How are the final research findings verified?

The skill includes a dedicated verification loop that cross-validates findings from parallel stages to check for contradictions, missing connections, or gaps in evidence quality.

How does SciOMC handle large research tasks?

It breaks down goals into 3-7 independent stages and can run up to 20 scientist agents in parallel, ensuring efficient processing of large amounts of data or code.

How does the model routing work?

SciOMC intelligently routes tasks: Claude 3.5 Haiku is used for simple data gathering, Sonnet for standard analysis, and Opus for high-complexity reasoning and architecture validation.

What is SciOMC AUTO mode?

AUTO mode allows the research workflow to run fully autonomously from initial decomposition to the final report generation without requiring manual user checkpoints for each stage.

Can I resume a research session if it is interrupted?

Yes, SciOMC maintains session state in a local .omc directory, allowing you to list all sessions and resume any interrupted research using the 'resume' command.

SciOMC Multi-Agent Research Orchestrator

Name: SciOMC Multi-Agent Research Orchestrator
Author: Yeachan-Heo

byYeachan-Heo

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9,838

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Productivity & Workflow

Orchestrates parallel AI scientist agents to conduct deep, multi-stage research and codebase analysis autonomously.

SciOMC is a powerful research orchestration skill for Claude Code designed to handle complex technical investigations through a structured multi-agent workflow. It decomposes high-level research goals into independent stages, executing them in parallel using specialized scientist agents routed to specific models based on task complexity. The skill manages the entire lifecycle of a research project—from initial hypothesis and evidence collection to cross-validation and final report synthesis—making it an essential tool for deep architectural reviews, security audits, and comprehensive codebase documentation.

Key Features

01Parallel scientist agent execution with concurrency limits

02Structured verification loop to cross-validate findings and resolve conflicts

039,838 GitHub stars

04Smart model routing (Haiku, Sonnet, Opus) based on task complexity

05Comprehensive report generation with evidence tagging and figure embedding

06Fully autonomous AUTO mode for end-to-end research workflows

Use Cases

01Analyzing performance characteristics and comparing architectural patterns

02Documenting complex cross-cutting concerns like authentication flows or error handling

03Performing deep security audits and vulnerability pattern detection across large codebases

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add yeachan-heo/oh-my-claudecode sciomc

For use in Claude.ai and ChatGPT

Download Skill