Charto

Zero External Dependencies

This skill is fully self-contained. No additional setup or npm install required.

• ✅ All JavaScript dependencies bundled into bundle.mjs
• ✅ WASM binaries included for PNG rendering
• ✅ Works immediately after folder download
• ✅ Cross-platform (macOS, Linux, Windows)

Just use the .github/skills/charto/ folder as-is.

This skill is a single end-to-end workflow with internal phases, not separate sub-skills.

Project assets for this skill live here:

• references/chart-workflow-guide.md: decision and workflow reference
• scripts/build/dist/: prebuilt runtime snapshot for direct sharing (generated by npm run build)
  • bundle.mjs: fully bundled MCP server (all JS deps included)
  • index_bg.wasm: WASM binary for PNG rendering
• Root scripts/*.mjs: runnable helper scripts that import from .github/skills/charto/scripts/build/dist/

Core flow:

1. Load the input data with load_tabular_file.
2. Infer schema via infer_schema.
3. Propose ranked chart choices with suggest_chart_options.
4. If the user picked an option, build it with generate_vega_spec.
5. Render output artifacts with render_chart_preview.
6. Return artifact paths and a short rationale.

Large dataset flow (required):

1. Always pass rowLimit when a file may be large.
2. If large dataset metadata is returned:
   • clearly state that large dataset mode was triggered
   • surface recommended options first
   • explain any fallback aggregation applied
3. In large dataset mode, use includePngBase64: false unless inline base64 is explicitly requested.

Rules:

• Never invent columns, values, or transformations.
• Prefer readable, aggregated visuals over noisy row-level output.
• If no viable chart option exists, explain why and ask for dataset adjustments.
• Return generated artifact paths whenever available.
• Ask for the dataset path if missing.
• PNG rendering uses bundled WASM; if rendering fails, fall back to HTML output (no external dependencies needed).