2万 件 ・ 関連度順
Use this skill when the user asks how to design or improve a fleet safety scorecard — what KPIs to track, how to weight them, telematics signals vs document compliance vs roadside outcomes, monthly cadence, driver-facing vs admin-facing dashboards, gamification considerations, peer-comparison metrics, and how a scorecard ties to insurance premiums + retention. Reference SMS Methodology v3.20 for industry-standard weights.
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 DataQ — FMCSA's data review system at dataqs.fmcsa.dot.gov — for disputing inspection violations, crash records, or other entries that appear in a carrier's CSA / SMS score. Covers Request for Data Review (RDR) process, success rates, common dispute grounds, what evidence to attach, timeline expectations, and how successful disputes reduce BSI (BASIC Severity Indicator) scores. Cite 49 CFR 392.7 and the FMCSA DataQs User Guide.
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 an MRO for drug testing program oversight. Covers MRO qualifications under Part 40, what the MRO does, and how to evaluate MRO 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。
Use when a carrier (asset-based, brokerage, or 3PL) asks how to respond to a shipper RFP / RFQ — bid packaging, lane analysis, rate strategy, SOPs/SOWs, qualifications response, insurance compliance, EDI requirements, and how to win competitive bids without leaving margin on the table.
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 you receive an FMCSA Compliance Review notification. Covers what to expect, what documents to produce, and best preparation strategies.
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 trucking terminology — bobtail vs deadhead vs loaded vs empty trailer — and the insurance, weight, and fuel-tax implications of each. Covers bobtail insurance (also called non-trucking liability), how to track bobtail miles for state taxes, and when "deadhead" affects driver pay.
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 Americans with Disabilities Act (ADA) accommodation for CDL drivers — interaction between ADA + FMCSA medical certification, when DOT-disqualifying conditions trigger ADA analysis, reasonable accommodation case examples, employer obligations, and how to handle a driver with a condition that may affect CDL status. Cite Title I ADA + 49 CFR 391.41.
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 carrier asks about disaster recovery (DR) and business continuity planning (BCP) — cyber incident, natural disaster, terminal loss, key-person departure, financial liquidity event, major customer loss, insurance crisis, or fuel supply disruption. Covers risk assessment, continuity strategy, communication plans, and recovery time objectives.
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 carrier asks how to calculate cost-per-mile (CPM) at the fleet, truck, lane, or driver level — separating fixed vs variable costs, allocating overhead, accounting for empty miles, and using CPM to negotiate rates, build pricing tiers, or evaluate lane profitability.
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 document crashes that don't qualify as DOT-recordable. Covers what to track, why it matters, and insurance/CSA implications.
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 accident claims management — first-notice-of-loss procedures, working with insurance adjusters, claim severity classification, subrogation, claim closure timelines, and how to influence claim outcomes. Different from accident-investigation-playbook (which covers facts); this covers the insurance + claim side.
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。
Use for sensemaking, frame revision, anomaly handling, questioning strategy, and ambiguity diagnosis with the Data/Frame model before action is chosen. NOT for deterministic classification, settled execution planning, or situations where the frame is already stable.
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 and diagnose FIPA-style ontology-service interactions while keeping declared ontology relations, provider capability, and application authorization separate. NOT for treating an ontology mapping as provider authority or guaranteed interoperability.
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 library of agent interaction protocols for structured multi-agent communication
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 in temporal event detection, spatio-temporal clustering (ST-DBSCAN), and photo context understanding. Use for detecting photo events, clustering by time/location, shareability prediction, place recognition, event significance scoring, and life event detection. Activate on 'event detection', 'temporal clustering', 'ST-DBSCAN', 'spatio-temporal', 'shareability prediction', 'place recognition', 'life events', 'photo events', 'temporal diversity'. NOT for individual photo aesthetic quality (use photo-composition-critic), color palette analysis (use color-theory-palette-harmony-expert), face recognition implementation (use photo-content-recognition-curation-expert), or basic EXIF timestamp extraction.
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。
Build face recognition systems with InsightFace, ArcFace, enrollment pipelines, HDBSCAN clustering, and privacy-compliant architecture. Activate on: face recognition, face enrollment, face clustering, identity verification, facial search. NOT for: general object detection (computer-vision-pipeline), emotion analysis (ai-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。
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。
Manage feature manifests for code traceability. Use when creating new features, updating existing features, checking feature health, or exploring the feature-to-code relationship. Activates for manifest validation, feature creation, changelog updates, and traceability queries.
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 dashboards for migrations and runtimes. Use for authority drift, verifier status, burn-down, runtime health, or pain panels. NOT for vanity analytics, ad hoc charts, or duplicate reporting.
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。
Audit designs, color palettes, and UI components for WCAG 2.1 accessibility compliance, providing specific fixes for contrast, touch targets, focus indicators, and screen reader support. NOT for color harmony aesthetics or design system creation.
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。
Generate, fill, and assemble PDF documents at scale. Handles legal forms, contracts, invoices, certificates. Supports form filling (pdf-lib), template rendering (Puppeteer, LaTeX), digital signatures (DocuSign), and document assembly. Use for legal tech, HR automation, invoice generation. Activate on "PDF generation", "form filling", "document automation", "digital signatures". NOT for simple PDF viewing, basic file conversion, or OCR text extraction.
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。