2.5万 件 ・ 関連度順
概要と使いどころ
Use when a carrier asks about electric trucks — Tesla Semi, Freightliner eCascadia, Volvo VNR Electric, Peterbilt 579EV, range, charging, total cost of ownership, regulatory pushes (CARB ACT, ACF), incentives, infrastructure, depot vs en-route charging, and which routes/applications are EV-ready today.
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 this skill when selecting a Consortium/Third-Party Administrator (C/TPA) for drug + alcohol testing program management. Covers what services they provide, what to look for, and red flags.
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 this skill when the user asks about Driver Qualification Files (DQF) — what must be in a DQ file under 49 CFR 391, retention periods, what's required pre-hire vs ongoing, document expiration tracking, audit-readiness for driver files, common DQF deficiencies that auditors find, or how to handle missing documents on existing drivers. Always cite the specific subsection of 49 CFR 391.
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 a fleet manager or owner asks when to replace tractors and trailers, optimal trade cycle age, total cost of ownership analysis, residual value timing, dealer-vs-auction sale strategy, and how trade cycle affects driver retention and operating cost.
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 this skill to understand why CSA BASIC alert thresholds differ across carrier types. Covers general freight (65th percentile), passenger/hazmat (60th), and the regulatory rationale.
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 this skill when the user asks how to manage a trucking carrier's public reputation — handling a major accident in the news, social media + Glassdoor + Indeed reviews, customer disputes that escalate, employee disputes, regulator perception, and how to communicate during a crisis. Reference industry PR + crisis communication practices.
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 this skill to obtain a Motor Carrier (MC) number from FMCSA. Covers application, fees, and timeline.
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 this skill when the user asks about US-Canada cross-border CMV operations — CVOR (Commercial Vehicle Operator's Registration), NSC (National Safety Code), Ontario / Quebec / BC specific rules, US carrier obtaining Canadian operating authority, FAST card for drivers, customs (CBSA), Health Canada hazmat, and how Transport Canada equivalents differ from US FMCSA. Reference USMCA + Transport Canada NSC 14.
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 this skill when the user asks about FMCSA Compliance Safety Accountability (CSA) program scoring — the seven BASIC categories, BASIC Severity Indicator (BSI), peer percentiles, intervention thresholds, how violations age out, SMS Methodology, ISS (Inspection Selection System), what "alert" status means, Safety Measurement System mechanics, or DataQ disputes. Cite SMS Methodology v3.20.
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 this skill when the user asks how to market a trucking company — sales channels, prospecting, website + brand, industry directories (D&B Hoovers, ZoomInfo), referral programs, content marketing, and ROI of different acquisition channels. Reference industry sales practices.
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 this skill when the user asks how to investigate a CMV accident — what to do at the scene, the first 24 hours, evidence preservation, who to call, preventability determination, ELD data preservation, dash cam review, witness interviews, working with insurance + attorney, and how to build a learning culture from incidents. Reference 49 CFR 392.7 + insurance industry best practices.
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 this skill if you're a new motor carrier expecting your first FMCSA safety audit. Covers what to expect, focus areas, and common findings.
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。
FIPA standard for agent platform management including lifecycle, directory, and communication services
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。
Prepare high-quality datasets for LLM fine-tuning with filtering, deduplication, augmentation, and RLHF data formatting. Activate on: fine-tuning data, training data curation, RLHF dataset, data quality filtering, SFT dataset. NOT for: model training infrastructure (ai-engineer), prompt engineering without fine-tuning (prompt-engineer).
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。
An innate exploratory drive that guarantees no graph node remains permanently invisible to an agent population. After a warm-up period (step > 3), each agent fires a coverage scan with probability |unseen_nodes| / |all_nodes|. When triggered, the agent teleports directly to the globally unseen node with the highest belief uncertainty, works it, and returns control to the normal action-selection loop. Probability is self-annealing: it starts near 1.0 when almost everything is unseen and decays toward 0.0 as coverage saturates, requiring no manual schedule. The mechanism is "innate" (hard-coded into the agent step loop) as distinct from the "adaptive" EFE path, which requires local neighbors and learned precision weights. Together they form a two-layer exploration architecture: adaptive for locally-guided foraging, innate for topological completeness.
