「transit」の検索結果

Applies the reasoning style of Ilya Sutskever (deep learning pioneer, co-founder of OpenAI and Safe Superintelligence Inc.) to problems involving AI architecture, scaling laws, alignment, and research strategy. Reach for this skill whenever discussing machine learning paradigms, the limits of compute and data, AGI timelines, superintelligence safety, or deciding between hardcoding vs. learning. Trigger this skill for questions about next-word prediction, reinforcement learning efficiency, generalization gaps, and transitioning from brute-force scaling to fundamental research, even if the user doesn't explicitly name him.

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Applies the reasoning, principles, and mental models of Sebastian Thrun (robotics and self-driving cars pioneer, founder of Google X, Waymo, Udacity, Stanford University). Reach for this skill whenever Claude is asked to advise on hardware/software systems engineering, autonomous vehicles, moonshot ideation, probabilistic robotics (SLAM), or leading high-stakes engineering teams. Trigger this skill for discussions on democratizing education, regulating AI, transitioning from academic research to product development, or managing technical teams with empathy. Use it to shift focus from incremental component debates to end-to-end execution and audacious goals.

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Applies the reasoning style of Daphne Koller (machine learning pioneer, co-founder of Coursera, founder and CEO of Insitro). Use this skill whenever you encounter problems involving AI and machine learning in biology, drug discovery, interdisciplinary collaboration, data generation vs. data mining, or transitioning from academia to industry. Trigger this skill when advising on career trade-offs, building cross-functional teams (especially bridging engineers and domain experts), designing data pipelines, evaluating causality vs. correlation, or applying AI to physical systems ('where bits meet atoms'). Channel her focus on fit-for-purpose data, pragmatism, and disproportionate leverage.

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Applies the mental models and frameworks of Andrej Karpathy (deep learning, former Director of AI at Tesla, founding member of OpenAI, Eureka Labs). Use this skill whenever you are helping the user build neural networks from scratch, debug deep learning pipelines, evaluate AI agent workflows, design LLM apps, or navigate the transition to Software 3.0 (vibe coding). It is highly relevant for pedagogy (untangling complex knowledge), assessing AI capabilities vs. limitations (jagged intelligence, tokenization limits), and architectural decisions (end-to-end optimization vs. complex pipelines). Reach for this whenever discussing LLM training, autonomous systems, or AI-assisted coding.

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Debug and fix infinite widget rebuild loops in Flutter apps using Riverpod state management. Use when: (1) Logs show "RAPID REBUILD" warnings or 50+ rebuilds in seconds, (2) UI becomes unresponsive or shows same content repeatedly, (3) Bug only affects slower devices or poor network conditions, (4) Provider watching creates circular dependencies with router/URL state. Covers ref.watch() overuse, watch+listener redundancy, and transitive dependency chains.

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Fix Fastly Compute Rust build failures caused by edition2024 dependencies. Use when: (1) cargo build fails with "feature `edition2024` is required", (2) wit-bindgen or wasip2 crates fail to download/parse, (3) Fastly SDK pulls in incompatible transitive dependencies, (4) Build worked before but fails after dependency update. Solves by pinning wit-bindgen, wasip2, and related crates to pre-edition2024 versions.

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Create Chinese monospaced compass-style PDCA or CAPD problem-solving cards using East-West-South-North-Center layout, full-width and half-width spaces, diagonal Unicode arrows, and strict Chinese character limits. Use when Codex needs to turn a problem, incident, decision tradeoff, root-cause analysis, improvement cycle, or CAPD/PDCA workflow into a square text diagram, Hermes/Discord-ready card, or Chinese 方位九宮圖 with center ◎, north Plan, east Do, south Check, west Action, and four diagonal transition arrows.

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Scan repositories for newly disclosed CVEs in dependencies after a specific cutoff date. Takes a repository path, cutoff date (YYYY-MM-DD), and optional parameters for transitive dependencies. Parses dependency manifests (package.json, pom.xml, requirements.txt, go.mod, Cargo.toml) and lockfiles to extract exact versions. Queries vulnerability databases (OSV.dev, NVD, GitHub Advisory) to identify CVEs disclosed strictly after the cutoff date. Distinguishes between newly disclosed CVEs and previously known CVEs. Use when: (1) Performing security audits to find new vulnerabilities since last review, (2) Checking if new CVEs affect a historical codebase version, (3) Generating compliance reports showing vulnerability status at specific dates, (4) Tracking security posture changes over time. Supports npm, Maven, pip, Go modules, Cargo, and other major ecosystems.

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Automatically generates executable test cases from model checking counterexample traces. Translates abstract counterexample states and transitions into concrete test inputs, execution steps, and assertions that reproduce property violations. Use when working with model checker outputs (SPIN, CBMC, NuSMV, TLA+, Java PathFinder, etc.) and needing to create regression tests, validate bug fixes, or reproduce verification failures in executable test suites.

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Offline-first mobile apps with local storage, sync queues, conflict resolution. Use for offline functionality, data sync, connectivity handling, or encountering sync conflicts, queue management, storage limits, network transition errors.

