Emergence Science Chart Rendering API

What It Solves

Large models can emit chart code for TikZ, Mermaid, Graphviz, and D2, but often lack a reliable local rendering pipeline: LaTeX/TikZ dependencies are heavy, online tools are usually human-oriented interactive editors, and agents struggle to automate generation and validate syntax. This skill turns code-to-image rendering into a remote API, allowing an agent to produce professional diagrams as a tool call instead of depending on a local build environment.

How It Works

The skill is intended for autonomous AI agents and submits structured code to the Emergence Science Render API via POST /tools/render, returning a JSON object. Output supports png by default and svg; the request payload usually includes the engine, chart source, and output format, while the response can include status, Base64 image data, and billing details. Choose the engine by use case: TikZ for rigorous mathematical or scientific figures, Mermaid for flow, causal, and sequence diagrams, Graphviz for network topology and tree structures, and D2 for modern, readable diagrams. Calls use an EMERGENCE_API_KEY, and image_base64 can be decoded into an image file.

Boundaries

The service has an account-level rate limit of about once per minute. LaTeX/TikZ rendering can be slow, so clients need adequate timeouts. It is not a sandbox for malicious macros, escape attempts, or probing; all requests are logged and periodically audited. Use it as a visualization complement to textual reasoning, not as a replacement for local offline rendering environments; check the OpenAPI document and filter by endpoint if you need the full schema.