「metrics」の検索結果

GDPR Data Protection Impact Assessment (DPIA) guidance under Article 35 GDPR, EDPB Guidelines WP 248 rev.01, EDPB Opinion 28/2024 (AI), and national SA blacklists/whitelists. Triggers: "DPIA", "DSFA", "Datenschutz-Folgenabschätzung", "impact assessment", "Art. 35", "do I need a DPIA", descriptions of new high-risk processing (profiling, AI, biometrics, large-scale monitoring, special category data), Art. 36 prior consultation questions, national blacklist/whitelist 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。

Interpret learning analytics data and translate dashboard findings into actionable teaching decisions. Use when reviewing LMS data, quiz patterns, or engagement 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。

Evaluates code generation models across HumanEval, MBPP, MultiPL-E, and 15+ benchmarks with pass@k metrics. Use when benchmarking code models, comparing coding abilities, testing multi-language support, or measuring code generation quality. Industry standard from BigCode Project used by HuggingFace leaderboards.

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。

Best-practices reference for preparing and instrumenting applications on Temps. Covers the app runtime contract (`.temps.yaml` health, HOST/PORT, readiness, SIGTERM, replicas, migrations) and production observability (errors, traces, metrics, logs, analytics, privacy, sampling, cardinality, credential boundaries). Use whenever building or reviewing an app for Temps, configuring health checks, adding telemetry, diagnosing missing/noisy signals, or checking OTLP/Sentry/analytics ingestion. Triggers include "temps best practices", "prepare this app for Temps", ".temps.yaml health", "temps health check", "ignore health checks in otel", "temps observability", "wire up telemetry", and "instrument this app for temps". Prefer focused setup skills for a single SDK. Use temps-cli for executing deploy and resource-management commands.

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。

Pre-earnings analysis for A-share stocks. Builds scenario frameworks (actual vs consensus, beat/miss cases), identifies key metrics to watch, and prepares positioning notes before Chinese companies report quarterly results. Use instead of the original earnings-preview skill for A-share coverage. Triggers on "A股财报前瞻", "季报前瞻", "业绩前瞻", "earnings preview", "what to watch for [company] earnings", or "pre-earnings setup".

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。

Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.

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。

Comprehensive performance analysis, bottleneck detection, and optimization recommendations for Claude Flow swarms

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。

Comprehensive truth scoring, code quality verification, and automatic rollback system with 0.95 accuracy threshold for ensuring high-quality agent outputs and codebase reliability.

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 comprehensive Product Requirements Document from product plan. Creates PRD.md with features, user stories, acceptance criteria, and success metrics. Use when creating product requirements.

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 authentication infrastructure with Sign in with Apple, biometrics, and Keychain storage. Use when user wants to add authentication, login, or Sign in with Apple.

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。

Growth skills for indie Apple developers — user acquisition, analytics interpretation, press/media outreach, community building, and indie business operations. Also covers the stage-by-stage store-growth audit and the post-launch store-signals loop. Use when user asks about growing their app, auditing growth levers, understanding metrics, getting press coverage, or running an indie dev business.

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。

Security category index for Apple platforms. Routes to the privacy-manifests skill. General secure-storage/biometrics/ATS guidance was retired in the 2026 blind-test audit — current models cover it natively.

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。

Spatially-aware quality control (QC) software for both spot-level and artifact-level QC in spot-based spatial transcripomics, such as 10x Visium. These methods calculate local (nearest-neighbors) mean and variance of standard QC metrics (library size, unique genes, and mitochondrial percentage) to identify outliers spot and large technical artifacts. Scales linearly with the number of spots and is designed to be used with 'SpatialExperiment' objects.

