「simula」の検索結果

Use XcodeBuildMCP to build, run, launch, and debug the current iOS project on a booted simulator. Trigger when asked to run an iOS app, interact with the simulator UI, inspect on-screen state, capture logs/console output, or diagnose runtime behavior using XcodeBuildMCP tools.

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Fix Monte Carlo project completion simulations that give identical dates for all sub-groups (milestones, priorities, epics). Use when: (1) All sub-group predictions converge to the same date despite different remaining counts, (2) Proportional throughput scaling produces flat/identical results, (3) Applying overall scope rate to individual sub-groups causes simulations to hit max_weeks cap and never converge, (4) Building project forecasting tools that predict completion for sub-groups of a larger backlog. Covers hypergeometric draw model for milestones and cumulative priority model for sequential priorities.

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Orchestrate production-grade Blender work by probing the installed Blender version, retrieving relevant official Blender documentation, assigning visual design intent, classifying shape grammar and geometry/deformation/procedural/physics/shading needs, comparing direct Blender components with node systems, creating staged artifacts, and routing to specialist skills. Use for every non-trivial Blender creation, reconstruction, simulation, animation, environment, or scene-modification request, especially when the user does not know whether to use topology, Boolean, Array, curves, snapping, Displace, simulation, Geometry Nodes, or shading.

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Audit Blender scenes and assets for topology, transforms, normals, surface continuity, classified connections, intersections, modifier/node intent, procedural performance, simulation stability, protected-scene changes, and fixed-view visual evidence. Use after every major modeling or simulation stage and before render, bake, export, or claims of completion.

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Test native, React Native, hybrid, and Flutter mobile apps with Appium 3.x, Detox, Maestro, and Patrol. Covers device farm setup (BrowserStack, Sauce Labs), gesture simulation, deep link and cold-start testing, push notifications, biometric (Face ID) auth, offline/poor-network simulation, and iOS/Android permission dialog handling. Use when: "mobile test," "Appium," "Detox," "Maestro," "Patrol," "Flutter test," "iOS test," "Android test," "device farm," "deep link," "biometric," "Face ID," "permission dialog," "React Native test." Not for: device/browser matrix strategy in the abstract — use cross-browser-testing; app startup/memory/battery profiling depth — use performance-testing; mobile screenshot diffing — use visual-testing. Related: ci-cd-integration, cross-browser-testing, performance-testing, test-data-management, test-reliability.

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Design and implement Monte Carlo methods for uncertainty quantification, risk analysis, and probabilistic simulations across scientific and financial domains. Use when "monte carlo, random sampling, uncertainty quantification, risk analysis, stochastic simulation, MCMC, variance reduction, probabilistic, " mentioned.

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Use this skill to operate the Aomi CLI for natural-language crypto and DeFi workflows, including balance checks, route simulation, transaction review, and explicit user-approved signing flows across EVM chains.

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Use this skill to operate the Aomi CLI for natural-language crypto and DeFi workflows, including balance checks, route simulation, transaction review, and explicit user-approved signing flows across EVM chains.

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ANDREJ KARPATHY — SKILL COMPLETA v2.0 workflow skill. Use this skill when the user needs Agente que simula Andrej Karpathy — ex-Director of AI da Tesla, co-fundador da OpenAI, fundador da Eureka Labs, e o maior educador de deep learning do mundo and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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Create Chinese HBG “模拟人生 / 人生副本” narrative videos with a consistent comic IP, a rapid multi-life opening, continuous natural-speed narration, synchronized short captions, dense static manga storyboards, audible fixed-level BGM, alternating zoom/pan motion in HyperFrames, and a consent-gated localhost-only account-backed Images API through CLIProxyAPI as the preferred image channel. Use for 模拟人生、人生副本、统一主角漫画、快闪职业开头、旁白配图、静态漫画分镜、zoom 推拉、左右平移、Edge TTS、字幕压制、本地反代自己的 Codex 账号、CLIProxyAPI，或把长篇中文人生故事组装成视频。

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Edit drafts into natural prose, inspect AI-sounding patterns, or review how a specified audience might respond passage by passage. Zero Slop runs inside the user's existing AI assistant with local tools that protect source details. Use for humanizing or de-slopping writing, polishing outward-facing prose, social drafts, final editorial checks, or an explicit simulated reader review. Preserve facts, voice and format; reader simulations are hypotheses, not human feedback.

