sciomc

Name: sciomc
Availability: InStock
Author: tiankong0101-byte

Orchestrates parallel research workflows for complex technical analysis and evidence-backed reporting.

Updated May 17, 2026

Search Tags:#research #verification #session management #synthesis #parallel analysis #autonomous workflow

Ready to run

npx skills add https://github.com/tiankong0101-byte/skills-registry --skill sciomc-tiankong0101-byte

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: sciomc
Source: https://github.com/tiankong0101-byte/skills-registry/tree/main/skills/oh-my-claudecode/skills/sciomc
Command: npx skills add https://github.com/tiankong0101-byte/skills-registry --skill sciomc-tiankong0101-byte

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill coordinates complex research by splitting a broad question into multiple independent investigations, running them in parallel, and then verifying and synthesizing the results into one coherent answer.

Core Features & Use Cases

Parallel decomposition and execution: Breaks a research goal into 3 to 7 stages and runs specialized scientist agents concurrently.
Verification and synthesis: Cross-checks findings for contradictions, gaps, and evidence quality before producing a final report.
AUTO research mode: Supports autonomous iteration, session persistence, cancellation, resumption, and structured report generation for long-running analysis.
Use case: Analyze a codebase’s authentication flow, compare competing implementation approaches, or produce an evidence-backed technical research report.

Quick Start

Use the sciomc skill to research the performance characteristics of sorting algorithms with parallel investigation and verified findings.

Frequently Asked Questions about sciomc

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

FAQPage Schema

What is parallel research workflow decomposition for complex technical analysis?▼

Parallel research workflow decomposition splits a broad technical analysis goal into 3 to 7 independent investigations, runs specialized agents concurrently, and syntheses verified findings into one coherent, evidence-backed report.

How do I run parallel research agents to compare competing implementation approaches?▼

To compare competing implementation approaches, you initiate the skill to run parallel research agents that investigate each approach concurrently, cross-check findings for contradictions, and synthesize the results into a comparative report.

Can I use autonomous AUTO mode for long-running codebase investigations with session persistence?▼

Yes, AUTO mode supports autonomous iteration for long-running codebase investigations by providing session persistence, allowing you to cancel, resume, and generate structured reports for multi-stage research tasks.

Does this approach verify research findings and cross-validate evidence quality before synthesis?▼

Yes, the workflow cross-checks parallel investigation findings for contradictions, gaps, and evidence quality, applying confidence-tagged findings and cross-validation before producing a final synthesized report.

What are the limitations of using autonomous research workflows for architecture review?▼

Autonomous research workflows for architecture review require multiple concurrent investigation stages and structured stage tracking, making them less suited for simple, single-step queries that do not benefit from parallel decomposition and synthesis.

Is sciomc the best way to orchestrate multi-stage research tasks with evidence-backed reporting?▼

Sciomc is designed for multi-stage research tasks, orchestrating parallel scientist agents that cross-validate evidence and synthesize confidence-tagged findings into a structured, evidence-backed technical research report.