deep-research

Generates cited, multi-source research reports using a filesystem-backed, resumable workflow.

Updated Jun 19, 2026
One-click install
npx skills add https://github.com/MuhammadUA/Axe --skill deep-research-muhammadua
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: deep-research
Source: https://github.com/MuhammadUA/Axe/tree/main/.kortix/opencode/skills/GENERAL-KNOWLEDGE-WORKER/deep-research
Command: npx skills add https://github.com/MuhammadUA/Axe --skill deep-research-muhammadua

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill eliminates the burden of disorganized, uncited research by providing a systematic, evidence-based workflow to produce thorough, source-backed reports on any topic, saving hours of manual effort and ensuring scientific rigor.

Core Features & Use Cases

  • Systematic Multi-Source Investigation: Decomposes research questions into sub-queries, searches academic databases, government sources, and peer-reviewed literature, and cross-references findings for accuracy.
  • Context-Efficient Workflow: Uses the filesystem as working memory to store scraped content and notes, keeping the LLM context lean and making research resumable and searchable.
  • Use Case: If you need a literature review on the efficacy of mindfulness-based stress reduction, this Skill will compile all relevant studies, extract key findings, resolve conflicting evidence, and generate a fully cited report with confidence levels for each claim.

Quick Start

Use the deep-research skill to generate a cited report on the current state of quantum computing error correction research.

Frequently Asked Questions about deep-research

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

FAQPage Schema
How do I generate a cited literature review without exceeding the LLM context window?

To generate a cited literature review without exceeding the LLM context window, this Skill uses a filesystem-backed workflow that stores scraped content and extracted notes to disk, keeping the context lean and research resumable.

What is the best way to fact-check and cross-reference multiple academic sources?

The best way to fact-check academic sources is a systematic workflow that decomposes research questions into sub-queries, cross-references findings from multiple databases, and resolves conflicting evidence to generate fully cited reports with confidence levels.

Can I resume an evidence synthesis task if my research session is interrupted?

Yes, you can resume evidence synthesis tasks because the workflow operates using the filesystem as working memory, storing scraped content, notes, and source metadata to disk for searchable and context-efficient research operations.

Does this multi-source research workflow require any specific external dependencies or components?

No specific external dependencies or components are required to use this multi-source research workflow, as it operates independently to decompose queries, extract notes, and compile evidence-based reports.

How does systematic investigative research handle conflicting evidence from peer-reviewed literature?

Systematic investigative research handles conflicting evidence by cross-referencing findings from peer-reviewed literature, resolving discrepancies during evidence synthesis, and assigning confidence levels to each claim in the final cited report.