3,141 件 ・ 関連度順
概要と使いどころ
Use when a carrier needs to build an internal dispatcher training program, onboard new dispatchers, or certify dispatcher competency. Covers job description, required skills, training modules, certification frameworks (CDS, CTP), shadowing, evaluation, and career path.
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 evaluate whether credit reports are appropriate for driver applicant screening. Covers EEOC guidance, FCRA, and common carrier policies.
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 buying or selling a trucking company — valuation drivers (revenue, fleet age, CSA scores, customer concentration), asset purchase vs stock purchase, FMCSA authority transfer, due diligence checklist, common deal structures (cash, earnout, seller-financed), and what changes operationally after acquisition. Reference 49 CFR 365.401 (authority transfer).
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 use the Pre-Employment Screening Program (PSP) for evaluating driver applicants. Covers what PSP shows, cost, and how to interpret reports.
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。
Launch a specific Coval evaluation with explicit cases and execution bounds. Use when resources are already selected; for result analysis use quick-eval.
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。
Retrieve and analyze simulation results from a Coval run. Use when user wants to review evaluation outcomes or debug agent behavior.
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。
End-to-end Coval adversarial / red-team testing workflow. Builds one adversarial test set (12 core attack vectors plus legitimate controls, each with an expected-behavior checklist), creates a persistent "Adversarial User" persona and a Composite Evaluation metric that scores each scenario against its own expected behaviors, launches a multi-iteration run against the agent (voice or chat), polls for completion, builds a per-scenario pass/fail scorecard, and creates a saved report grouped by Test Case. Use when a user wants to follow the Adversarial & Red-Team Testing cookbook (https://docs.coval.dev/guides/adversarial-red-team-testing) without doing each step by hand. Triggers: "adversarial test set", "red team my agent", "jailbreak / prompt-injection testing", "test my agent against bad actors".
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。
Delegate a read-only Coval evaluation, simulation, monitoring, product-how-to, or troubleshooting subtask to Sofia through the official Coval MCP consult_sofia tool. Use when the user needs Coval-specific FDE judgment, analysis of organization data, metric or test-set recommendations, or a diagnosis grounded in Coval runs and conversations.
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。
Choose the next useful step for evaluating a voice or chat agent with Coval. Use for getting started or deciding what to do next; use a specific skill directly when the task is already clear.
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。
Set up and connect a new Coval agent for evaluation. Guides through agent type selection, endpoint configuration, system prompt, and default resource attachment. Use when user says "set up an agent", "connect my agent", "create an agent", "add an agent", or "configure agent endpoint".
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 an existing Coval evaluation setup for coverage, misleading scores, missing evidence, judge validation and execution risk. Read-only; use when inheriting an eval or deciding whether its results support a release decision.
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 abstract strategy games with perfect information, no randomness, and strategic depth. Use when designing a board game, exploring abstract strategy games, brainstorming game mechanics, or evaluating game balance. Keywords: board game, game design, strategy, mechanics, balance.
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。
Complete workflow for static structural analysis. Use when analyzing stress, displacement, or reaction forces under constant loads. For strength and stiffness evaluation.
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。
The science of learning through controlled experimentation. A/B testing isn't about picking winners—it's about building a culture of validated learning and reducing the cost of being wrong. This skill covers experiment design, statistical rigor, feature flagging, analysis, and building experimentation into product development. The best experimenters know that every test, positive or negative, teaches something valuable. Use when "a/b test, experiment, hypothesis, statistical significance, sample size, feature flag, variant, control, treatment, p-value, conversion rate, test winner, split test, experimentation, testing, statistics, feature-flags, hypothesis, growth, optimization, learning, validation" mentioned.
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。
Perform 12-Factor App compliance analysis on any codebase. Use when evaluating application architecture, auditing SaaS applications, or reviewing cloud-native applications against the original 12-Factor methodology.
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。
Codified expertise for managing carrier portfolios, negotiating freight rates, tracking carrier performance, allocating freight, and maintaining strategic carrier relationships. Informed by transportation managers with 15+ years experience. Includes scorecarding frameworks, RFP processes, market intelligence, and compliance vetting. Use when managing carriers, negotiating rates, evaluating carrier performance, or building freight 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。
Formal evaluation framework for Claude Code sessions implementing eval-driven development (EDD) principles
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。
X-ray any AI model's behavioral patterns — refusal boundaries, hallucination tendencies, reasoning style, formatting defaults. No API key needed.
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。
Azure Resource Manager SDK for Arize AI Observability and Evaluation (.NET).
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。
Azure AI Projects SDK for Java. High-level SDK for Azure AI Foundry project management including connections, datasets, indexes, and evaluations.
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。
High-level SDK for Azure AI Foundry projects with agents, connections, deployments, and evaluations.
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。
Azure AI Projects SDK for .NET. High-level client for Azure AI Foundry projects including agents, connections, datasets, deployments, evaluations, and indexes.
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。
Architectural decision-making framework. Requirements analysis, trade-off evaluation, ADR documentation. Use when making architecture decisions or analyzing system design.
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。