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Use this skill when calculating control system performance metrics such as rise time, overshoot percentage, steady-state error, or settling time for evaluating simulation results.

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。

Structure a direct experience into a full learning cycle with concrete experience, reflection, and conceptual transfer. Use when planning field trips, simulations, or practical tasks.

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。

Simulate pending Sealevel (SVM) warp-route governance txs — signed directly or via a Squads multisig — by forking Solana mainnet locally with surfpool, replaying the exact transactions, then running warp check against the desired registry config. Use to verify that a not-yet-submitted SVM governance change produces the intended on-chain config before it is signed/executed.

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Design a game day — simulated failure scenario, runbook, and post-event review. Use when asked to "run a game day", "plan a failure drill", or "simulate an outage".

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Real-world problem formulation, mathematical abstraction, and applied mathematics for translating between practical problems and mathematical frameworks. Covers the modeling cycle (problem identification, assumptions, formulation, analysis, validation, interpretation), Polya's framework adapted for modeling, common model types (linear, exponential, logistic, periodic, power-law), dimensional analysis (Buckingham Pi theorem), optimization (linear programming, gradient descent, constraint satisfaction), probability models (Markov chains, queuing theory, Monte Carlo simulation), statistical modeling (regression, hypothesis testing, model selection), model criticism (overfitting, underfitting, sensitivity analysis), and real-world case studies. Use when formulating mathematical models, performing dimensional analysis, optimizing systems, running simulations, or evaluating model validity.

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Generates simulation inputs across fidelity levels — OpenFOAM CFD cases, ngspice netlists, interactive React artifacts, and FreeCAD FEM setups — from verified engineering calculations.

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。

Quantum computing framework for building, simulating, optimizing, and executing quantum circuits. Use this skill when working with quantum algorithms, quantum circuit design, quantum simulation (noiseless or noisy), running on quantum hardware (Google, IonQ, AQT, Pasqal), circuit optimization and compilation, noise modeling and characterization, or quantum experiments and benchmarking (VQE, QAOA, QPE, randomized benchmarking).

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。

Bisimulation game for resilient skill dispersal across AI agents with GF(3) conservation and observational bridge types.

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。

Test an uncertain Anabasis v2 path at the smallest real layer that can decide it, before a paid round is asked to: one fact from a log or a dry run, a walk of one value across the layers a change touches, a replay of every recorded log through this tree's readers, a whole round rehearsed on a seeded copy of a campaign with a script in each model seat (`bun run runs seed`, `bun run runs rehearse`), or one live seat from a seed. Use when the operator asks whether a change will work in the real system, to simulate or rehearse a round, to stand again in a position a past run stood in, what a campaign of a given size can read, or what a kill or a stop leaves behind. Not for reading a finished run (whole-run-investigation) or starting a paid one (launch-run).

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Audit and safely clean Xcode-related developer storage on macOS. Use whenever a developer mentions low disk space, Xcode storage, DerivedData, simulator devices or runtimes, stale beta platforms in Xcode Settings, DeviceSupport, archives, dSYMs, CocoaPods caches, simulator dyld caches, project .build folders, downloaded Xcode DMGs/XIPs, duplicate Xcode installers, or old Xcode applications. Also use this skill proactively when you hit low storage during other work, such as a build, download, or install failing with an out-of-disk-space error. Always measure first, report recoverable GiB with evidence, and obtain explicit itemized approval before any mutation.

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Runs Monte Carlo simulations for portfolio analysis with return distribution, tail risk, and path-dependent scenario evaluation. Use when running portfolio simulations, estimating tail risk, or analyzing return distributions.

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Generate 20,000+ particle swarm simulators in two modes: sandbox (complete Three.js host runtime with gesture controls, security validation, code injection pipeline) and sim (behavior function bodies that position/color particles via a sandboxed API). The AI writes ONLY a function body — the host handles rendering, input, and security. Triggers on particle swarm, swarm simulator, particle behavior, swarm sandbox, gesture particles, 20K particles, particle function body, swarm sim, particle playground.

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Design and build runnable iOS UI mockups in SwiftUI, including UI direction, multiple visual or interaction variants, realistic sample data, state switching, Xcode Previews, and Simulator validation. Use when the user wants to explore what an iOS screen should look like, compare SwiftUI UI ideas, create a clickable native prototype, validate an app flow before production implementation, or asks for a SwiftUI mock, iOS mockup, native prototype, 画面モック, UI案, SwiftUIで動くモック, or 実際に触れるiOSモック.