internet-research-orchestrator

Name: internet-research-orchestrator
Availability: InStock
Author: Ahmed

Coordinate TODAS-based multi-agent research with adaptive subagent allocation and logging.

Updated Nov 19, 2025

Search Tags:#multi-agent #adaptive #dimension-analysis #emerging-domains #TODAS #novelty-detection #research-synthesis

Ready to run

npx skills add https://github.com/ahmedibrahim085/Multi-Agent-Research-System --skill internet-research-orchestrator

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: internet-research-orchestrator
Source: https://github.com/ahmedibrahim085/Multi-Agent-Research-System/tree/main/.claude/skills/internet-research-orchestrator
Command: npx skills add https://github.com/ahmedibrahim085/Multi-Agent-Research-System --skill internet-research-orchestrator

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill coordinates TODAS-based multi-agent research to tackle novel or emerging domains by dynamically allocating 1-7 specialized subagents, enabling depth and breadth coverage with adaptive depth-based strategies.

Core Features & Use Cases

Adaptive agent orchestration: scales from 1 to 7 subagents based on query novelty and complexity.
Depth/Breadth research strategies: supports depth-first, breadth-first, and straightforward investigations with structured plans.
Comprehensive logging and governance: phase-based decision tracing, self-challenge validation, and session logging for reproducibility.
Novel domain focus: optimized for post-training information, unprecedented topics, and rapidly evolving technologies.
Synthesis and reporting: aggregates results from multiple perspectives into a coherent, source-attributed report.

Quick Start

Submit a query characterized by novelty (e.g., "emerging technologies in 2025") to trigger TODAS.
The orchestrator analyzes novelty, determines query type, and allocates 1-7 specialized agents.
Subagents perform research in parallel, results are synthesized, and decisions are logged to project_logs.

Frequently Asked Questions about internet-research-orchestrator

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

FAQPage Schema

How do I research emerging or novel topics that fall outside standard training data?▼

Multi-agent research orchestration automates investigation of post-training or unprecedented domains by dynamically allocating 1-7 specialized subagents to perform depth-first, breadth-first, or straightforward analysis, synthesizing results into a coherent, source-attributed report.

Can I scale research coordination based on how complex or novel a query is?▼

Yes. Adaptive orchestration analyzes query novelty and complexity to determine agent allocation, scaling from 1 to 7 subagents and selecting appropriate investigation strategies—depth-first for deep exploration, breadth-first for broad coverage, or straightforward for direct answers.

How do I ensure research decisions are traceable and reproducible?▼

Phase-based decision logging, self-challenge validation, and session logging to project_logs provide full traceability of orchestration choices, agent assignments, and reasoning steps, enabling reproducibility and governance across research workflows.

What's the best way to coordinate multiple research agents across unfamiliar domains?▼

TODAS-based orchestration coordinates specialized subagents through novelty assessment and phase-based planning, automatically allocating resources, validating findings through self-challenge, and aggregating parallel results into synthesis—optimized for emerging technologies and rapidly evolving fields.

Do I need prior knowledge of a topic to use multi-agent research coordination?▼

No. The orchestrator is designed for novel or emerging domains where prior knowledge is minimal. It performs adaptive depth and breadth analysis, novelty detection, and self-challenge validation to handle unprecedented topics without requiring domain expertise upfront.

Can multi-agent research handle topics that span multiple specialized areas?▼

Yes. Breadth-first and depth-first strategies enable investigation across interdisciplinary domains. Adaptive allocation of 1-7 specialized subagents, combined with comprehensive synthesis, addresses complex queries spanning multiple emerging or novel knowledge areas.