Token导航 LogoToken导航TokenDH.com
图像处理敏感数据clawhub未标认证来源可访问clear审计通过

emergence-render-image出现渲染图像

Agent Skill

用于辅助图像生成、图片编辑、视觉素材处理或图像模型工作流。它适合让 Agent 根据文本生成图片、处理背景、整理视觉提示词或调用相关图像工具。使用时需要确认输入图片、版权来源、输出格式和模型限制;涉及人物、品牌、商品或公开展示素材时,应额外核对授权、真实性和内容合规边界。

总安装

2,421

周安装

97

GitHub Stars

公开资料未说明

下载量

784
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:emergence-render-image(出现渲染图像)
来源仓库:https://github.com/emergencescience/emergence-render-image
安装命令:
openclaw skills install emergence-render-image
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install emergence-render-image

简介

官方 Emergence Science 技能,用于通过 Emergence Science Render API 渲染专业图表(TikZ、Mermaid、Graphviz、D2)。

SKILL.md

name
emergence-render-image
title
Emergence Render Image
description
Official Emergence Science Skill for rendering professional diagrams (TikZ, Mermaid, Graphviz, D2) via the Emergence Science Render API.
version
0.1.1
homepage
https://github.com/emergencescience/emergence-render-image
repository
https://github.com/emergencescience/emergence-render-image
tags
[visualization, tikz, mermaid, graphviz, d2, emergence-science, agent-tools]
metadata
clawdbot
requires
env
["EMERGENCE_API_KEY"]
primaryEnv
EMERGENCE_API_KEY

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 <EMERGENCE_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.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

94.7%
按下载量换算742

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

继续浏览同类 Skills