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Found 622 Skills
SQL and Python-based employee performance analytics with KPI aggregation, departmental insights, and HR dashboard generation
Murder Mystery 2 inventory tracking, analytics dashboard, and gameplay optimization toolkit for Roblox
End-to-end data engineering pipeline for Harvard Art Museums API with ETL, 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.
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.
Every Semrush Analytics + Projects feature, plus a local SQLite store and cross-domain joins no other Semrush tool has. Trigger phrases: `show me what changed for <domain> this week`, `find the keyword gap between <my domain> and <competitor>`, `show me new referring domains for <domain>`, `triage my Site Audit`, `what did Semrush cost me this month`, `detect keyword cannibalization on <domain>`, `track SERP feature changes for <keyword>`, `use semrush`, `run semrush`.
Routes PubNub questions to the correct documentation source, MCP tool, and specialist skill. Classifies intent (chat vs non-chat, conceptual vs implementation, runtime testing vs analytics) and points the agent to the right next step. Use when a user mentions PubNub for the first time, asks "where do I start", "which docs", "what should I use", or any time the appropriate next skill is unclear.
Expert-level data science, analytics, visualization, and statistical modeling
Comprehensive guide to building video applications with Mux, the developer-first video infrastructure platform. This skill covers video streaming, live streaming, player integrations, analytics with Mux Data, and AI-powered workflows. Whether you are building a video-on-demand platform, live streaming application, or integrating video into an existing product, this documentation provides the patterns and code examples needed to ship quickly.
Эксперт Sales Ops. Используй для процессов продаж, CRM, forecasting и sales analytics.
Use when you need to choose the right visualization for your data and question, then create a narrated report that highlights insights and recommends actions. Invoke when analyzing data for patterns (trends, comparisons, distributions, relationships, compositions), building dashboards or reports, presenting metrics to stakeholders, monitoring KPIs, exploring datasets for insights, communicating findings from analysis, or when user mentions "visualize this", "what chart should I use", "create a dashboard", "analyze this data", "show trends", "compare these metrics", "report on", "what does this data tell us", or needs to turn data into actionable insights. Apply to business analytics (revenue, growth, churn, funnel, cohort, segmentation), product metrics (usage, adoption, retention, feature performance, A/B tests), marketing analytics (campaign ROI, attribution, funnel, customer acquisition), financial reporting (P&L, budget, forecast, variance), operational metrics (uptime, performance, capacity, SLA), sales analytics (pipeline, forecast, territory, quota attainment), HR metrics (headcount, turnover, engagement, DEI), and any scenario where data needs to become a clear, actionable story with the right visual form.
Use when creating data reports on Xiaohongshu performance, summarizing analytics findings, presenting insights to stakeholders, documenting marketing results, or building reporting templates