Zscaler Vantagedata — Security skill for Claude Code
AI-Powered Multi-Table Data Analyst Agent with deterministic Pandas execution, dual-pass grounding audit, interactive Recharts visualizations, and an n8n-style workflow studio.
How to install Zscaler Vantagedata
This entry records only its repository, not the path inside it, so there is no
exact command to give. Open JK-asthetic/Zscaler---Vantagedata and copy the folder into
~/.claude/skills/, or the file into ~/.claude/agents/.
What Zscaler Vantagedata does
AI-Powered Multi-Table Data Analyst Agent with deterministic Pandas execution, dual-pass grounding audit, interactive Recharts visualizations, and an n8n-style workflow studio. Built with Next.js 14, FastAPI & Claude.
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README
VantageData v2.0 — AI-Powered Multi-Table Intelligence
**VantageData** is a production-grade enterprise AI Data Analyst agent that enables business users to query, analyze, and visualize complex multi-table datasets using natural language.
Every answer is backed by deterministic Python/Pandas tool execution, verified through an independent dual-pass grounding audit, and visualized with interactive charts.
🌟 Key Capabilities
1. Dynamic Table Registry & File Uploads
- In-Memory Table Registry: Pre-loaded with core SaaS tables (
customers,subscriptions,usage,support_tickets,revenue_events) with instant runtime indexing. - Dynamic CSV & JSON Uploads: Business users can upload arbitrary datasets at runtime. Uploaded tables inherit identical analytical tooling with zero special-casing.
2. Token-Efficient Analytical Engine (Pandas Powered)
- Never Dumps Raw Data: Unlike basic LLM wrappers that flood prompt contexts with 50-row raw JSON dumps, VantageData executes computations directly in Pandas across the entire dataset (whether 7 rows or 100,000 rows).
- Specialized Analytics:
group_by: Category grouping with aggregations (count,sum,avg,min,max).value_counts: Categorical frequency distribution and percentage shares.summary_statistics: Full column profiling (null counts, unique counts, numeric stats, top values).calculate_metric: Domain metrics (total_mrr,total_arr,churn_summary,high_risk_customers).query_table: Pinpoint record lookups with column projection (columns) to eliminate token waste.
3. Interactive Visual Chart Engine 📊
- Multi-Type Visualizations: Automatically renders interactive Pie, Donut, Bar, and Line charts in chat message bubbles via Recharts.
- Live View Switcher: Users can toggle between Pie, Bar, and Line views on the fly.
- Interactive Tooltips & KPI Cards: Hover over slices or bars for exact counts
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