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Found 65 Skills
Create, edit, audit, and extract Excel spreadsheets (.xlsx): generate reports/exports, apply formulas/formatting/charts/data validation, parse existing workbooks, and avoid spreadsheet risks (formula injection, broken links, hidden rows). Supports ExcelJS, openpyxl, pandas, XlsxWriter, and SheetJS.
Detect anomalies in data using statistical and ML methods. Z-score, IQR, Isolation Forest, and time-series anomalies.
Shuffle repetitive JSON objects safely by validating schema consistency before randomising entries.
Ingestion pipeline architecture overview and convention reference. Use when you need a quick orientation to the pipeline framework or want to know which doctor agent to use for a specific concern.
Fetch analytics from Umami. Use when the user asks about umami, analytics, website traffic, daily stats, pageviews, visitors, how is my site doing, traffic report, site performance, bounce rate, visitor count, active users, who is on my site, or website statistics.
Vendor-neutral skill to analyze onboarding funnel dropoff and propose prioritized interventions.
Vendor-neutral skill to compare forecast assumptions over time and flag high-impact drift.
Use this skill when the user wants to build tool/scripts or achieve a task where using data from the Hugging Face API would help. This is especially useful when chaining or combining API calls or the task will be repeated/automated. This Skill creates a reusable script to fetch, enrich or process data.
A fast, extensible progress bar for Python and CLI. Instantly makes your loops show a smart progress meter with ETA, iterations per second, and customizable statistics. Minimal overhead. Use for monitoring long-running loops, simulations, data processing, ML training, file downloads, I/O operations, command-line tools, pandas operations, parallel tasks, and nested progress bars.
Analyze datasets to discover patterns, anomalies, and relationships. Use when exploring data files, generating statistical summaries, checking data quality, or creating visualizations. Supports CSV, Excel, JSON, Parquet, and more.
Explains core Apache Beam programming model concepts including PCollections, PTransforms, Pipelines, and Runners. Use when learning Beam fundamentals or explaining pipeline concepts.
Research Xiaohongshu accounts from validated recent-post surfaces, then aggregate account-level content signals without pretending follower or bio metrics are available when the validated profile actor is empty.