Token导航 LogoToken导航TokenDH.com
效率需要联网clawhub未标认证来源可访问clear审计提醒

emergence-diagram-rendering涌现图渲染

Agent Skill

emergence-diagram-rendering 用于补充效率相关能力,适合在 OpenClaw 中需要让 Agent 承接效率相关任务时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

2,254

周安装

93

GitHub Stars

公开资料未说明

下载量

737
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-diagram-rendering(涌现图渲染)
来源仓库:https://github.com/emergencescience/emergence-diagram-rendering
安装命令:
openclaw skills install emergence-diagram-rendering
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-diagram-rendering

简介

自主代理的高保真图表生成(Mermaid、D2、Graphviz)。支持本地优先渲染和持久运行历史记录。

SKILL.md

name
emergence-diagram-rendering
slug
emergence
title
Emergence Diagram Rendering
description
High-fidelity diagram generation (Mermaid, D2, Graphviz) for autonomous agents. Supports local-first rendering and persistent run history.
version
1.1.0
author
Emergence Science
site
https://emergence.science
repository
https://github.com/emergencescience/emergence-diagram-rendering
requires
env
bin

Diagram Rendering Skill (Internal Monologue)

You are an autonomous solver agent capable of transforming natural language into technical visuals. You prioritize Local Rendering for speed and privacy, using the Cloud API only as a fallback.

1. Activation Triggers

Invoke this skill when the user asks to:

  • "Draw," "map out," or "diagram" a system.
  • "Visualize" an architecture or cloud infrastructure.
  • "Create a flowchart" or "sequence diagram."
  • "Show me an ERD" or "database schema."

2. Decision Reasoning

  • D2: Use for complex architecture, nested containers, and high-fidelity layouts.
  • Mermaid: Use for standard flowcharts, sequence diagrams, and simple logic paths.
  • Graphviz (DOT): Use for mathematical graphs, network topologies, and relational ERDs.

3. Template-Assisted Generation

Before generating from scratch, check ./templates/.

  • These are "Gold Standard" examples.
  • You can inject data into templates using the --inject '{"key": "value"}' flag in local_render.py.

4. Persistent Execution & Self-Correction

Your rendering attempts are stored in ./runs/<run_id>/.

  1. Attempt Render: Call ./.venv/bin/python3 scripts/local_render.py <engine> "<code>".
  2. Handle Failure: If the output is an error, open the metadata.json in the specific run directory.
  3. Parse Stderr: Read the compiler's stderr. It will pinpoint the exact line and character of your syntax error.
  4. Recursive Fix: Use the error feedback to fix your code and re-run. Do not give up until the status is "success".

5. Visual Verification (Vision Agents)

If you have a Vision Language Model (VLM) capability:

  • Inspect the generated PNG/SVG in the run folder.
  • Compare the visual output against the logical intent of the prompt.
  • If the layout is confusing or logically incorrect, refine the code and re-render.

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

89.66%
按下载量换算661

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。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