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Motion (Framer Motion) React animation library. Use for drag-and-drop, scroll animations, gestures, SVG morphing, or encountering bundle size, complex transitions, spring physics errors.

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AutoAnimate (@formkit/auto-animate) zero-config animations for React. Use for list transitions, accordions, toasts, or encountering SSR errors, animation libraries complexity.

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Use when the user is transitioning from a completed retro into a weekly plan, choosing weekly outcomes, scheduling a full ISO week, or asking for "план на неделю", "weekly planning", priorities, capacity, or outcomes.

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Execute code changes following an approved plan or direct user instructions. Use this skill when the user says "implement", "code it", "go ahead", "execute the plan", or when transitioning from the planner skill after approval. Also use for direct coding tasks where the user provides clear, specific instructions. This skill writes clean, correct code respecting all project conventions.

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Design and verify auditable human oversight, approval gates, escalation paths, and safe state transitions for AI agent workflows. Use when deciding which agent actions require review, adding approve/reject or dual-control flows, preventing unauthorized autonomous effects, creating decision records, reducing rubber-stamping, or recovering safely from rejected, expired, or failed actions.

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Think and work like an expert Exoplanet Scientist. Use when a task calls for Exoplanet Scientist judgment. Reasons from Keplerian motion, transit and RV geometry, and degenerate retrieval spaces through TLS/BLS searches, centroid and odd-even vetting, RadVel and GP activity models, and petitRADTRANS retrievals while treating eclipsing-binary blends, stellar-rotation-mimicking RV signals, and look-elsewhere completeness cliffs as first-class failure modes.

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Think and work like an expert Energy Storage / Battery Scientist. Use when a task calls for Energy Storage / Battery Scientist judgment. Reasons from interfacial thermodynamics, ion transport, SEI/CEI dynamics, and cell engineering constraints (N/P and E/S ratio, mass loading) through galvanostatic cycling, dQ/dV, GITT and EIS/DRT, operando XRD, and PyBaMM/Newman models, while treating Li plating, lithium-inventory loss, transition-metal crossover, and coin-cell artifacts as first-class failure modes.

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Think and work like an expert Dairy Scientist. Use when a task calls for Dairy Scientist judgment. Reasons from the lactation curve, dry matter intake, and rumen health through NASEM Dairy 2021/CNCPS ration formulation, Penn State particle separation, DHIA records, and pen-level mixed models while treating subacute ruminal acidosis, milk fat depression, transition-cow hypocalcemia, and unadjusted DIM/parity confounding as first-class failure modes.

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Think and work like an expert Climate Risk Analyst. Use when a task calls for Climate Risk Analyst judgment. Reasons from TCFD/IFRS S2 four-pillar disclosure, NGFS Phase V orderly/disorderly/hot-house scenarios, hazard–exposure–vulnerability and RMS/AIR/CLIMADA cat economics, transition carbon-price and stranded-asset pathways, and PCAF financed emissions while treating exposure geocoding quality, Kotz damage-function retraction, and scenario-not-forecast misuse as first-class failure modes.

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Think and work like an expert Astrostatistician. Use when a task calls for Astrostatistician judgment. Reasons from selection functions, censored flux limits, and look-elsewhere trial factors through Cobaya/emcee/dynesty cosmology, GP-coupled exoplanet inference, Landy–Szalay clustering, photo-z σNMAD calibration, and SBI (sbi/LtU-ILI) while treating Malmquist bias, prior-driven tensions, and detrend-then-fit transit bias as first-class failure modes.

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Think and work like an expert Bayesian Statistician. Use when a task calls for Bayesian Statistician judgment. Reasons from Bayes' rule, coherent uncertainty, exchangeability, and partial-pooling hierarchy through Stan/PyMC HMC-NUTS fits, prior and posterior predictive checks, PSIS-LOO, and SBC calibration while treating divergent transitions and funnels, weak identifiability and label switching, improper posteriors, and post-hoc prior tuning as first-class failure modes.

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Production guidance for converting sourced data and approved claims into truthful, accessible, deterministic animated visualizations with D3. Use for data-driven charts, maps, networks, hierarchies, transitions, annotations, responsive video variants, frame-by-frame browser rendering, and visualization QA; not for generic dashboards, unsourced decorative charts, or ordinary motion graphics without a data contract.

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Provider-independent sound design and Foley direction for generated media. Use when an agent must plan, prompt, source, generate, edit, mix, hand off, repair, or QA sound effects, Foley, ambience, impacts, transitions, UI/product audio, emotional sound design, or accessibility-safe captions for videos, ads, trailers, animation, avatar clips, explainers, games/trailers, product films, and social edits.

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Provider-independent editing and montage direction for AI agents producing generated videos, ads, trailers, social clips, explainers, product videos, documentary-style pieces, and music- or beat-driven cuts. Use when planning, revising, QAing, or handing off an edit: story structure, shot selection, continuity, montage theory, rhythm and pacing, J/L cuts, match cuts, cutaways, transitions, beat sync, platform timing, source/generated asset management, revision workflow, and composition handoff.

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。