132 件 ・ 関連度順
概要と使いどころ
Decompose and explain healthcare cost growth into contributing factors including utilization changes, unit price shifts, case mix evolution, and population changes. Use when analyzing PMPM cost trends, explaining cost variance to leadership, preparing actuarial summaries, or identifying cost reduction opportunities.
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。
Assesses physical and transition climate risk for CRE properties and portfolios. Translates hazard exposure (flood, wind, wildfire, extreme heat, sea level rise) and regulatory/market shifts into financial impacts on NOI, cap rates, insurance costs, and tenant demand. Produces dollar-denominated risk, not abstract hazard scores.
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。
Stellar spectral analysis from first light to chemical abundance. Covers continuum emission and absorption, the OBAFGKM classification sequence, luminosity classes, line identification, Doppler shifts, curve-of-growth abundance analysis, and the astrophysical conclusions that follow from a spectrum. Use when classifying a star, measuring radial velocity, inferring composition or temperature, or teaching why the Sun is mostly hydrogen.
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。
Optimize Core Web Vitals (LCP, INP, CLS) for better page experience and search ranking. Use when the task involves `improve Core Web Vitals`, `fix LCP`, `reduce CLS`, `optimize INP`, `page experience optimization`, or `fix layout shifts`.
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。
Optimize Core Web Vitals (LCP, INP, CLS) for better page experience and search ranking. Use when asked to "improve Core Web Vitals", "fix LCP", "reduce CLS", "optimize INP", "page experience optimization", or "fix layout shifts".
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。
Optimize Core Web Vitals (LCP, INP, CLS) for better page experience and search ranking. Use when the task involves `improve Core Web Vitals`, `fix LCP`, `reduce CLS`, `optimize INP`, `page experience optimization`, or `fix layout shifts`.
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。
Analyzes web performance using Chrome DevTools MCP. Measures Core Web Vitals (LCP, INP, CLS) and supplementary metrics (FCP, TBT, Speed Index), identifies render-blocking resources, network dependency chains, layout shifts, caching issues, and accessibility gaps. Use when asked to audit, profile, debug, or optimize page load performance, Lighthouse scores, or site speed. Biases towards retrieval from current documentation over pre-trained knowledge.
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 or update an ADR under `docs/ADR/` for architectural decisions, dependency changes, data-model changes, or cross-cutting policy shifts. Use when the user asks to write, update, or document an ADR, record a design decision, capture architecture trade-offs, or justify a repo-wide technical policy.
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。
Builds regime detection models with hidden Markov, threshold, and Bayesian change-point methodologies for strategy adaptation. Use when modeling regime changes, detecting market shifts, or adapting strategies to market conditions.
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。
Monitors market regime signals with volatility clustering, correlation dynamics, and liquidity condition assessment. Use when analyzing market regimes, detecting regime shifts, or adjusting strategy for market conditions.
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。
Implement comprehensive model drift monitoring using Evidently AI, statistical tests (PSI, KS), and custom metrics to detect data drift and concept drift in production ML systems. Set up automated alerting and reporting workflows to catch degradation before it impacts business metrics. Use when production models show unexplained performance degradation, when new data distributions differ from training data, when seasonal shifts affect input features, or when regulatory requirements mandate model monitoring.
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。
"Apply the Dynamic Capabilities framework (Teece et al., 1997) — sensing, seizing, and transforming — to analyze how firms adapt, integrate, and reconfigure competences in rapidly changing environments. Use this skill when the user needs to explain why some firms sustain advantage while others decline, evaluate organizational agility, distinguish operational from strategic capabilities, or when they ask 'how do we stay competitive as the market shifts', 'why did this firm fail to adapt', or 'what capabilities do we need to build'.".
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。
"Apply Kuhn's paradigm theory to analyze scientific progress through the cycle of normal science, anomalies, crisis, and revolution. Use this skill when the user needs to understand why a field resists change, trace paradigm shifts in a discipline, analyze incommensurability between competing frameworks, or when they ask 'why do scientists ignore contradictory evidence', 'how do scientific revolutions happen', or 'why can't proponents of different paradigms agree'.".
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。
"Apply Complex Adaptive Systems theory to analyze phenomena exhibiting emergence, self-organization, co-evolution, and edge-of-chaos dynamics. Use this skill when the user needs to understand why a system behaves unpredictably despite known components, model agent-based interactions that produce emergent outcomes, analyze fitness landscapes, or when they ask 'why does this system behave in ways no one designed', 'how do local interactions create global patterns', or 'why do small changes sometimes cause massive system shifts'.".
