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echart-skill

Analyze local data with DuckDB SQL and generate offline ECharts dashboards and reports.

43|6|Updated Mar 20, 2026
Search Tags:#data visualization#dashboard#data analysis#business intelligence#sql#duckdb#echarts
One-click install
npx skills add https://github.com/lgwanai/echart-skill --skill echart-skill-lgwanai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: echart-skill
Source: https://github.com/lgwanai/echart-skill
Command: npx skills add https://github.com/lgwanai/echart-skill --skill echart-skill-lgwanai

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, openpyxl, duckdb, structlog, pydantic, httpx, tenacity, thefuzz, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve? It lets teams run professional data analysis entirely on local machines without uploading business data to external BI platforms or exposing raw records to LLMs, while keeping every query, metric definition, and output auditable. ## Core Features & Use Cases - Local SQL Analysis Pipeline: Import CSV/Excel files or connect MySQL/PostgreSQL/MongoDB, then query through audited DuckDB runners with PII detection, column-level masking, and lineage tracking. - Visualization & Reporting: Generate 27 ECharts chart types from 354 official recipes, interactive dashboards, and pyramid-structured enterprise reports as self-contained offline HTML files. - Governance & Quality: Define reusable metric calibers and table schemas, score data quality, run forecasting and attribution analysis, and validate every deliverable through a static-plus-browser quality gate. - Use Case: A sales analyst imports a quarterly Excel export, defines the GMV metric once, asks for a regional sales dashboard, and receives an offline HTML dashboard with evidence-bound charts and an audit trail. ## Quick Start Ask the agent to import your sales spreadsheet, query it with SQL, and generate an interactive sales dashboard as a standalone HTML file.

Frequently Asked Questions about echart-skill

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate an ECharts dashboard from local data?▼

Import your CSV or Excel file, run SQL queries through the audited sql_runner script, then request a dashboard in natural language. The output is a self-contained HTML file with inlined ECharts that opens offline in any browser.

How to analyze Excel files with SQL without uploading data?▼

The import command loads Excel or CSV files into a local DuckDB database, including multi-sheet and merged-cell handling. All queries, statistics, and reports run locally, and the model only sees schemas and aggregated results.

Can it connect to MySQL or PostgreSQL databases?▼

Yes, the dbconn command manages MySQL, PostgreSQL, and MongoDB connections with passwords passed via environment variable placeholders. Queries execute through the sql_runner script with the same privacy and audit pipeline as local data.

Does it send raw data to the LLM?▼

No, raw tables and detail rows never enter the model context. The model receives only schema, aggregated results, and sample summaries, while 12 types of PII fields are auto-detected and can be masked at the column level.

Why does a generated dashboard fail validation?▼

The delivery gate blocks HTML with console errors, external CDN requests, missing ECharts instances, zero-size canvases, or evidence mismatches. Run the validate_delivery script on the output and fix the reported structural or governance issues.

What are the limitations compared to Tableau or Power BI?▼

It is an agent-driven local tool rather than a hosted BI platform, so it lacks server-based collaboration, scheduled cloud sharing, and drag-and-drop editing. It suits teams wanting offline, auditable analysis without deploying BI infrastructure.

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