DiagForge Bootstrap
This is a lightweight onboarding skill for the DiagForge repository.
It is not the full DiagForge system.
Its job is to guide an agent to the correct GitHub repository, documents, smoke test, and execution flow.
DiagForge itself is an agent-driven closed loop built on top of Microsoft Visio.
Its goal is to turn reference figures into directly editable diagram assets by helping agents operate Visio more like a capable human user rather than as a blind API caller.
What this skill can do
This skill can help an agent:
- - understand what DiagForge is trying to achieve
- find the correct GitHub repository and entry documents
- avoid random first-run behavior and jump into the intended workflow
- run the canonical cold-start smoke test
- start reproducing reference figures through the DiagForge Visio loop
- move toward a result that a human can continue editing directly in Visio
Typical outcomes
After using this skill, an agent should be able to:
- - explain the DiagForge workflow clearly
- bootstrap itself into the repository with the correct read order
- validate that the Visio bridge and execution path are working
- begin work on figure reproduction with better layer awareness
- help produce editable
.vsdx outputs instead of dead image copies
What this skill is for
Use this skill when an agent needs to:
- - find the DiagForge source repository
- understand the top-level architecture quickly
- avoid free-form blind retries
- run the canonical cold-start smoke test
- begin work in the correct layer
When to use it
Use this skill when:
- - an agent is entering DiagForge for the first time
- a new environment needs to be validated before real drawing work
- a user wants an agent to help reproduce a figure through Visio
- the goal is not only to look similar to the reference, but to obtain a directly editable diagram asset
What this skill is not
This skill does not bundle the whole repository.
It does not include Visio bridge code, benchmark PNGs, or runtime artifacts.
The full project lives in the GitHub repository:
INLINECODE1
Recommended workflow
- 1. Clone the GitHub repository locally.
- Read the cold-start entry documents.
- Run the canonical smoke test before doing open-ended drawing work.
- Only then move on to real jobs or system improvements.
Clone the repository
CODEBLOCK0
If SSH is not available, use HTTPS instead.
Read order
Read these files first:
- 1. INLINECODE2
- INLINECODE3
- INLINECODE4
- INLINECODE5
- INLINECODE6
Canonical smoke test
From the repo root:
CODEBLOCK1
Expected outputs:
Routing rule
When working inside DiagForge:
- - if the issue is round-specific, keep it in review artifacts
- if it looks structural but still needs validation, write a proposal
- if it is already reusable experience, promote it into a lesson
- if the shared fix is clear, patch the owning layer directly
Where to go next
See:
- - INLINECODE9
- INLINECODE10
- INLINECODE11
DiagForge 引导技能
这是一个用于 DiagForge 仓库的轻量级上手技能。
它并非完整的 DiagForge 系统。
其职责是引导智能体找到正确的 GitHub 仓库、文档、冒烟测试以及执行流程。
DiagForge 本身是一个基于 Microsoft Visio 构建的智能体驱动闭环系统。
其目标是通过帮助智能体更像一个熟练的人类用户(而非盲目的 API 调用者)来操作 Visio,从而将参考图形转化为可直接编辑的图表资产。
本技能的功能
本技能可帮助智能体:
- - 理解 DiagForge 试图实现的目标
- 找到正确的 GitHub 仓库和入口文档
- 避免随机的首次运行行为,直接进入预期工作流程
- 运行标准的冷启动冒烟测试
- 通过 DiagForge Visio 循环开始复现参考图形
- 朝着人类可直接在 Visio 中继续编辑的结果前进
典型成果
使用本技能后,智能体应能够:
- - 清晰解释 DiagForge 工作流程
- 按照正确的阅读顺序自行引导进入仓库
- 验证 Visio 桥接和执行路径是否正常工作
- 以更好的图层感知能力开始图形复现工作
- 帮助生成可编辑的 .vsdx 输出,而非死板的图像副本
本技能的用途
当智能体需要以下操作时,请使用本技能:
- - 查找 DiagForge 源代码仓库
- 快速理解顶层架构
- 避免无目的的盲目重试
- 运行标准的冷启动冒烟测试
- 在正确的图层开始工作
使用时机
在以下情况下使用本技能:
- - 智能体首次进入 DiagForge
- 在实际绘图工作前需要验证新环境
- 用户希望智能体通过 Visio 帮助复现图形
- 目标不仅是与参考图形相似,而是获得可直接编辑的图表资产
本技能不包括的内容
本技能不包含整个仓库。
它不包括 Visio 桥接代码、基准 PNG 或运行时工件。
完整项目位于 GitHub 仓库:
https://github.com/qweadzchn/DiagForge
推荐工作流程
- 1. 在本地克隆 GitHub 仓库。
- 阅读冷启动入口文档。
- 在进行开放式绘图工作前运行标准冒烟测试。
- 然后才能继续处理实际任务或系统改进。
克隆仓库
bash
git clone git@github.com:qweadzchn/DiagForge.git
cd DiagForge
如果 SSH 不可用,请改用 HTTPS。
阅读顺序
请先阅读以下文件:
- 1. AGENTSTARTHERE.md
- AGENTGUIDE.md
- GETSTARTED.md
- docs/human/setup/AGENTCOLDSTARTSMOKETEST.md
- MODE_POLICY.md
标准冒烟测试
在仓库根目录执行:
powershell
python Setup\preparesmoketest.py --config Setup\examples\smoke-test-inputpng-1.json
python Setup\rundrawjob.py --config Setup\examples\smoke-test-inputpng-1.json
python Setup\execute_drawdsl.py --config Setup\examples\smoke-test-inputpng-1.json --round 1 --save-final
预期输出:
- - OutputPreview/smoke-inputpng-1/round-01.png
- OutputEditable/1smoketest_final.vsdx
路由规则
在 DiagForge 内部工作时:
- - 如果问题是特定轮次的,保留在审查工件中
- 如果问题看起来是结构性的但仍需验证,撰写提案
- 如果已经是可复用的经验,提升为课程
- 如果共享修复方案明确,直接修补对应的图层
后续步骤
请参阅:
- - README.md
- CONTRIBUTING.md
- docs/architecture/FEEDBACKPROMOTIONLOOP.md