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。
Principled action selection for autonomous agents using Expected Free Energy (EFE) under the Active Inference framework. Each candidate action is scored as G(n) = w_prag * (-E[p_n] * damping) + w_epist * (-Var[p_n] * novelty(n)), where agent beliefs are maintained as per-node Beta distributions and updated via Bayesian observation. Selection is a softmax over -gamma * G, making exploration an automatic consequence of uncertainty rather than a hardcoded epsilon. Precision weights w_prag and w_epist self-adapt via surprise history, shifting the agent between exploitation and exploration regimes without any manually tuned schedule.
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。
Design error handling strategies for TypeScript and Python applications — exception hierarchies, Result/Either types, retry patterns, error boundaries, and structured error logging. Use when designing error handling architecture, choosing between exceptions and Result types, implementing retry logic, or building error recovery flows. Activate on "error handling", "exception hierarchy", "Result type", "retry pattern", "circuit breaker", "error boundary", "Pokemon exception". NOT for debugging specific runtime errors, logging infrastructure setup, or monitoring/alerting configuration.
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。
Adversarial reviewer for The Federated Harbor whitepaper — the third paper in the Curiositech sequence after Anchor and Bonded Commons. Probes federation-specific threats: trust transitivity, cross-harbor token forgery, federated revocation under partition, cross-harbor Sybil, cross-domain settlement, equivocation, bond-pool draining, cold-start joining, federation-operator Sybil. Use during a versioned red-vs-white round; pairs with federated-harbor-whitehat. NOT for incident response, NOT for the Anchor or Bonded papers (use redteam-review).
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 and review Cloudflare Durable Objects. Use when building stateful coordination (chat rooms, multiplayer games, booking systems), implementing RPC methods, SQLite storage, alarms, WebSockets, or reviewing DO code for best practices. Covers Workers integration, wrangler config, and testing with Vitest. Biases towards retrieval from Cloudflare docs 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。
Expert landscape designer transforming yards through photo mapping, 3D visualization, seasonal planning, and deep plant knowledge. Specializes in fast-growing privacy screens (knows arborvitae pitfalls), architecture-appropriate design, outdoor living spaces, and realistic maintenance expectations. Activate on "landscape design", "yard design", "garden planning", "plant selection", "privacy screen", "outdoor living", "backyard makeover", "arborvitae", "hedge", "fast growing tree", "landscaping ideas". NOT for interior design (use interior-design-expert), hardscape construction (consult contractors), or lawn care chemicals (consult local experts).
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。
Advanced CV for infrastructure inspection including forest fire detection, wildfire precondition assessment, roof inspection, hail damage analysis, thermal imaging, and 3D Gaussian Splatting reconstruction. Expert in multi-modal detection, insurance risk modeling, and reinsurance data pipelines. Activate on "fire detection", "wildfire risk", "roof inspection", "hail damage", "thermal analysis", "Gaussian Splatting", "3DGS", "insurance inspection", "defensible space", "property assessment", "catastrophe modeling", "NDVI", "fuel load". NOT for general drone flight control, SLAM, path planning, or sensor fusion (use drone-cv-expert), GPU shader development (use metal-shader-expert), or generic object detection without inspection context (use clip-aware-embeddings).
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。
Multi-stage Docker build optimizer for minimal, secure production images. Activate on: Dockerfile optimization, multi-stage build, distroless image, container size reduction, Docker security scanning, BuildKit features. NOT for: container orchestration (use kubernetes-manifest-generator), CI/CD pipelines (use github-actions-pipeline-builder), runtime container config (use environment-config-manager).
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。
Generates production-ready design tokens from natural language descriptions. Outputs Tailwind configs, CSS custom properties, and DTCG W3C tokens from 24 trends + 31 AI-ready styles with 2800+ component examples.
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。
Creates comprehensive documentation for design systems - token tables, usage guidelines, component examples, and accessibility notes. Use after generating tokens to create developer-friendly docs.
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。