Profile and explore a dataset to understand its shape, quality, and patterns. Use when encountering a new table or file, checking null rates and column distributions, spotting data quality issues like duplicates or suspicious values, or deciding which dimensions and metrics to analyze.
How to install explore-data?
clawpod-app/awesome-openclaw-agent-packs/explore-data
$npx -y skills add clawpod-app/awesome-openclaw-agent-packs --skill explore-dataInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/clawpod-app/awesome-openclaw-agent-packs" --skill "clawpod-app/awesome-openclaw-agent-packs/explore-data"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/clawpod-app/awesome-openclaw-agent-packs" that are relevant to the current task. Run `npx skills add "https://github.com/clawpod-app/awesome-openclaw-agent-packs"` and select the relevant skills, then follow their instructions.
Related
6 picksType
- azure-kustoQuery and analyze data in Azure Data Explorer (Kusto/ADX) using KQL for log analytics, telemetry, and time series analysis.Jul 2026
- analyticsWhen the user wants to set up, improve, or audit analytics tracking and measurement.Jul 2026
- firecrawl-dashboard-reportingPull metrics from analytics dashboards and internal web tools with Firecrawl browser.Jun 2026
- data-storytellingTransform data into compelling narratives using visualization, context, and persuasive structure.Jul 2026
- data-visualizationCreate effective data visualizations with Python (matplotlib, seaborn, plotly).Jul 2026
- extension-oqlMake a canister's data queryable by the Caffeine Data Intelligence agent.Jul 2026
