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deep-research

Enforce a mandatory multi-source research protocol across web, social media, code repositories, videos, and discussions.

13|Updated Apr 5, 2026
Search Tags:#research protocol#subagent orchestration#parallel research#multi-source analysis#source synthesis#comprehensive investigation#mandatory workflow
One-click install
npx skills add https://github.com/sergiocoding96/hermes-multi-agent --skill deep-research-sergiocoding96
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: deep-research
Source: https://github.com/sergiocoding96/hermes-multi-agent/tree/main/skills/deep-research
Command: npx skills add https://github.com/sergiocoding96/hermes-multi-agent --skill deep-research-sergiocoding96

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Ad-hoc research often misses critical data sources, leading to incomplete, biased findings and wasted time redoing work. This Skill enforces a standardized, mandatory research protocol that ensures all relevant public data streams are covered before any investigation begins.

Core Features & Use Cases

  • Mandatory Multi-Source Skill Loading: Requires activating 5 core research skills (web search, YouTube content, X/Twitter, GitHub, Reddit) to capture every major public data source for any topic.
  • Structured Subagent Orchestration: Provides a clear, step-by-step workflow to assign specialized skills to parallel subagents, cutting research time while maintaining depth and accuracy.
  • Use Case: When investigating a new open source project like Hermes Multi-Agent, this protocol ensures you collect official documentation, community sentiment on X and Reddit, GitHub repository activity, tutorial content from YouTube, and general web insights instead of relying on a single source.

Quick Start

Ask the AI to run a deep research investigation on the latest version of the Hermes multi-agent system to compile findings from all available public sources.

Frequently Asked Questions about deep-research

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

FAQPage Schema
How do I ensure comprehensive multi-source research and avoid biased findings?▼

Comprehensive multi-source research requires a mandatory protocol that enforces coverage of web content, social media sentiment, code repository activity, video transcripts, and community discussions. This eliminates incomplete findings by standardizing investigation workflows.

What is the best way to orchestrate parallel research subagents for a new project?▼

The best way to orchestrate parallel research subagents is through a structured workflow that assigns specialized skills to gather data from web search, YouTube, X/Twitter, GitHub, and Reddit simultaneously, cutting research time while maintaining depth and accuracy.

How does cross-source result synthesis work for community discussions and web content?▼

Cross-source result synthesis works by loading mandatory research skills to collect and merge data streams from web insights, social media sentiment, repository activity, video transcripts, and community discussions into a single comprehensive investigation report.

Can I use this research protocol to investigate open source projects across different public data streams?▼

Yes, you can use this mandatory research protocol to investigate open source projects by collecting official documentation, community sentiment on X and Reddit, GitHub repository activity, tutorial content from YouTube, and general web insights instead of relying on a single source.

When do I need a mandatory pre-research protocol for full analysis?▼

You need a mandatory pre-research protocol for full analysis whenever you face investigative tasks prone to missing critical data sources. It enforces standardized skill loading and parallel subagent orchestration to prevent incomplete, biased findings and wasted time redoing work.

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