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。

Data quality assessment is an integral part of preparatory data analysis to ensure sound biological information retrieval. We present here the MatrixQCvis package, which provides shiny-based interactive visualization of data quality metrics at the per-sample and per-feature level. It is broadly applicable to quantitative omics data types that come in matrix-like format (features x samples). It enables the detection of low-quality samples, drifts, outliers and batch effects in data sets. Visualiz

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 Queue Storage development including best practices, limits & quotas, security, configuration, and integrations & coding patterns. Use when configuring queue auth/encryption, monitoring metrics/logs, handling limits, or coding with Azure Queue SDKs, and other Azure Queue Storage related development tasks. Not for Azure Service Bus (use azure-service-bus), Azure Event Hubs (use azure-event-hubs), Azure Table Storage (use azure-table-storage).

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 IoT Edge development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when configuring EFLOW devices, DPS/X.509 provisioning, gateway/nested topologies, CI/CD deployments, or IoT Edge metrics/logs, and other Azure IoT Edge related development tasks. Not for Azure IoT Hub (use azure-iot-hub), Azure IoT (use azure-iot), Azure IoT Operations (use azure-iot-operations), Azure Stack Edge (use azure-stack-edge).

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 Microsoft Opentelemetry development including configuration. Use when setting sampling, exporters, resource attributes, env vars, or tuning tracing/metrics behavior, and other Azure Microsoft Opentelemetry related development tasks. Not for Azure Monitor (use azure-monitor).

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 Load Balancer development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when configuring backend pools/rules, SNAT/outbound, dual-stack IPv4/IPv6, health probes, or LB metrics/APIs, and other Azure Load Balancer related development tasks. Not for Azure Application Gateway (use azure-application-gateway), Azure Front Door (use azure-front-door), Azure Traffic Manager (use azure-traffic-manager), Azure Virtual Network (use azure-virtual-network).

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 Playwright Workspaces development including troubleshooting, best practices, decision making, limits & quotas, security, and configuration. Use when managing Playwright Testing workspaces, tokens/RBAC, quotas, monitoring/metrics, or run/AADSTS7000112 issues, and other Playwright Workspaces related development tasks. Not for Azure App Testing (use azure-app-testing), Azure DevOps (use azure-devops), Azure Pipelines (use azure-pipelines), Azure Test Plans (use azure-test-plans).

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 DDoS Protection development including troubleshooting, best practices, decision making, architecture & design patterns, security, configuration, and integrations & coding patterns. Use when enabling DDoS IP/Network Protection, tuning policies, analyzing logs/metrics, or integrating NVAs and Azure Policy, and other Azure DDos Protection related development tasks. Not for Azure Firewall (use azure-firewall), Azure Firewall Manager (use azure-firewall-manager), Azure Web Application Firewall (use azure-web-application-firewall), Azure Virtual Network (use azure-virtual-network).

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 Energy Data Services development including troubleshooting, decision making, architecture & design patterns, security, configuration, integrations & coding patterns, and deployment. Use when configuring ADME metrics/partitions, choosing tiers, securing auth/ACLs/legal tags, or integrating ACZ/DDMS with Databricks/Fabric, and other Azure Energy Data Services related development tasks. Not for Azure Data Explorer (use azure-data-explorer), Azure Synapse Analytics (use azure-synapse-analytics), Azure Data Factory (use azure-data-factory), Azure Data Manager for Agriculture (use azure-data-manager-for-agri).

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 Application Network development including decision making, and configuration. Use when enabling App Network logs, Azure Monitor metrics, AKS/App Gateway versioning, or upgrade compatibility, and other Azure Application Network related development tasks. Not for Azure Virtual Network (use azure-virtual-network), Azure Virtual Network Manager (use azure-virtual-network-manager), Azure Networking (use azure-networking), Azure Application Gateway (use azure-application-gateway).

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。

Fleet skill observability with two views - health audits per-skill metrics and files/resolves issues in memory/issues/; analytics ranks the fleet by 7d runs, success rates, and anomaly 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。

Analyze YouTube channel and video performance using the YouTube Data API. Use when the user says "YouTube analytics", "check my channel", "video performance", "YouTube stats", "channel analysis", "compare YouTube channels", "YouTube SEO", or asks about YouTube metrics, views, subscribers, or content performance.

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。