auto-translate

Name: auto-translate
Availability: InStock
Author: Shawn

Derive and visualize workflow execution trees from dependency DAGs and fan-out constraints.

Updated Jun 12, 2026

Search Tags:#automation #workflow #visualization #execution #dag #parallelism

Ready to run

npx skills add https://github.com/shawnroos/auto --skill auto-translate

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: auto-translate
Source: https://github.com/shawnroos/auto/tree/main/skills/auto-translate
Command: npx skills add https://github.com/shawnroos/auto --skill auto-translate

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill eliminates uncertainty in complex automation loops by providing a clear, deterministic preview of how a workflow will execute before it actually runs.

Core Features & Use Cases

Execution Tree Derivation: Maps out parallel waves, fan-out nesting, and substrate routing for any defined workflow.
Topology Preview: Generates a visual ASCII representation of the workflow structure to verify wave order and parallelism.
Use Case: Before running a complex adversarial pair workflow, use this skill to confirm that the dependency graph and fan-out limits are configured correctly to avoid unexpected execution behavior.

Quick Start

Ask the agent to translate the current workflow into an execution tree to preview the wave order and substrate routing.

Frequently Asked Questions about auto-translate

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

FAQPage Schema

How do I visualize a workflow execution tree before running an automation loop?▼

You can visualize a workflow execution tree by deriving its structure from a dependency DAG and fan-out constraints, which generates an ASCII representation to verify parallel waves and substrate routing.

What is workflow fan-out nesting and how does it affect parallel execution?▼

Workflow fan-out nesting defines how parallel tasks branch within an execution tree, determining the wave order and parallel execution limits needed to ensure correct substrate routing during automated loops.

How do I validate dependency DAG topologies for complex automation workflows?▼

Validating dependency DAG topologies involves deriving the execution tree to preview wave order and fan-out nesting, ensuring deterministic structural analysis catches unexpected execution behavior before the workflow runs.

Does this execution tree visualization require any specific workflow modules?▼

Generating an execution tree visualization requires the internal execution_tree and workflow modules to perform deterministic structural analysis on the dependency DAG and fan-out constraints.

Why does my workflow execution tree show unexpected parallel wave ordering?▼

Unexpected parallel wave ordering in an execution tree happens when dependency DAG configurations or fan-out limits are not set correctly, causing incorrect substrate routing during topology preview verification.

When should I not use automated execution tree derivation for workflow verification?▼

Execution tree derivation is not suited for workflows lacking a defined dependency DAG or fan-out constraints, as deterministic structural analysis requires these to map parallel waves and substrate routing accurately.