「shifts」の検索結果

Develop or document a complete brand voice and tone system covering voice attributes, tone shifts by context, vocabulary preferences, grammar rules, and copy examples. Use this skill whenever the user wants to define how a brand sounds, write a voice and tone document, audit existing copy for voice consistency, train a team or AI assistant on brand voice, or refine the personality of brand writing. Triggers on brand voice, voice and tone, tone of voice, writing voice, brand personality, copy voice, voice document, voice guidelines, how should we write, voice training, voice audit. Also triggers when the user has copy that 'feels off' and the underlying issue is voice, even if not stated explicitly. On a voice consistency check, this skill owns defining and documenting the voice system; use `editorial-qa` when a specific draft needs checking against an existing system before it publishes.

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Rate market weather by script: economy, competition, platform and regulatory shifts, scored. "is now a good time to launch"

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Schedule labor crews based on CWICR norms and project timeline. Calculate crew sizes, shifts, and labor loading curves.

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Monitor competitor pricing pages and send alerts when prices change. Track discount patterns, promotional cycles, and pricing strategy shifts.

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Refresh the user's competitive and market context. Re-scan named rivals and the category for what changed since the brief was written (rebrands, repositioning, new entrants, pricing shifts, renamed categories) and update docs/gtm-cofounder/founder-brief.md and the roadmap with anything that moves positioning. Use on a cadence, or whenever a competitor rebrands, a new tool appears, or the user senses the market has shifted under them.

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Monitor competitor pricing pages and send alerts when prices change. Track discount patterns, promotional cycles, and pricing strategy 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。

Think and work like an expert Hydrologist. Use when a task calls for Hydrologist judgment. Reasons from hydrologic-cycle closure (P = ET + Q + ΔS + I), runoff-generation mechanisms, and channel routing through HEC-HMS, HEC-RAS, the National Water Model, and split-sample KGE/NSE/PBIAS calibration, while treating post-flood rating-curve shifts, radar QPE bias, snow/rain misclassification, and non-stationarity in extremes as first-class failure modes.

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Think and work like an expert Epigeneticist. Use when a task calls for Epigeneticist judgment. Reasons from chromatin state, DNA methylation, histone marks, accessibility, and 3D genome topology through ChIP/CUT&RUN, ATAC-seq, WGBS/EM-seq, Hi-C, and dCas9-DNMT3A/KRAB perturbation while treating cell-composition shifts, batch confounding, antibody nonspecificity, Tn5 bias, and incomplete bisulfite conversion as first-class failure modes.

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Think and work like an expert Ecosystem Ecologist. Use when a task calls for Ecosystem Ecologist judgment. Reasons from NEE/NEP mass balance, ecological stoichiometry, and u*-filtered eddy covariance; processes with ONEFlux/REddyProc, NEON DP4.00200, and CENTURY/DayCent while treating gap-fill partitioning artifacts, chamber pressure pulses, harvest omission, and footprint shifts as first-class failure modes.

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Think and work like an expert Cognitive Scientist. Use when a task calls for Cognitive Scientist judgment. Reasons from Marr's levels of analysis, latent processes behind RT and accuracy, and strong inference through PsychoPy paradigms, signal-detection d-prime/criterion, sequential-sampling and ACT-R models, and crossed mixed-effects designs while treating speed-accuracy tradeoffs, criterion shifts, item confounds, and underpowered WEIRD samples as first-class failure modes.

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Think and work like an expert Atomic, Molecular & Optical Physicist. Use when a task calls for Atomic, Molecular & Optical Physicist judgment. Reasons from Rabi/OBE dynamics, laser-cooling hierarchy, optical lattices and Hubbard U/J, and magic-wavelength clock budgets through NIST ASD, ARC, QuTiP/PyLCP, and in-situ lattice-depth calibration while treating power-based depth guesses, polarization impurities, BBR shifts, and imaging-heating conflation as first-class failure modes.

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Rapidly assess crisis situations by monitoring Twitter, Reddit, news, and Chinese social platforms simultaneously. Detects escalation velocity, identifies key narratives, tracks official responses, and measures public sentiment shifts during critical events.

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Identify differentially bound regions across CLIP-seq conditions (knockdown vs control, treatment vs vehicle, disease vs healthy) using DEWSeq (sliding-window DESeq2), Flipper (Skipper-downstream), ASpeak, edgeR, or limma-voom. Use when computing condition-level changes in RBP binding intensity, choosing peak-level vs window-level vs crosslink-level testing, designing replicate experiments, or distinguishing biological binding shifts from technical confounders.

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Identifies differentially bound ChIP-seq regions between conditions using DiffBind, csaw (sliding windows), DESeq2/edgeR/PyDESeq2 on count matrices, NormR (control-aware), or MAnorm2. Distinguishes three distinct normalization problems (composition bias, trended bias, global shifts) and matches each to its appropriate fix including spike-in scaling. Use when comparing ChIP-seq binding between experimental conditions, choosing normalization for global vs local changes, integrating spike-in data, or reconciling DiffBind/DESeq2 disagreement.