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。
"Apply supply and demand analysis to explain price determination, market equilibrium, and the effects of policy interventions. Use this skill when the user needs to analyze how prices are set in a market, predict the effect of taxes/subsidies/price controls, or understand shifts in supply or demand curves — even if they say 'why did the price go up', 'what happens if the government sets a price cap', or 'how does a tariff affect the market'.".
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。
"Implement Statistical Process Control charts to monitor production process stability. Use this skill when the user needs to detect process shifts, set control limits, or distinguish common cause from special cause variation — even if they say 'process monitoring', 'control chart', or 'is our process in control'.".
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。
Frappe HRMS and ERPNext HR guidance for employees, attendance, leave, payroll, shifts, expense claims, recruitment, onboarding, and HR workflows. Use when work touches HRMS or people operations in the Frappe ecosystem.
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 planning, implementing, or reviewing frontend dependency upgrades, package migrations, lockfile changes, major framework version bumps, CVE remediation, peer dependency conflicts, ESM/CJS shifts, build-tool compatibility, or CI verification matrices; Chinese triggers include dependency upgrades, version upgrades, lockfile, peer dependency, CVE fixes, major version migrations.
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。
Shifts Layer 3 model selection to cost-optimized alternatives when economy mode is active.
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。
Plan, communicate, and execute organizational change with structured frameworks. Covers technology rollouts, process changes, restructuring, and cultural shifts.
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。
Tracks and analyzes competitor moves — pricing changes, feature launches, hiring, and positioning shifts
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。
Identifies differential m6A methylation between conditions from MeRIP-seq paired IP/input data using exomePeak2 (GC-bias-aware differential via its bam_ip/bam_input control + bam_treated_ip/bam_treated_input treatment arms), QNB beta-binomial, MeTDiff HMM, and RADAR, plus the paired-symmetric edgeR/DESeq2-on-peak-counts route when batch/lot covariates need fixed-effect handling that exomePeak2's API does not accept. Covers paired vs unpaired vs interaction designs, batch confounding and per-lot meta-analysis, the stoichiometry-vs-expression-vs-IP-efficiency confound, and effect-size filtering against under-powered N=2 designs. Use when comparing m6A across two or more conditions, choosing between exomePeak2/QNB/RADAR/MeTDiff for a design, handling batch confounding when exomePeak2's API is too rigid, distinguishing real hyper/hypo-methylation from expression shifts, applying effect-size thresholds, or planning orthogonal stoichiometry validation (GLORI/SAC-seq/m6Anet mod_ratio).
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。
Model gene-family birth-death dynamics across a species tree using CAFE5 (Mendes et al 2020 Bioinformatics 36:5516 gamma-distributed rate categories), CAFE5-error (annotation-error-aware), Count (Csurös 2010 ancestral state reconstruction), BadiRate (Librado 2012 likelihood + parsimony), DupliPHY-Family, and ALE/AleRax (for per-family DTL; see [[gene-tree-species-tree-reconciliation]]). Test lineage-specific gene-family expansions and contractions, distinguish biological dynamics from annotation artifacts, account for assembly fragmentation, identify functional enrichment in expanded / contracted families. Use when correlating gene-family changes with phenotype evolution, ranking lineages by adaptive gene-family-rate shifts, post-WGD dosage-balance analysis, or building Birth-death models from OrthoFinder presence/absence matrices.
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。
Detect positive (diversifying / episodic / pervasive) selection using codon dN/dS frameworks. Implements PAML codeml site models (M0/M1a/M2a/M7/M8/M8a), branch models, branch-site model A (Zhang 2005), and HyPhy methods (BUSTED, BUSTED-S, BUSTED-MH, BUSTED-PH, MEME, FEL, FUBAR, aBSREL, SLAC, RELAX, GARD, FUBAR-MH). Includes McDonald-Kreitman framework (asymptotic alpha, impMKT, polyDFE, DFE-alpha, GRAPES) for within-species + divergence inference, RERconverge for trait-correlated rate shifts, CSUBST for convergent substitution, and PhyloAcc for accelerated noncoding evolution. Use when testing adaptive evolution at codons, branches, or full gene; running GARD recombination pre-screen; controlling alignment-error and gBGC false positives; reconciling PAML vs HyPhy results; or performing genome-scale selection scans.
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。