meta-orchestrator

Decompose complex tasks into DAG-based workflows for parallel execution and fault-tolerant orchestration.

9|Updated Jun 6, 2026
One-click install
npx skills add https://github.com/youxing-max/Meta-Orchestrator --skill meta-orchestrator-youxing-max
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: meta-orchestrator
Source: https://github.com/youxing-max/Meta-Orchestrator/tree/main/.claude/skills/meta-orchestrator
Command: npx skills add https://github.com/youxing-max/Meta-Orchestrator --skill meta-orchestrator-youxing-max

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

DAG-based workflow orchestration engine that brings OpenSquilla's MetaSkill execution model to Claude Code. You are both the planner AND the runtime -- decompose, dispatch, track, and synthesize.

Core Features & Use Cases

  • Session-Start Mandate: Skill is always active at session start to ensure it remains in context.
  • DAG Decomposition & Execution: Breaks down non-trivial tasks into DAG steps with parallelism and fault tolerance; can reuse existing workflows and automatically re-route on failures.
  • Workflow Planning & Synthesis: Classifies tasks into Tiered complexity (T0-T3) and synthesizes final outputs after all steps complete.

Quick Start

Start a new session and invoke this skill to classify user requests and generate a DAG plan before execution.

Frequently Asked Questions about meta-orchestrator

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

FAQPage Schema
How do I break down complex multi-step tasks for parallel execution?

DAG-based workflow orchestration decomposes complex multi-step tasks into a directed acyclic graph. This allows parallel execution and fault-tolerant scheduling across non-trivial multi-file tasks within Claude Code workflows.

How does fault-tolerant orchestration handle step failures during workflow execution?

Fault-tolerant orchestration automatically re-routes workflows upon step failures. It tracks parallel dispatch and manages recovery to ensure the overall workflow completes without manual intervention.

When do I need DAG planning for multi-file tasks?

DAG planning is needed for non-trivial multi-file tasks requiring structured scheduling and recovery. It classifies task complexity into tiers and generates a directed acyclic graph plan before execution begins.

Can I reuse existing workflows when orchestrating parallel tasks?

Yes, the orchestration engine can reuse existing workflows. It synthesizes final outputs after all parallel steps complete and relies on frontmatter metadata for skill discovery and activation.

What is the best way to synthesize outputs from parallel workflow steps?

Output synthesis combines results from all completed parallel steps into a final output. The orchestrator manages this process after dispatching and tracking the entire directed acyclic graph workflow.

Do I need to manually activate workflow orchestration at session start?

No, the skill is mandated to be active at session start to ensure it remains in context. This allows it to immediately classify user requests and generate a DAG plan for execution.