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概要と使いどころ
Unity Catalog metric views: define, create, query, and manage governed business metrics in YAML. Use when building standardized KPIs, revenue metrics, order analytics, or any reusable business metrics that need consistent definitions across teams and tools.
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。
Guides privacy program effectiveness measurement including leading and lagging indicators, KPI definition, benchmarking methodology, executive reporting formats, board-level privacy dashboards, and metric-driven program improvement. Covers operational, compliance, risk, and strategic privacy metrics across the program lifecycle. Keywords: privacy metrics, KPIs, benchmarking, executive reporting, dashboard, program effectiveness.
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。
Guides DPIA for biometric processing systems including facial recognition, fingerprint, voice, iris, and gait analysis. Covers Art. 9 special category requirements, Art. 35(3)(b) mandatory DPIA triggers for large-scale biometric processing, and EDPB Guidelines 3/2019 on video surveillance. Keywords: biometric, facial recognition, fingerprint, DPIA, Art. 9, special category, EDPB Guidelines 3/2019.
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。
This skill should be used when the user asks to "make an isometric animation", "build a 2.5D isometric scene", "create an isometric infographic", "animate an exploded diagram", "do an isometric city/stack build", "show stacked layers in iso", "extrude blocks with depth", or "add a gentle camera drift to an iso scene". Covers CSS 3D transforms, SVG iso planes, and Three.js OrthographicCamera for true 3D iso — no build step.
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。
Track, calculate, and optimize key performance metrics for SaaS, marketplace, consumer, and B2B startups from seed through Series A, including unit economics, growth efficiency, and cash management. Use this skill when defining a metrics framework, calculating CAC/LTV/burn multiple, benchmarking business health, or preparing metrics dashboards for investors or board 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。
Technical leadership guidance for engineering teams, architecture decisions, and technology strategy. Includes tech debt analyzer, team scaling calculator, engineering metrics frameworks, technology evaluation tools, and ADR templates. Use when assessing technical debt, scaling engineering teams, evaluating technologies, making architecture decisions, establishing engineering metrics, or when user mentions CTO, tech debt, technical debt, team scaling, architecture decisions, technology evaluation, engineering metrics, DORA metrics, or technology strategy.
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。
Define and design a product metrics dashboard with key metrics, data sources, visualization types, and alert thresholds. Use when creating a metrics dashboard, defining KPIs, setting up product analytics, or building a data monitoring plan.
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。
Monitors and troubleshoots GKE TPU workloads, nodes, and node pools using GKE system metrics and PromQL. Use when monitoring TensorCore duty cycle, TPU memory, node readiness, multi-host TPU node pool availability, host maintenance or preemption interruptions, and calculating MTTR or MTBI metrics for GKE TPUs. Don't use for general non-TPU GKE workload monitoring or non-metric TPU debugging.
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 valid Cloud Monitoring ListTimeSeries requests and aggregation specifications from metric descriptors and resource parameters. Use when asked to create, generate, format, or build ListTimeSeries requests, JSON payloads, filter expressions, or aligner/reducer aggregations for Cloud Monitoring metrics and charts. Don't use for metric discovery or metric selection.
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 valid PromQL queries from Cloud Monitoring metric descriptors and resource parameters. Use when asked to create, generate, write, or format PromQL queries, PromQL strings, or PromQL aggregations for Cloud Monitoring metrics and resources. Don't use for raw metric discovery or metric selection.
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 crafted, highly detailed, interactive isometric SVG figures that explain a technical idea as a real physical object (a test rig, a dial gauge, a cabinet of drawers, a plotter, a lock), with many small precise solid parts, four-tone shading, correct painter's order, a framed card with title, hint and live readout, and calm eased motion. Use this whenever someone wants an isometric illustration, an explanatory diagram or figure for docs, a blog post, a landing page or an article, a "Linear-style" or "premium" technical drawing, an interactive explainer, or an SVG that shows how a system, algorithm or component works, even if they never say "isometric". Works framework-free (TypeScript/JS that writes SVG and HTML) and in React/Next.js, and can add realistic WebGL shaders (fire, exhaust, water, caustics, lamp light) that live inside the drawing in the same isometric perspective. Also publishes a finished figure to the Anatomy community gallery when asked.
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。
Draws true-isometric diorama illustrations of developer and design workspaces in one green ramp, generated as SVG with a bundled scene kit. Traits: one rounded off-white slab with a faceted bevelled edge; every face filled by the way it faces (top lightest, right darkest) from five greens; 0.9 deep-green outlines on every edge; dense fine repeated detail (rack units, ribs, vents, keys, code lines); soft green shadows and glows on the slab. Covers projection, shading, line weights, object vocabulary, layout and the iso.mjs kit (racks, databases, laptops, containers, cards, badges, books, plants, cables, status tower). Use when someone asks for isometric illustration, an iso scene, 2.5D tech art, monochrome or green isometric art, a server room, dev stack or cloud picture, or art for empty states, onboarding, 404 pages, blog headers, feature spots or marketing cards in this style.
