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orchestrate

Provide reusable orchestration primitives for OMCR research engine workflows.

30|8|Updated May 10, 2026

Search Tags:#state management #orchestration #research automation #agent dispatch #iterative loops #academic workflow #omcr

Ready to run

npx skills add https://github.com/youngeun1209/oh-my-claudecode-research --skill orchestrate-youngeun1209

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: orchestrate
Source: https://github.com/youngeun1209/oh-my-claudecode-research/tree/main/skills/orchestrate
Command: npx skills add https://github.com/youngeun1209/oh-my-claudecode-research --skill orchestrate-youngeun1209

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill eliminates the need for OMCR research engines to reimplement common orchestration logic, ensuring consistent state handling, agent dispatch, evaluation, and looping behavior across all research workflows without duplicated code.

Core Features & Use Cases

4 Reusable Primitives: Provides state-read, dispatch, evaluate, and loop primitives that handle core orchestration tasks for OMCR engines.
Consistent Safety Guardrails: Enforces serial execution, iteration caps, budget limits, and atomic state writes across all engines that use the primitives.
Use Case: Engines like /iterate-revision, /literature-sweep, and /supervisor-drive compose these primitives to implement their workflows instead of writing custom orchestration code from scratch.

Quick Start

Import the relevant phase files from the orchestrate skill when building a new OMCR research engine to reuse standard orchestration logic without custom implementation.

Frequently Asked Questions about orchestrate

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

FAQPage Schema

How do I handle state management and agent dispatch for academic research automation without duplicating code?▼

Reusable orchestration primitives handle state management and agent dispatch, eliminating duplicated logic across OMCR research engines. This enforces consistent serial execution, iteration caps, and budget limits.

What is the best way to implement iterative loops with budget limits for academic workflows?▼

Using orchestration primitives that execute iterative loops with built-in budget and iteration safeguards is the best way. This protects atomic state writes and standardizes loop behavior across all research engines.

How do I build a literature sweep workflow that composes standard orchestration logic?▼

Compose literature sweep workflows by importing phase files from the orchestrate skill. This provides standard state-read, dispatch, evaluate, and loop primitives instead of writing custom orchestration code from scratch.

Can I use these orchestration primitives for research engine revision and reviewer response workflows?▼

Yes, the orchestration primitives support all OMCR engine development scenarios including revision, reviewer response, figure generation, outline expansion, and supervisor drive workflows. They ensure consistent state handling across these varied academic tasks.

Do I need to write custom evaluation logic for each new agent dispatch workflow?▼

No, you do not need custom evaluation logic. The orchestrate skill provides a reusable evaluate primitive that handles verdict rule application and consistent evaluation behavior across all OMCR research engines.