-flow min-cut and Goemans–Williamson primal-dual rounding, Karp–Rabin fingerprinting, competitive ratio and Yao's principle, PTAS/FPTAS (Williamson–Shmoys), and Instance Space Analysis over DIMACS10/MIPLIB 2017/SuiteSparse while treating amortized-versus-average-case conflation, unproven greedy killed by a 4-node counterexample, Monte Carlo without a false-match probability, DIMACS10 suite overfitting, and 'linear time' hiding word-size tricks over bit-length L as first-class failure modes.

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。

Think and work like an expert Algebraist. Use when a task calls for Algebraist judgment. Reasons from carriers, operations, and morphisms through isomorphism theorems, universal properties, exact-sequence and homological tools (Ext, Tor, snake lemma), and computational systems like GAP, Magma, SageMath, and Lean while treating silently smuggled hypotheses (commutativity, units, Noetherian, algebraically closed base), characteristic-p false friends, and noncanonical isomorphisms as first-class failure modes.

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。

Think and work like an expert Air Quality Scientist. Use when a task calls for Air Quality Scientist judgment. Reasons from source emissions through transformation, transport, and dose using SMOKE/MOVES inventories, WRF-driven CTMs like CMAQ and CAMx, PMF/ME-2 apportionment, and concentration-response functions, while treating rotational PMF ambiguity, AOD-to-PM bias in humid regions, uncalibrated low-cost sensors, and untreated wildfire exceptional events as first-class failure modes.

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。

Think and work like an expert AI Researcher. Use when a task calls for AI Researcher judgment. Reasons from data generating processes, inductive biases, and compute-data-algorithm trade-offs through train/val/test discipline, seed sweeps, ablation ladders, and standards like NeurIPS reproducibility checklists, model cards, and lm-eval-harness, while treating data leakage (Kapoor & Narayanan taxonomy), benchmark contamination, spurious correlations, and reward-model overoptimization as first-class failure modes.

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。

Think and work like an expert Agronomist. Use when a task calls for Agronomist judgment. Reasons from 4R stewardship and G×E×M through MRTN economic N, calibrated soil-test extractants, penetrometer compaction diagnosis, on-farm strip mixed models, partial budgets, and AgroEcoList reporting while treating pseudo-replication, yield-monitor drift, and yield-goal N over-application as first-class failure modes.

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。

Think and work like an expert Agroecologist. Use when a task calls for Agroecologist judgment. Reasons from socio-ecological farm systems, functional diversity, soil-biology-mediated fertility, and yield-service trade-offs through mother-baby and mixed-model trials, N/P/C mass balances, PLFA/amplicon and pollinator surveys, and NDVI/FRAGSTATS landscape analysis, while treating edge-effect and plot-size artifacts, weather-year confounding, surface-only soil carbon, and ignored labor/tenure adoption constraints as first-class failure modes.

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。

Think and work like an expert Agricultural Entomologist. Use when a task calls for Agricultural Entomologist judgment. Reasons from pest population dynamics, economic injury levels and thresholds, and degree-day phenology through systematic scouting, IRAC mode-of-action rotation, RCBD efficacy trials, and conservation biocontrol while treating misidentification, secondary pest flares from enemy removal, resistance under repeated MoA, and trap-catch-without-field-verification as first-class failure modes.

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。

Think and work like an expert Agricultural Engineer. Use when a task calls for Agricultural Engineer judgment. Reasons from mass, energy, and momentum balances on variable biological media through ET-based scheduling, psychrometric grain-drying balances, ASABE D497 draft estimates, EPANET pipe networks, and RTK-GNSS/ISOBUS precision-ag validation while treating soil compaction, clogged drip emitters, grain-bin hotspots, GPS drift, and uncalibrated yield monitors as first-class failure modes.

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。

Think and work like an expert Aerospace Engineer. Use when a task calls for Aerospace Engineer judgment. Reasons from margin-managed factors of safety, mass properties, and the analysis-test-similarity V&V hierarchy through FUN3D/SU2 CFD, NASTRAN/Abaqus FEA, JSBSim/Simulink 6-DOF, and FAR/CS, DO-178C, and NASA-STD compliance while treating flutter, buckling, inlet distortion, mass growth, and single-point failures as first-class failure modes.

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。

Think and work like an expert Aeronomy Scientist. Use when a task calls for Aeronomy Scientist judgment. Reasons from MLT lidar and ISR profiles through IRI/NRLMSIS benchmarks, treating ion-line spectra, metal-layer winds, and storm-time TEC as distinct observables.

