Data science — Skills
Data analysis, ML, and analytics prompts.
367 skills in this category
Execute KQL queries and analyze data in Azure Data Explorer for log analytics, telemetry, and time series insights.
Resolve reproduction-critical gaps by extracting dataset, preprocessing, and protocol details from primary papers.
Set up, audit, and improve analytics tracking to measure marketing and product decisions.
Uncover what customers think, say, and struggle with through transcript analysis and online research.
Implements Manus-style file-based planning to organize and track progress on complex tasks. Creates task_plan.md, findings.md, and progress.md. Use when asked to plan out, break down, or organize a multi-step project, research task, or any work requiring 5+ tool calls. Supports automatic session recovery after /clear.
Unified indexing and search across code repositories, documentation, research papers, datasets, local folders, Slack, and Google Drive.
Research organization and collaboration through Google Workspace integration.
analytics
tavily research
Universal AI-powered web scraper for any platform. Scrape data from Instagram, Facebook, TikTok, YouTube, LinkedIn, X/Twitter, Google Maps, Google Search, Google Trends, Reddit, Airbnb, Yelp, and 15+ more platforms. Use for lead generation, brand monitoring, competitor analysis, influencer discovery, trend research, content analytics, audience analysis, review analysis, SEO intelligence, recruitment, or any data extraction task.
Web search API for LLMs with real-time data access, content extraction, site crawling, and AI-powered research.
Exhaustive research with configurable depth, latency, and cost trade-offs for complex topics.
firecrawl research papers
firecrawl deep research
firecrawl market research
firecrawl lead research
emblem market research
Production-ready Grafana dashboards for system and application metrics visualization.
Microsoft Fabric Lakehouse storage for unified tabular and non-tabular data with Delta Lake, SQL analytics, and fine-grained security.
Fast web search for current information, research, and fact-finding across the internet.
Create professional, dark-themed SVG diagrams of any type — architecture diagrams, flowcharts, sequence diagrams, structural diagrams, mind maps, timelines, illustrative/conceptual diagrams, and more. Use this skill whenever the user asks for any kind of technical or conceptual diagram, visualization of a system, process flow, data flow, component relationship, network topology, decision tree, org chart, state machine, or any visual representation of structure/logic/process. Also trigger when the user says "画个图" "画一个架构图" "diagram" "flowchart" "sequence diagram" "draw me a ..." or uploads content and asks to visualize it. Output is always a standalone .svg file.
ml pipeline workflow
data-visualization
keyword research
Related categories
FAQ
What are data science skills?
Data science skills are reusable instructions that teach AI agents how to work in data science workflows. They help agents follow framework conventions, generate better output, and stay aligned with best practices in this domain.
How do I install a data science skill?
Run the install command shown on each skill page, e.g. `npx skills add owner/repo --skill skill-name`. The skill becomes available in your agent sessions after installation.
Which tools and frameworks are covered?
Browse skills tagged for data science to find options for popular stacks and libraries. The catalog is community-maintained and updated as new skills are published to GitHub.