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Found 588 Skills
MCP server for Google Ads, Meta Ads & GA4 — 250+ tools for campaign management, analytics & optimization across all platforms
End-to-end data engineering pipeline using Harvard Art Museums API with ETL, SQL analytics, and Streamlit visualization
ETL pipeline and analytics application for Harvard Art Museums API with SQL storage and Streamlit visualization
Murder Mystery 2 inventory tracking, analytics dashboard, and gameplay optimization toolkit for Roblox
End-to-end data engineering and analytics application using Harvard Art Museums API with ETL pipelines, SQL analytics, and Streamlit visualization
Use the viral.app API from an agent with a local CLI for account analytics, tracked videos/accounts, projects, creator hub, and live data operations.
Redis Cluster and replication guidance covering hash tags for multi-key operations, avoiding CROSSSLOT errors, and reading from replicas to scale read-heavy workloads. Use when designing keys for a sharded Redis Cluster, debugging CROSSSLOT errors on MGET / SDIFF / pipelines, configuring a multi-key transaction in a cluster, or routing reads to replicas for caches, analytics, or dashboards.
Build ETL pipelines and analytics dashboards for Harvard Art Museums API data with MySQL storage and Streamlit visualization
Community skill for applying the Geist design system to Vercel-inspired UI across React, Next.js, Vite, Astro, Svelte, Vue, HTML/CSS, Tailwind, shadcn, and Radix surfaces. Use it for typography, spacing, color tokens, material treatment, component styling, app shells, dashboards, forms, tables, dialogs, empty/loading/error states, responsive layouts, and UI polish. This is a community-authored skill, not an official Vercel skill. Trigger when the user asks for Geist, Vercel-style UI, or generic clean, modern, premium, beautiful, polished SaaS/developer-product visual design where no other final visual system, brand direction, or art direction is requested. Do not trigger for non-visual frontend work such as bug fixes, data wiring, analytics, tests, build tooling, API/state changes, or behavior-only accessibility fixes unless the task also creates or materially changes rendered UI.
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.
GPU-accelerate Python code using CuPy, Numba CUDA, Warp, cuDF, cuML, cuGraph, KvikIO, cuCIM, cuxfilter, cuVS, cuSpatial, and RAFT. Use whenever the user mentions GPU/CUDA/NVIDIA acceleration, or wants to speed up NumPy, pandas, scikit-learn, scikit-image, NetworkX, GeoPandas, or Faiss workloads. Covers physics simulation, differentiable rendering, mesh ray casting, particle systems (DEM/SPH/fluids), vector/similarity search, GPUDirect Storage file IO, interactive dashboards, geospatial analysis, medical imaging, and sparse eigensolvers. Also use when you see CPU-bound Python code (loops, large arrays, ML pipelines, graph analytics, image processing) that would benefit from GPU acceleration, even if not explicitly requested.
Datadog Browser SDK — RUM, Logs, Session Replay, profiling, product analytics, and error tracking setup, configuration, and migration. Use when upgrading Browser SDK versions, setting up RUM or Logs, or troubleshooting browser-side Datadog instrumentation.