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。
This skill helps users automatically extract detailed video metrics and channel information from YouTube based on keyword searches using the BrowserAct API. The Agent should proactively apply this skill when users express needs such as extract specific keyword YouTube video detailed data, monitor the latest video performance of competitor channels, collect comment and like counts for videos on a specific topic, find AI agent tutorials published this week and extract metrics, evaluate total views and subscriber info for specific videos, scrape detailed metrics of marketing campaign videos, track video trends for a tech topic periodically, get high quality video list data for specified keywords on YouTube, mine detailed information of the latest YouTube videos, collect video duration and engagement data for specific industries, or monitor YouTube content creator performance metrics.
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。
Print a debt-ops health summary from the metrics log, covering registration rate, hook feedback action rate, ADR creation, and AI-authored share. Use when the user asks for "debt-ops metrics", "debt health", "registry stats", or invokes $metrics. Read-only, never writes the log.
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 the user has evaluation principles or a dataset but needs help choosing the right graders, designing evaluation metrics, creating LLM-as-judge prompts, combining multiple metrics into a composite score, or building an automated evaluation pipeline. Also use when the user mentions grader selection, metric design, judge prompt engineering, rubric design, evaluation pipeline code, or "how to evaluate [X] automatically." Outputs executable OpenJudge pipeline code.
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 knowledge for Azure AI Metrics Advisor development including decision making, limits & quotas, security, configuration, and integrations & coding patterns. Use when configuring data feeds, tuning anomaly detection, managing alerts/hooks, or calling Metrics Advisor REST/SDKs, and other Azure AI Metrics Advisor related development tasks. Not for Azure AI Anomaly Detector (use azure-anomaly-detector), Azure Monitor (use azure-monitor), Azure Stream Analytics (use azure-stream-analytics).
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 crafted, highly detailed, interactive isometric SVG figures that explain a technical idea as a real physical object (a test rig, a dial gauge, a cabinet of drawers, a plotter, a lock), with many small precise solid parts, four-tone shading, correct painter's order, a framed card with title, hint and live readout, and calm eased motion. Use this whenever someone wants an isometric illustration, an explanatory diagram or figure for docs, a blog post, a landing page or an article, a "Linear-style" or "premium" technical drawing, an interactive explainer, or an SVG that shows how a system, algorithm or component works, even if they never say "isometric". Works framework-free (TypeScript/JS that writes SVG and HTML) and in React/Next.js, and can add realistic WebGL shaders (fire, exhaust, water, caustics, lamp light) that live inside the drawing in the same isometric perspective.
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。
Applies Eric Ries's Lean Startup methodology for building products under extreme uncertainty. Use when iterating toward product/market fit, designing MVPs, deciding whether to pivot or persevere, setting up actionable metrics, or accelerating the Build-Measure-Learn loop. Triggers include 'how do we test this idea fast', 'what should our MVP look like', 'our metrics look good but we're not growing', 'should we pivot', 'we're building features no one uses', 'how do we measure validated learning', 'vanity metrics vs real metrics', 'how to do innovation accounting'. NOT for companies with proven product/market fit scaling a known playbook (use Crossing the Chasm), not for determining Market Type (use Four Steps), not for sales methodology (use SPIN Selling), not for pricing strategy (use Monetizing Innovation).
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。
Systematic investigation of metric changes and anomalies. Use when a metric unexpectedly changes, investigating business metric drops, explaining performance variations, or drilling into aggregated metric drivers.
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。
Standard business metric calculation with industry benchmarks. Use when calculating SaaS metrics (MRR, churn, LTV, CAC), e-commerce KPIs, or product analytics metrics with proper definitions.
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 privacy KPI dashboards tracking DSAR volume and response time, breach count and severity, DPIA completion rate, training coverage, and consent rates. Includes metric definitions, data collection patterns, visualization designs, and executive reporting templates for privacy program measurement.
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。
Governs biometric data processing for employee timekeeping and access control under Art. 9 GDPR special category rules. Covers fingerprint, facial recognition, iris scanning, and voice recognition. Applies necessity tests, evaluates less intrusive alternatives, and implements employee objection procedures. Keywords: biometric data, Art. 9, fingerprint, facial recognition, access control, timekeeping, special category.
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。
Делает ревью продуктовых метрик — тренды, аномалии, root causes и рекомендации к действиям. Включает декомпозицию North Star (L1/L2), диагностику retention-кривых, анализ воронки, разбор A/B-экспериментов, проверку соответствия OKR и фреймворк атрибуции аномалий. User-invoked only — do NOT auto-trigger. Triggers on /pm-metrics, "обзор метрик", "разбор воронки", "анализ удержания", "ретеншн", "A/B результаты", "review metrics", "DAU analysis", "retention analysis", "funnel analysis", "metric anomaly".
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 knowledge for real-time and baked lighting in games - from cinematography fundamentals to engine-specific optimization, covering GI, time-of-day, volumetrics, and platform-aware lighting pipelinesUse when "lighting, light design, baked lighting, realtime lighting, lightmap, lightmapping, light probe, reflection probe, global illumination, GI, ambient occlusion, shadow, shadow cascade, time of day, day night cycle, volumetric fog, volumetric lighting, god rays, HDR, tonemapping, bloom, exposure, emissive, area light, Lumen, Enlighten, ray tracing, RTGI, light baking, lighting, global-illumination, lightmapping, shadows, GI, light-probes, reflection-probes, HDR, tonemapping, volumetric, fog, time-of-day, baked, realtime, mixed-lighting, lumen, enlighten, radiosity, ray-tracing, RTGI" 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。