Loading...
Loading...
Found 131 Skills
Expert knowledge for Azure Osconfig development including troubleshooting, security, configuration, and integrations & coding patterns. Use when running OSConfig via IoT Hub for commands, SSH posture, agent health, Windows baselines, or LAPS, and other Azure Osconfig related development tasks. Not for Azure Update Manager (use azure-update-manager), Azure Automation (use azure-automation), Azure Policy (use azure-policy).
Academic backtesting framework for quantitative research. ~30 risk and performance ratios, 10 classes of indicators, event-driven engine with 6+ strategies, MPT optimizer, forward-looking simulation with Johnson SU + t-Copula, walk-forward CV, stress testing, fundamental analysis (Altman Z, Piotroski, DuPont). All flat Python + numpy.
Expert-level biology, biotechnology, genetics, bioinformatics, and computational biology
Use when starting a new project, adding a major feature to an existing system, or when unsure which skills to run and in what order. Supports macOS, iOS, web, full-stack, voice agent, and edge/IoT+ML projects.
Expert knowledge for Azure Kubernetes Service Edge Essentials development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when managing AKS Edge/Arc clusters, Arc connectivity, IoT/OPC/ONVIF workloads, TPM/AI deployments, or gMSA, and other Azure Kubernetes Service Edge Essentials related development tasks. Not for Azure Kubernetes Service (AKS) (use azure-kubernetes-service), Azure IoT Edge (use azure-iot-edge), Azure Stack Edge (use azure-stack-edge), Azure Container Apps (use azure-container-apps).
Use this skill when creating database schemas or tables for Timescale, TimescaleDB, TigerData, or Tiger Cloud, especially for time-series, IoT, metrics, events, or log data. Use this to improve the performance of any insert-heavy table. **Trigger when user asks to:** - Create or design SQL schemas/tables AND Timescale/TimescaleDB/TigerData/Tiger Cloud is available - Set up hypertables, compression, retention policies, or continuous aggregates - Configure partition columns, segment_by, order_by, or chunk intervals - Optimize time-series database performance or storage - Create tables for sensors, metrics, telemetry, events, or transaction logs **Keywords:** CREATE TABLE, hypertable, Timescale, TimescaleDB, time-series, IoT, metrics, sensor data, compression policy, continuous aggregates, columnstore, retention policy, chunk interval, segment_by, order_by Step-by-step instructions for hypertable creation, column selection, compression policies, retention, continuous aggregates, and indexes.
Builds custom trigger types for events iii does not handle natively. Use when integrating webhooks, file watchers, IoT devices, database CDC, or any external event source.
Technical analysis patterns - Elliott Wave, Wyckoff, Fibonacci, Markov Regime, and Turtle Trading with confluence detection. Use when analyzing charts, identifying trading signals, or calculating technical levels.
Workload-aware architecture design for Apache Doris. MUST USE when designing data architectures, choosing between data models, planning ingestion strategies, sizing clusters, or translating business requirements into Apache Doris system designs. Complements doris-best-practices with decision frameworks and sizing-first workflow. Use when user describes a workload involving: IoT, sensor data, telemetry, real-time analytics, dashboard, log analysis, log search, CDC sync, time-series, device monitoring, point query service, ad-hoc analytics, lakehouse federation, ETL/ELT pipeline, report analytics, clickstream, user behavior, observability, metrics, fleet tracking, or any OLAP workload requiring table design from scratch. Also triggers on prompts like: "design a table for...", "how should I store...", "build an architecture for...", "we have X devices sending data every Y seconds", "recommend a cluster size for...", "what data model should I use for...", "we need to ingest X GB/day", "migrate from MySQL/PostgreSQL to Apache Doris". Also use for legacy analytics/search/serving stack consolidation prompts even when Apache Doris is not named explicitly, including replacing or migrating from Impala, Kudu, Elasticsearch/ES, Greenplum, Presto, HBase, Hive, Hadoop, Redis, or Lambda-style multi-engine data platforms.
Use when choosing among Nature, Nature Methods, or Nature Biotechnology, or when preparing a Nature Portfolio life-science manuscript for venue fit, article-type framing, and policy-aware pre-submission checks.
Guide des bonnes pratiques Vue.js 3 couvrant la Composition API, la conception de composants, les patrons de réactivité, le styling utility-first avec Tailwind CSS, l'intégration native de la bibliothèque de composants PrimeVue et l'organisation du code. À utiliser lors de l'écriture, la revue ou le refactoring de code Vue.js pour garantir des patrons idiomatiques et un code maintenable.
A skill that uses GLM-V native grounding capabilities for coordinate conversion, bounding-box visualization, and more. GLM-V native grounding can locate any target specified by the prompt in an image and output relative coordinates normalized to 0-1000 based on image size. Coordinate formats include 2D bounding box (default), 2D points, and 3D bounding box. GLM-V also supports spatiotemporal localization and tracking of multiple prompt-specified targets in videos, outputting 2D bounding boxes per second.