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。

Think and work like an expert Aeronautical Engineer. Use when a task calls for Aeronautical Engineer judgment. Reasons from airfoil polars, drag buckets, and static margin through AVL/DATCOM stability derivatives, wind-tunnel blockage and wall corrections, FAR 25 §25.101–25.207 compliance matrices, and AC 25-7 flight-test evidence—not generic aerospace or pure CFD aerodynamics.

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。

Source technical and professional talent by combining LinkedIn profiles, GitHub contributions, and company intelligence. Identifies candidates with specific skills, assesses expertise depth, and provides outreach context for recruiting teams.

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 implementing features or fixing bugs with strict Test-Driven Development (TDD). Activate for coding tasks that require new functionality, refactoring, or comprehensive test coverage, especially when the user mentions TDD or Test Driven Development.

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。

Написание русскоязычной статьи или лонгрида с нуля: бриф, фактура, структура, черновик и самопроверка по методу Людмилы Сарычевой. Use this skill whenever the user asks to write, outline, structure, draft, assemble, or turn notes/interviews/materials into a Russian article, newsletter essay, longread, case, guide, or expert text. Триггеры: «напиши статью», «собери лонгрид», «напиши текст для блога про…», «есть интервью с экспертом, сделай статью», «составь план статьи», «придумай структуру», «собери материал», «сделай черновик», «напиши колонку», «из интервью в статью», «план лонгрида», «текст с нуля», «помоги написать материал». Для коротких постов в соцсети см. skill post; для правки готового текста — redaktura; для текстов интерфейса — ux-copy; для настройки проекта — redpolitika.

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。

TikTok Ads platform expertise. Audit campaigns, creative strategy, audience targeting, Spark Ads, TikTok Shop integration, pixel/Events API setup, and performance optimization. Use when the user asks about TikTok advertising, short-form video ads, TikTok Shop, Spark Ads, or social commerce advertising.

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。

LinkedIn Ads platform expertise. Audit campaigns, optimize targeting (job title, company, seniority, industry), creative strategy, Lead Gen Forms, conversion tracking, and ABM campaigns. Use when the user asks about LinkedIn advertising, B2B paid social, LinkedIn campaign optimization, Lead Gen Forms, Matched Audiences, or professional audience targeting.

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。

Klaviyo API and developer integration expertise. Event tracking, SDKs, webhooks, rate limits, OAuth, catalog sync, and code patterns. Use when the user asks about Klaviyo API, integrating with Klaviyo, tracking events, building custom integrations, webhook handling, or developer implementation. For marketing strategy, flow optimization, and campaign auditing, see the klaviyo-analyst skill.

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。

Google Tag Manager expertise. Audit GTM containers, design tag and trigger architecture, debug firing issues, implement consent mode v2, and advise on server-side tagging. Use when the user asks about GTM, tag management, container audits, consent mode, server-side tagging, or tracking implementation.

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。

Shopify e-commerce platform marketing expertise. Audit store performance, optimize conversion funnels, configure tracking, and integrate marketing tools. Use when the user asks about Shopify, e-commerce optimization, Shopify analytics, store conversion, product feeds, or Shopify app integrations.

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。

Generate structured research briefs from RSS feeds and web sources on any topic. Synthesizes multiple sources into actionable analysis with key findings, data points, expert perspectives, and content angles.

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。

Meta Ads (Facebook & Instagram) platform expertise. Audit campaigns, audiences, creative strategy, pixel tracking, and CAPI. Use when the user asks about Facebook Ads, Instagram Ads, Meta Ads, social media advertising, Advantage+ campaigns, or Meta pixel/CAPI setup.

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。

Braze customer engagement platform expertise. Audit campaigns, Canvases, segments, messaging channels, and data architecture. Use when the user asks about Braze, customer engagement, push notifications, in-app messaging, cross-channel orchestration, or lifecycle marketing at scale.

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。

Microsoft Advertising (Bing Ads) platform expertise. Audit campaigns, keywords, audiences, and UET tracking. Use when the user asks about Microsoft Ads, Bing Ads, search advertising on Microsoft, LinkedIn audience targeting, or Performance Max campaigns on Microsoft.

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。

Looker Studio (formerly Google Data Studio) expertise. Build dashboards, design data visualizations, connect data sources, and create marketing reports. Use when the user asks about Looker Studio, Data Studio, marketing dashboards, data visualization, report building, or connecting analytics data 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。