sciomc

Orchestrate parallel scientist agents to execute multi-stage research workflows.

Updated Mar 31, 2026
One-click install
npx skills add https://github.com/ClementATH/oh-my-claudecode --skill sciomc-clementath
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: sciomc
Source: https://github.com/ClementATH/oh-my-claudecode/tree/main/skills/sciomc
Command: npx skills add https://github.com/ClementATH/oh-my-claudecode --skill sciomc-clementath

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Automates complex research workflows by coordinating multiple scientist agents to explore hypotheses in parallel, accelerating discovery and ensuring thorough verification.

Core Features & Use Cases

  • Decomposition: break a research goal into independent stages that can run concurrently.
  • Parallel Execution: dispatch multiple agents to run stages in parallel, then synchronize results.
  • Verification & Synthesis: cross-validate findings and generate a comprehensive report; supports AUTO mode for autonomous execution.

Quick Start

Start a new sciomc session with your research goal, e.g., '/oh-my-claudecode:sciomc <goal>'.

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?

Parallel scientist agents decompose complex research goals into independent stages, run investigations concurrently, cross-validate findings, and synthesize comprehensive reports for automated research workflows.

What is the best way to decompose complex research goals into parallelizable stages?

Explicit stage decomposition breaks complex research goals into independent concurrent investigations, dispatching multiple agents to run stages in parallel and synchronizing cross-validated findings into a synthesized report.

Can I run autonomous parallel investigations without manual intervention?

Yes, the optional AUTO mode enables autonomous execution of parallel scientist agent investigations, allowing multi-stage research goals to run without manual intervention while maintaining cross-validation and comprehensive report synthesis.

How does cross-validation work when running parallel research agents?

Cross-validation in parallel research agent orchestration synchronizes independent agent findings and cross-checks them before synthesis, enforcing guardrails for safe, auditable execution and accurate verification of multi-stage research results.

Are there guardrails for safe and auditable execution in automated research orchestration?

Automated research orchestration enforces guardrails for safe, auditable execution through explicit stage decomposition, cross-validation of parallel agent findings, and session management to ensure verified synthesis of comprehensive reports.