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PythonReactSEOPDF
GitHub Skill

internet-research-orchestrator

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.

ahmedibrahim085☆ 0 Étoiles du dépôt0 Forks du dépôt

Installation

Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.

Voir la source ↗Guides

Instructions

Fonctions et usage

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.

Démarrage rapide

Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.

Guides ↗

Exemples

Consultez les exemples du dépôt source.

Voir la source ↗

Historique source

Date d’indexation
2026-01-21
Mise à jour de l’index
2026-01-26
Branch
main

Les dates concernent ce répertoire. Consultez le dépôt pour l’historique du code.

GitHub ↗

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