Multi-Agent-Research-System
Multi-Agent-Research-System contains 3 collected skills from ahmedibrahim085, with repository-level occupation coverage and site-owned skill detail pages.
Skills in this repository
Orchestrate comprehensive 7-phase RBMAS research for multi-dimensional queries (4+ dimensions). Coordinates multiple specialist agents through SCOPE → PLAN → RETRIEVE → TRIANGULATE → DRAFT → CRITIQUE → PACKAGE methodology. Use for thorough internet research requiring multiple sources, iterative refinement, and quality gates. Triggers - research, investigate, analyze with 4+ distinct dimensions or comprehensive depth requirements.
Orchestrate lightweight parallel internet research (2-4 dimensions). Spawns light-research-researcher workers for each subtopic dimension, coordinates findings, synthesizes final reports. Use for standard research queries with 2-3 distinct angles. Examples - cloud gaming optimization, quantum computing overview, WebRTC performance analysis. Triggers - research, investigate, analyze with multiple aspects.
Orchestrate comprehensive TODAS research for novel/emerging domains (1-7 subagents adaptive). Specializes in unprecedented topics, post-training data, and emerging technologies. Uses adaptive depth-based methodology: straightforward queries (1 agent), standard queries (2-3 agents), complex queries (5-7 agents). Handles depth-first (multiple perspectives), breadth-first (distinct sub-topics), and straightforward investigations. Triggers include "novel", "emerging", "2025", "2026", "unprecedented", "new technology", research on topics that didn't exist during training cutoff.