← Back to Skills Marketplace
emergencescience

Emergence Render Image

by emergencescience · GitHub ↗ · v0.1.1 · MIT-0
cross-platform ✓ Security Clean
75
Downloads
0
Stars
0
Active Installs
2
Versions
Install in OpenClaw
/install emergence-render-image
Description
Official Emergence Science Skill for rendering professional diagrams (TikZ, Mermaid, Graphviz, D2) via the Emergence Science Render API.
README (SKILL.md)

Emergence Render Image Skill

This skill provides a programmatic interface to the Emergence Science Render API. It allows humans and AI agents to transform structured code into professional-grade scientific and technical visualizations.

1. Persona & Objective

The primary user of this skill is the Autonomous AI Agent. As many LLMs lack the ability to directly render pixels, this skill acts as the agent's "visual cortex" and "drawing hand," enabling it supplemented textual reasoning with high-fidelity diagrams.

Existing Pain Points

  • Human-Centric Tools: Most online TikZ/Mermaid tools are interactive editors designed for humans, making them difficult for agents to automate.
  • Syntactic Hallucination: LLMs often struggle with valid TikZ syntax. Without the ability to perform repetitive editing and validation via a stable API, agents are subject to hallucinations.
  • Heavy Dependencies: TikZ and LaTeX libraries are resource-heavy to install and maintain locally. A REST API is the most efficient solution for agents to generate serious academic-level images on demand.

2. Authentication & Credits

Registration

Humans must register on the Emergence Science Web UI using GitHub OAuth.

Token Management

  1. Navigate to the Web UI after login to obtain your EMERGENCE_API_KEY.
  2. Paste this token into your Agent's environment configuration.
  3. Scoped Access: This API key is utilized exclusively by this skill to call the rendering endpoint.
  4. Incentive: Every new verified user is granted 1,000,000 micro-credits to be used across the Emergence Science ecosystem, including rendering services.

3. Usage & Examples

The service supports multiple diagramming engines and output formats.

Endpoint

https://api.emergence.science/tools/render

Method: POST
Headers:

  • Authorization: Bearer \x3CEMERGENCE_API_KEY>
  • Content-Type: application/json

[!WARNING] Response Latency: The REST API response time can be as slow as 1 minute due to the heavy computational overhead of LaTeX/TikZ rendering. Agents and callers should implement appropriate socket timeouts and be patient during large image generation.

Supported Formats

  • png (Default)
  • svg

[Engine: TikZ]

Used for high-rigor mathematical and scientific plots.

Request Payload:

{
  "engine": "tikz",
  "code": "\\begin{tikzpicture}[x=1cm, y=1cm]\
\\draw[blue, thick] (0,0) circle (1.5);\
\\
ode at (0,0) {Quantum Core};\
\\end{tikzpicture}",
  "format": "png"
}

[Engine: Mermaid]

Best for workflows, causal graphs, and sequence diagrams.

Request Payload:

{
  "engine": "mermaid",
  "code": "graph TD\
  Agent[AI Agent] -->|Auth| Hub[Emergence Hub]\
  Hub -->|Credits| Render[Render API]\
  Render -->|Image| Agent",
  "format": "svg"
}

[Engine: Graphviz]

Ideal for visualizing complex network topologies and tree structures.

Request Payload:

{
  "engine": "graphviz",
  "code": "digraph G {\
  rankdir=LR;\
  Input -> Processor -> Output;\
  Processor -> DB [label=\"cache\"];\
}",
  "format": "png"
}

[Engine: D2]

Modern, fast, and highly readable diagramming language.

Request Payload:

{
  "engine": "d2",
  "code": "User -> API: Request\
API -> Database: Query\
Database -> API: Results\
API -> User: Response",
  "format": "png"
}

[Response Schema]

The API returns a JSON object containing the status, the rendered image in Base64 format, and billing details.

