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Found 131 Skills
Time-series database implementation for metrics, IoT, financial data, and observability backends. Use when building dashboards, monitoring systems, IoT platforms, or financial applications. Covers TimescaleDB (PostgreSQL), InfluxDB, ClickHouse, QuestDB, continuous aggregates, downsampling (LTTB), and retention policies.
Skill for building platform-independent design systems. Develops consistent component libraries for all UI frameworks. Use proactively when user needs consistent UI components or mentions design tokens. Triggers: design system, component library, design tokens, shadcn, 디자인 시스템, デザインシステム, 设计系统, sistema de diseño, biblioteca de componentes, tokens de diseño, système de design, bibliothèque de composants, jetons de design, Design-System, Komponentenbibliothek, Design-Tokens, sistema di design, libreria di componenti, token di design Do NOT use for: one-off UI changes, backend development, or simple static sites.
Riot 공식 LoL Esports 데이터와 Oracle's Elixir 스타일 historical 데이터로 LCK 경기 결과, 현재 순위, live turning point, 밴픽 matchup/synergy, patch meta, 팀 파워 레이팅을 조회한다.
Use this skill to analyze an existing PostgreSQL database and identify which tables should be converted to Timescale/TimescaleDB hypertables. **Trigger when user asks to:** - Analyze database tables for hypertable conversion potential - Identify time-series or event tables in an existing schema - Evaluate if a table would benefit from Timescale/TimescaleDB - Audit PostgreSQL tables for migration to Timescale/TimescaleDB/TigerData - Score or rank tables for hypertable candidacy **Keywords:** hypertable candidate, table analysis, migration assessment, Timescale, TimescaleDB, time-series detection, insert-heavy tables, event logs, audit tables Provides SQL queries to analyze table statistics, index patterns, and query patterns. Includes scoring criteria (8+ points = good candidate) and pattern recognition for IoT, events, transactions, and sequential data.
Industrial AI literature research with mandatory intake questions, venue-aware source prioritization, structured report outputs, and survey draft generation. Use when the user needs up-to-date research on predictive maintenance, intelligent scheduling, industrial anomaly detection, smart manufacturing, cyber-physical systems, edge AI for automation, or crossover robotics-for-industry topics. Also trigger for adjacent terms: "digital twin", "industrial IoT", "Industry 4.0", "manufacturing AI", "factory automation", "process optimization", or "survey draft" in industrial contexts.
Expert knowledge for Azure Data Manager for Agriculture development including limits & quotas, security, configuration, and integrations & coding patterns. Use when setting up BYOL creds/Private Link, ag data ingestion/IoT, AI/nutrient APIs, throttling, or Event Grid logs, and other Azure Data Manager for Agriculture related development tasks. Not for Azure Data Explorer (use azure-data-explorer), Azure Data Factory (use azure-data-factory), Azure Synapse Analytics (use azure-synapse-analytics), Azure Databricks (use azure-databricks).
Use this skill whenever the user asks about live sports scores, standings, team stats, game summaries (with box score, leaders, scoring plays, odds, and win probability), NFL / NBA / MLB / NHL / NCAA / MLS / EPL / WNBA games, team schedules, polls, or rankings. ESPN sports CLI with live scores across 10 leagues, offline search, head-to-head comparisons, and rich per-game summary payloads. No API key required. Triggers on natural phrasings like 'what's the score of the Lakers game', 'Patriots schedule this week', 'NFL standings', 'box score for tonight's Mavs game', 'Chiefs vs Eagles head to head', 'who's on top of the AP poll'.
Expert knowledge for Azure AI Anomaly Detector development including troubleshooting, best practices, architecture & design patterns, limits & quotas, configuration, and deployment. Use when using univariate/multivariate APIs, Docker/IoT Edge containers, predictive maintenance flows, or regional limits, and other Azure AI Anomaly Detector related development tasks. Not for Azure AI Metrics Advisor (use azure-metrics-advisor), Azure Monitor (use azure-monitor), Azure Machine Learning (use azure-machine-learning).
The craft of designing icons that communicate instantly across cultures, contexts, and scales. Icon design bridges semiotics, cognitive psychology, and visual craft to create symbols that users understand without thinking. Great icons are invisible in the best way - they convey meaning so naturally that users never pause to decode them. This skill covers icon grid systems, optical alignment, stroke consistency, metaphor selection, scalability across sizes, SVG optimization, and icon set coherence. The best icon designers understand that icons are a visual language - each icon must speak the same dialect while carrying its own distinct meaning. Use when "icon, iconography, symbol, glyph, icon set, icon library, pictogram, svg icon, icon grid, icon pack, feather icons, lucide, phosphor, heroicons, icon system, icon style, icons, iconography, svg, symbols, glyphs, pictograms, ui-icons, icon-set, visual-design, design-system" mentioned.
Builds Getis-Ord Gi* hotspot analysis workflows in CARTO. Triggers when the user mentions hotspots, coldspots, spatial clusters, Getis-Ord, Gi*, cluster detection, concentration areas, "where do X cluster", spacetime hotspot, temporal clusters, time-varying patterns, hotspot trends, emerging hotspots, Mann-Kendall, or wants to find statistically significant spatial or spatiotemporal patterns in point or grid data.
Expert knowledge for Azure Stack Edge development including troubleshooting, best practices, decision making, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when running IoT Edge or GPU/Kubernetes apps, configuring VMs/storage/networking, or managing device updates, and other Azure Stack Edge related development tasks. Not for Azure Data Box (use azure-data-box-family), Azure IoT Edge (use azure-iot-edge), Azure Kubernetes Service (AKS) (use azure-kubernetes-service), Azure Virtual Machines (use azure-virtual-machines).
Stand up vLLM or SGLang serving on Jetson, using upstream vLLM on Thor and Orin JetPack 7.2+, and NVIDIA-AI-IOT vLLM on older Orin.