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sciomc

Orchestrate parallel scientist agents for autonomous research workflows with synthesized reporting.

Updated Apr 11, 2026
Search Tags:#automation#workflow#research#agents#reporting#parallel
One-click install
npx skills add https://github.com/Pryma-Tech/iris --skill sciomc-pryma-tech
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: sciomc
Source: https://github.com/Pryma-Tech/iris/tree/main/cli/skills/sciomc
Command: npx skills add https://github.com/Pryma-Tech/iris --skill sciomc-pryma-tech

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Orchestrates parallel scientist agents to tackle complex research goals by automating goal decomposition, task orchestration, and result synthesis, reducing manual coordination overhead and speeding insights.

Core Features & Use Cases

  • Goal decomposition into multiple independent research stages to enable parallel investigations.
  • Parallel scientist invocation with configurable agents and models (haiku, sonnet, opus) to match task complexity.
  • AUTO mode for end-to-end autonomous execution with iterative refinement and progress tracking.
  • Verification and synthesis steps to cross-validate findings and generate comprehensive reports.
  • Session management for resuming interrupted research sessions and preserving findings and state.
  • Use Case: Analyze authentication patterns across the codebase and produce a structured security report.

Quick Start

Provide a research goal to /oh-my-claudecode:sciomc and optionally enable AUTO mode to start an autonomous workflow.

Frequently Asked Questions about sciomc

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

FAQPage Schema
How do I automate parallel research workflows to speed up investigation insights?▼

Decomposing research goals into independent stages enables parallel scientist agents to investigate concurrently. This orchestration reduces manual coordination overhead and synthesizes cross-validated findings into comprehensive structured reports.

What is the best way to decompose a large research goal into independent stages?▼

Breaking a research goal into multiple independent research stages enables parallel investigations. Configurable scientist agents execute these sub-tasks concurrently, allowing iterative refinement and structured findings extraction before final report synthesis.

Can I use different models like haiku, sonnet, or opus for parallel task execution?▼

Yes, parallel scientist invocation supports configurable agents and models including haiku, sonnet, and opus. This allows you to match model complexity and speed to the specific requirements of each parallel research stage.

How do I resume an interrupted autonomous research session without losing findings?▼

Session management capabilities allow you to resume interrupted autonomous research sessions while preserving previous findings and state. This ensures end-to-end autonomous execution via AUTO mode can continue without losing structured progress.

Does autonomous research workflow support cross-validation and verification of findings?▼

Yes, autonomous research workflows include explicit verification and synthesis steps to cross-validate findings across diverse domains. These steps ensure comprehensive report generation by iteratively refining and verifying extracted structured results.

When should I enable AUTO mode for end-to-end autonomous execution?▼

Enable AUTO mode when your research goal requires end-to-end autonomous execution with iterative refinement and progress tracking. It is ideal for complex investigations needing full orchestration from goal decomposition to synthesized reporting.

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