Agent Visio Use

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name: diagforge-bootstrap description: Bootstrap skill for DiagForge. Use this skill to onboard an agent into the DiagForge GitHub repository, understand the project structure, run the canonical cold-start smoke test, and begin working with the Visio-based drawing loop safely. version: 0.1.2 metadata: openclaw: homepage: https://github.com/qweadzchn/DiagForge requires: bins: - git - python env: - VISIO_BRIDGE_TOKEN

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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:

https://github.com/qweadzchn/DiagForge

Recommended workflow

1. Clone the GitHub repository locally. 2. Read the cold-start entry documents. 3. Run the canonical smoke test before doing open-ended drawing work. 4. Only then move on to real jobs or system improvements.

Clone the repository

git clone git@github.com:qweadzchn/DiagForge.git
cd DiagForge

If SSH is not available, use HTTPS instead.

Read order

Read these files first:

1. AGENT_START_HERE.md 2. AGENT_GUIDE.md 3. GET_STARTED.md 4. docs/human/setup/AGENT_COLD_START_SMOKE_TEST.md 5. MODE_POLICY.md

Canonical smoke test

From the repo root:

python Setup\prepare_smoke_test.py --config Setup\examples\smoke-test-inputpng-1.json
python Setup\run_draw_job.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

Expected outputs:

OutputPreview/smoke-inputpng-1/round-01.png

OutputEditable/1_smoke_test_final.vsdx

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:

README.md

CONTRIBUTING.md

docs/architecture/FEEDBACK_PROMOTION_LOOP.md