sciomc

Orchestrate parallel scientist agents for multi-stage research workflows.

16|3|Updated Mar 12, 2026
One-click install
npx skills add https://github.com/sehoon787/my-claude --skill sciomc-sehoon787
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: sciomc
Source: https://github.com/sehoon787/my-claude/tree/main/skills/omc/sciomc
Command: npx skills add https://github.com/sehoon787/my-claude --skill sciomc-sehoon787

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Orchestrates parallel scientist agents to conduct autonomous, multi-stage research workflows, reducing manual coordination and accelerating insights.

Core Features & Use Cases

  • Breaks research goals into independent stages that can run in parallel.
  • Orchestrates diverse scientist agents, routes outputs, and manages dependencies.
  • Provides AUTO mode for end-to-end execution with progress tracking and reporting.
  • Suitable for literature reviews, codebase analyses, experiment planning, and security assessments.

Quick Start

Provide a research goal and run the auto-enabled workflow with /oh-my-claudecode:sciomc AUTO: <your goal> to start autonomous analysis.

Frequently Asked Questions about sciomc

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

FAQPage Schema
How do I automate multi-stage research workflows with parallel agents?

Multi-stage research workflows are automated by breaking research goals into independent stages that run in parallel, orchestrated by diverse scientist agents that route outputs and manage dependencies for autonomous analysis.

What is parallel scientist orchestration for autonomous research?

Parallel scientist orchestration coordinates multiple agents to conduct research workflows simultaneously, reducing manual coordination and accelerating insights across codebases, datasets, and system designs.

Can I run end-to-end autonomous analysis without manual intervention?

Yes, AUTO mode enables end-to-end autonomous execution with progress tracking and reporting, requiring only an explicit workflow structure and a research goal to start.

What use cases suit parallel research agent orchestration?

Parallel research agent orchestration suits literature reviews, codebase analyses, experiment planning, and security assessments where goals require decomposition, parallel analysis, verification, and synthesis.

Does autonomous research orchestration require explicit workflow structure?

Yes, autonomous research orchestration requires explicit workflow structure to define stages, robust session management to track findings, and AUTO mode activation for end-to-end execution.

What are the limitations of parallel agent orchestration for research?

Parallel agent orchestration requires explicit workflow structure and robust session management to track stages, meaning unstructured or loosely defined research goals may not decompose effectively into parallel independent stages.