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The orchestration layer for AI-native creative production. This skill coordinates multiple AI tools—video, image, audio, digital humans, effects—into cohesive campaigns, productions, and creative systems. As AI tools proliferate, the challenge shifts from "can we create this?" to "how do we orchestrate these capabilities into something coherent?" The AI Creative Director thinks in systems, not tools. In pipelines, not one-offs. In brand consistency across AI-generated assets. This is where creative vision meets technical orchestration. The AI Creative Director doesn't just use AI tools—they compose them into creative instruments that produce at scales and speeds previously impossible. Use when "AI creative director, orchestrate AI, AI campaign, multi-tool, AI workflow, AI pipeline, coordinate AI, AI production, AI creative system, full AI production, AI at scale, orchestration, creative-direction, ai-production, workflow, pipeline, multi-tool, scale, quality-control" mentioned.

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Applies the practical, systems-level, and commercially-driven reasoning of Thomas Edison (founder of General Electric, inventor and industrialist). Use this skill whenever the user is navigating product commercialization, systems engineering, R&D strategy, scaling new technologies, evaluating patent decisions, or struggling with repeated iterative failures. Edison's approach shifts the focus from isolated 'genius' inventions to building entire profitable ecosystems, treating failure as a necessary process of elimination, and prioritizing relentless execution over pure theory.

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Applies the philosophical frameworks of Martha Nussbaum (American philosopher, capabilities approach, University of Chicago) to evaluate justice, human welfare, and ethical dilemmas. Use this skill whenever the user is discussing measuring societal well-being, educational curricula, animal rights, the role of emotions (like anger or disgust) in law and public life, or navigating human vulnerability and tragedy. Reach for this skill whenever evaluating policy impacts, responding to injustice, or questioning purely economic metrics like GDP. It shifts the focus to what people are actually able to do and be.

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Applies the nutritional epidemiology and public health frameworks of Frank B. Hu (nutrition epidemiologist, Harvard University). Use this skill whenever reasoning about diet quality, public health policy, planetary health, cardiometabolic disease prevention, or evaluating nutritional studies. Trigger this when the user asks about plant-based diets, macronutrient trade-offs ("compared to what?"), the impact of the food environment, or lifestyle factors for longevity. It shifts the AI's focus from single-nutrient reductionism to overall dietary patterns, emphasizing that "zip code is more important than genetic code" and that human health is inextricably linked to planetary health.

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Use this skill whenever you need to reason about public health, epidemiology, preventive medicine, healthy aging, longevity, lifestyle vs. genetics, or dietary patterns. Kay-Tee Khaw, an epidemiologist at the University of Cambridge, focuses on population health and how modest lifestyle changes impact chronic disease. Trigger this skill when evaluating health interventions, discussing longevity, analyzing real-world health data, or giving advice on diet and lifestyle. Apply her frameworks to shift focus from extreme interventions and isolated nutrients toward whole-food patterns, population-level risk shifts, and the compression of morbidity.

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Use this skill for ANY work involving React, Next.js, TypeScript, or Tailwind in the browser layer. This includes building components and pages, but equally covers debugging and fixing frontend issues: CSS/Tailwind classes not applying, form validation behavior, hydration mismatches between server and client renders, styling bugs, layout shifts, and rendering problems. Also use for refactoring components (e.g., splitting Server vs Client Components), data fetching patterns, state management, bundle optimization, and frontend tooling. If the problem involves what users see or interact with in a web browser — whether building, fixing, or refactoring — use this skill. Not for backend APIs, databases, infrastructure, or DevOps.

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Investigate unexpected behavior and mysterious bugs. Use when the cause of a problem is unknown and the user needs to understand WHY something is happening — symptoms like: sudden unexplained changes in metrics or behavior, works locally but not in staging/production, inconsistent or intermittent failures, correct code producing wrong results, operations succeeding but having no effect, environment-specific failures, duplicate executions, stale data, or any "why did this change?" or "why is this happening?" situation. Covers infrastructure anomalies (cache hit rates dropping, latency spikes, queue behavior shifts) as well as code bugs. The key signal is confusion about root cause, not a request to implement a known fix. Do NOT use for feature requests, known fixes, planning, or documentation tasks.

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Formulates LP, MILP, CP-SAT models; diagnoses infeasibility and gaps. Use when a MILP is infeasible, shifts need scheduling under capacity, or choosing a solver.

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Diagnose HitKeep traffic drops, spikes, source shifts, and suspicious changes. Use when traffic, sessions, visitors, pageviews, events, or conversions changed; when a deploy may have affected measurement or behavior; or when search, referral, direct, campaign, and bot explanations need to be separated.

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Refracting thinking by challenging assumptions, combining cross-domain knowledge, and shifting perspectives to reframe problems. Use for stuck situations or paradigm shifts. Does not write code.

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