orchestrate

Name: orchestrate
Availability: InStock
Author: AsiaOstrich

Execute DAG-based task plans with parallel layers and execution_report.json output.

6|1|Updated Mar 4, 2026

Search Tags:#automation #workflow #execution #plan #dag #orchestrate

Ready to run

npx skills add https://github.com/AsiaOstrich/dev-autopilot --skill orchestrate-asiaostrich

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: orchestrate
Source: https://github.com/AsiaOstrich/dev-autopilot/tree/main/.claude/skills/orchestrate
Command: npx skills add https://github.com/AsiaOstrich/dev-autopilot --skill orchestrate-asiaostrich

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Orchestrate multi-task execution plans by coordinating tasks across layered DAG dependencies, enabling reliable parallelism, safety checks, and automated reporting in Claude Code workflows.

Core Features & Use Cases

DAG-based task orchestration with per-layer parallel execution
Validation, safety checks, and optional judge reviews to ensure quality
Automatic generation of execution reports (execution_report.json) for auditing and review

Quick Start

Run the orchestrate workflow by providing a task plan and triggering the DAG-driven executor to process all layers with proper isolation and reporting.

Frequently Asked Questions about orchestrate

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

FAQPage Schema

How do I orchestrate multi-task plans with DAG execution in Claude Code?▼

DAG execution orchestrates multi-task plans by parsing layered dependencies and executing tasks sequentially or in parallel. It coordinates workflow execution automatically, applying safety checks and optional judge reviews to ensure reliable task completion.

What is parallel task execution with dependency-based failure handling?▼

Parallel task execution processes independent tasks simultaneously across DAG layers, while dependency-based failure handling ensures that downstream tasks are safely skipped or halted if their upstream dependencies fail, preventing cascading errors.

How do I automate execution reporting for multi-step workflows?▼

Automated execution reporting generates an execution_report.json file after completing DAG-based task plans. This report provides auditing and review details by capturing the execution status, safety check results, and task outcomes across all layers.

Does DAG-based workflow orchestration work with worktree isolation?▼

Yes, DAG-based workflow orchestration uses worktree isolation to separate per-layer parallel execution environments. This ensures that concurrent tasks operate independently without interfering with each other's files or execution state.

Can I validate task plans before executing a multi-layer workflow?▼

Yes, you can validate task plans before execution. The orchestration workflow applies validation and safety checks to the parsed DAG structure, ensuring that the sequential or parallel task layers are safe to execute.

When should I use DAG-driven orchestration instead of simple sequential task execution?▼

Use DAG-driven orchestration when your multi-task plans contain complex layered dependencies requiring parallel execution, safety checks, or judge reviews. Simple sequential execution lacks the dependency-based failure handling and worktree isolation needed for reliable parallelism.