Skill: davaded/echarts-ai-skill (version 0.1.1)

--- name: echarts-chart-skill description: Generate charts from natural language or tabular data, recommend chart types, and export ECharts-based HTML or SVG. Use when users ask for one-sentence chart generation, auto chart selection from data, or embeddable chart previews. metadata: short-description: Skill-first ECharts toolkit for agent chart workflows openclaw: slug: echarts-ai-skill version: 0.1.4 license: MIT homepage: https://github.com/davaded/Echarts-AI-Skill repository: https://github.com/davaded/Echarts-AI-Skill --- # ECharts Chart Skill Use this skill when the user wants chart output from a short description or from table-like data. ## Workflow 1. Translate the user's request into a `ChartRequest` JSON object. 2. If the chart type is unclear, run the recommendation command first. 3. Run the generation command to produce a stable ECharts option. 4. Run the render command when the user wants an embeddable `html` or `svg`. ## Files - Core types: `src/types/chart.ts` - Chart recommendation: `src/core/recommend.ts` - Option generation: `src/core/spec-to-option.ts` - Rendering: `src/core/render.ts` - Sample input: `examples/study-progress.request.json` - Universal metadata: `manifest.yaml`, `agents/openai.yaml` ## Setup ```powershell npm install ``` ## Output rules - `--out` writes to an exact file path. - `--out-dir` writes the default file into a directory you choose. - `desktop` and `home` are valid aliases for `--out-dir` when the user explicitly asks for those locations. - `~` is expanded to the current user's home directory. - If no output path is provided, files default to the current working directory. ## Commands ```powershell node dist/cli/recommend-chart.js --input examples\study-progress.request.json node dist/cli/generate-chart.js --input examples\study-progress.request.json node dist/cli/render-chart.js --input option.json --format html node dist/cli/render-chart.js --input option.json --format svg --out D:\reports\study-chart.svg ``` Default output filenames: - Recommendation: `spec.json` - Option: `option.json` - HTML preview: `preview.html` - SVG preview: `preview.svg` ## `ChartRequest` shape ```json { "title": "Monthly study completion", "dataset": [ { "day": "2026-03-01", "completionRate": 62, "targetRate": 75 }, { "day": "2026-03-02", "completionRate": 68, "targetRate": 75 } ], "goal": "trend", "xField": "day", "yField": "completionRate", "series": [ { "name": "Completion", "field": "completionRate" }, { "name": "Target", "field": "targetRate" } ] } ``` ## Guidance - Prefer deterministic field mapping over free-form inference when the user has already named fields. - For pie charts, keep one category field and one metric field. - For scatter charts, require numeric `xField` and `yField`. - If the user only gave natural language, construct the smallest valid `ChartRequest` before calling scripts. - If the user needs a report artifact, render `html` first and `svg` second.

path: agents/openai.yaml
content: interface:
  display_name: "ECharts AI Skill"
  short_description: "Generate and export ECharts with agent workflows"
  default_prompt: "Use $echarts-chart-skill to recommend a chart type, generate an ECharts option, or export HTML/SVG from structured data."


path: dist/types/chart.js
content: export {};


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)