1,379 件 ・ 関連度順
概要と使いどころ
Profile construction data to understand characteristics, distributions, quality metrics, and patterns. Essential for data quality assessment and ETL planning.
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。
Fetch weather data for construction scheduling. Historical data, forecasts, and risk assessment for outdoor work.
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。
Technical due diligence for M&A, investment, or acquisition. Reads a target company's codebase and generates a comprehensive tech DD report with architecture assessment, tech debt quantification, scalability analysis, security posture, team capability inference, build system quality, test coverage, deployment maturity, and open source license risks. Outputs tech-dd-report.md formatted like a real investment memo with risk ratings, remediation costs, and go/no-go recommendation.
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。
Analyze roster fit and personality dynamics. Leadership assessment, role clarity, locker room culture, trade/signing impact.
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。
Individualized development plans by weakness. Skill assessments, call reviews, ride-along checklists, certification tracking.
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。
Evaluates which SaaS tools can be replaced with AI agents. Takes a list of current SaaS subscriptions with costs, assesses replacement feasibility, estimates build vs buy economics, identifies Claude+MCP alternatives, and generates a comprehensive replacement plan with priority matrix, ROI analysis, implementation timeline, and risk assessment.
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。
Uses Agent SDK to deploy 3 parallel agents for client onboarding -- workflow auditor, tech stack mapper, and strategy drafter. Real consulting workflow that produces a complete client assessment.
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。
Production incident response automation. Reads logs, checks recent deploys, identifies root cause, suggests fixes, drafts incident comms, creates post-mortem templates. Severity classification (SEV1-4), escalation paths, status page updates. Generates incident-report.md with timeline, root cause, impact assessment, remediation steps, and prevention measures.
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。
Uses 1M context window to ingest an entire codebase and output a file-by-file migration plan. Supports JS to TS, React class to hooks, framework migrations, and more. Generates migration-plan.md with file inventory, dependency graph, migration order, file-by-file changes, estimated effort, and risk assessment.
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。
Structured deal assessment using MEDDIC, BANT. Risk scoring, required evidence by stage, red flag detection, coaching points.
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。
Assesses how ready a business is for AI adoption across six dimensions. Evaluates data maturity, tech stack, team skills, process documentation, budget, and culture. Generates a comprehensive ai-readiness-report.md with scores, gap analysis, and recommended starting points. Aligned with OneWave AI's audit 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。
Uses Cowork-style multi-step analysis to process deal room documents -- contracts, financials, org charts. Outputs risk assessment, term comparison, key findings, and negotiation recommendations.
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。
Analyzes changesets with risk scoring, categorization by type and impact, and release note preparation. Use when extracting insights from raw change data.
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。
Renamed to /model-assessment in v6 (removed in v7).
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。
Renamed to /model-assessment in v6 (removed in v7).
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。
Renamed to /model-assessment in v6 (removed in v7).
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。
Renamed to /model-assessment in v6 (removed in v7).
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 designing or auditing how an LLM or multimodal LLM is evaluated on a clinical task (report generation, VQA, text extraction). Covers reference standard, clinical-efficacy metrics beyond BLEU/ROUGE, hallucination, contamination and prompt sensitivity. Imaging models are /model-assessment.
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 validating or evaluating a trained medical-imaging model. Audits split leakage and validation design, computes task-correct held-out metrics (Dice + HD95, AUROC + AUPRC, FROC, calibration), and covers uncertainty/OOD and Grad-CAM explainability, each with a gate.
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。
Virginia Consumer Data Protection Act (VCDPA) compliance implementation. Covers 5 consumer rights, controller obligations, processor requirements, opt-in for sensitive data, data protection impact assessments, AG enforcement, and cure period provisions. Effective January 1, 2023.
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。
Vendor privacy risk tiering methodology for processor management. Covers scoring factors including data volume, sensitivity, transfer locations, certifications, breach history, and control maturity with weighted risk calculation and tier assignment.
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。
Implements the UK Age Appropriate Design Code (Children's Code) 15 standards under the Data Protection Act 2018 Section 123. Covers best interests assessment, age-appropriate application, transparency, data minimization, geolocation restrictions, and profiling defaults. Keywords: AADC, Children's Code, ICO, age appropriate design, UK.
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。
Vendor certification acceptance criteria and equivalence mapping. Covers ISO 27701, SOC 2 Privacy, APEC CBPR, EU Code of Conduct evaluation, certification scope analysis, gap supplementation requirements, and cross-framework equivalence assessment.
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。
US state privacy law applicability assessment tool. Evaluates revenue thresholds, data volume thresholds, business exemptions (GLBA, HIPAA, nonprofits), employee data carve-outs, and SBA small business determinations across all enacted state privacy laws.
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。