Sample Response:

{
    "status": "success",
    "data":
    {
        "image_base64": "PD94bWwgdmVyc2lvbj0iMS4wIiBlbmNvZ...dmc+Cg==",
        "format": "svg"
    },
    "billing":
    {
        "cost": 0.001,
        "remaining_credit": 0.564
    }
}

Post-Processing: Agents are encouraged to decode the data.image_base64 string directly using the base64 command (e.g., echo "..." | base64 -d > output.png).

[Discovery & OpenAPI]

The full up-to-date REST API schema is available at: https://emergence.science/openapi.json

[!TIP] The openapi.json file is extensive. It is recommended to use the jq command for targeted inspection and filtering of endpoints.

4. Policy & Constraints

Rate Limiting

Users and agents must respect the 1-minute rate limit per account. Excessive requests may trigger temporary IP-based or Account-based blocks.

Governance & Security

[!CAUTION] No Malicious Code Injection: Use of the API to attempt sandbox escapes, network penetration, or injection of malicious LaTeX/Mermaid macros is strictly prohibited. All requests are logged and periodically audited. Violations will result in immediate forfeiture of credits and account suspension.


[!NOTE] Future Roadmap: Support for PlantUML and C4 architectural diagrams is scheduled for release in May 2026.

Usage Guidance
This skill appears coherent for a hosted rendering API. Before installing: verify the API host and GitHub repository yourself (confirm the repo and endpoints exist), limit the scope of the EMERGENCE_API_KEY (use scoped keys if available), monitor billing/credit usage (the SKILL.md mentions credits and per-request cost), and be aware the skill recommends command-line tools like base64/jq (optional). If you allow autonomous agents to use this skill, ensure the agent's permissions match your risk tolerance and rotate the API key if you stop using the service.
Capability Analysis
Type: OpenClaw Skill Name: emergence-render-image Version: 0.1.1 The skill is a legitimate tool for rendering technical diagrams (TikZ, Mermaid, Graphviz, D2) via the Emergence Science API (api.emergence.science). It follows standard authentication patterns using an environment variable (EMERGENCE_API_KEY) and provides clear, helpful instructions for agents to process Base64-encoded image data. No indicators of malicious intent, data exfiltration, or harmful prompt injection were found.
Capability Tags
cryptorequires-oauth-tokenrequires-sensitive-credentials
Capability Assessment
Purpose & Capability
The skill claims to call a rendering REST API and only asks for EMERGENCE_API_KEY, which is proportionate and expected for a hosted render service. No unrelated credentials, config paths, or surprising binaries are requested.
Instruction Scope
SKILL.md stays within rendering-related actions (POST to the render endpoint, decode base64 images, respect rate limits). It suggests using common utilities (base64, jq) but does not instruct reading unrelated files or environment variables. The references to command-line tools are optional recommendations and not required for core functionality.
Install Mechanism
This is an instruction-only skill with no install spec and no code files, so nothing is written to disk during install — lowest-risk distribution model.
Credentials
Only EMERGENCE_API_KEY is declared as required and used by the instructions. There are no extra secrets or unrelated environment variables requested.
Persistence & Privilege
always is false and the skill does not request elevated or persistent platform privileges or modifications to other skills. Autonomous invocation is allowed by default (not a problem on its own).
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install emergence-render-image
  3. After installation, invoke the skill by name or use /emergence-render-image
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v0.1.1
Fixed metadata inconsistencies and narrowed credential scope for security compliance.
v0.1.0
Initial release of the Emergence Science Render API skill.
Metadata
Slug emergence-render-image
Version 0.1.1
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 2
Frequently Asked Questions

What is Emergence Render Image?

Official Emergence Science Skill for rendering professional diagrams (TikZ, Mermaid, Graphviz, D2) via the Emergence Science Render API. It is an AI Agent Skill for Claude Code / OpenClaw, with 75 downloads so far.

How do I install Emergence Render Image?

Run "/install emergence-render-image" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Emergence Render Image free?

Yes, Emergence Render Image is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Emergence Render Image support?

Emergence Render Image is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Emergence Render Image?

It is built and maintained by emergencescience (@emergencescience); the current version is v0.1.1.

💬 Comments