passto-desk

Convert plain text discussions into a shared Excalidraw workbench with a v3 domain artifact.

Updated Apr 27, 2026
One-click install
npx skills add https://github.com/Handy369/passto-pi-frame --skill passto-desk
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: passto-desk
Source: https://github.com/Handy369/passto-pi-frame/tree/main/extensions/passto-desk/skills/passto-desk
Command: npx skills add https://github.com/Handy369/passto-pi-frame --skill passto-desk

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

passto-desk fixes the disconnect between free-form discussion and durable shared collaboration by forcing conversations to be externalized into a structured, multi-layer workbench that both agents and humans can iteratively modify.

Core Features & Use Cases

  • Four-phase workflow: converts discussion into semantic objects/relations → structural view → visual mapping → Excalidraw scene, ensuring stable roundtrips and consistent evolution.
  • Shared collaboration backbone: produces a v3 domain model (passto-desk-domain-json/v3) that supports continuous updates instead of one-off drawings.
  • Readability-first outputs: generates a minimal, human-readable skeleton first, then incrementally improves lane/group/labels/notes when needed.

What problem does it solve?

It is ideal when you need to collaboratively externalize: processes, architecture, dependencies, stages, decisions, and relationships into a shared visual artifact that can be safely edited over multiple turns.

Quick Start

Ask the AI to use passto-desk to create a shared workbench from your discussion, starting with a minimal skeleton of the main flow and key dependencies.

Frequently Asked Questions about passto-desk

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I turn a chat discussion into a shared Excalidraw workbench?▼

To turn a chat into a shared workbench, passto-desk models discussion semantics, structures views, maps to visuals, and produces a round-trippable domain v3 artifact for Excalidraw. It generates a minimal human-readable skeleton first, then incrementally improves lanes and labels.

What is the best way to collaboratively map architecture visualization and workflow dependencies?▼

Collaborative mapping of architecture visualization works best by externalizing relationships into structured, multi-layer visual artifacts. This Skill forces chats into a semantic-to-visual pipeline, ensuring stable roundtrips and consistent evolution of workflow dependencies across multiple turns.

Can I use Excalidraw for multi-turn collaborative editing of complex decision stages?▼

Yes, Excalidraw supports multi-turn collaborative editing when paired with a structured domain v3 model. It safely handles iterative modifications of decision dependencies by generating a semantic backbone that both agents and humans can continuously update.

How does semantic modeling transform plain text into a visual mapping scene?▼

Semantic modeling transforms plain text by extracting objects and relations, structuring them into views, and mapping them to a visual scene. This four-phase pipeline ensures readability-first outputs with controlled runtime imports favoring structured edges, lanes, and notes.

Does collaborative workflow mapping support round-trippable domain JSON outputs?▼

Yes, collaborative workflow mapping supports round-trippable domain JSON v3 outputs. The generated artifact acts as a shared collaboration backbone, allowing continuous updates and safe editing rather than producing one-off, static drawings.

When should I not use a shared workbench map for process visualization?▼

You should not use a shared workbench map for one-off questions or simple processes that lack object relationships and decision dependencies. It is designed for multi-turn collaboration where architecture, stages, and workflows require iterative refinement.