deep-research

Orchestrate a six-phase literature review producing structured notes and a final report.

Updated Apr 23, 2026
One-click install
npx skills add https://github.com/Embers-of-the-Fire/agent-research-skills-opencode --skill deep-research-embers-of-the-fire
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: deep-research
Source: https://github.com/Embers-of-the-Fire/agent-research-skills-opencode/tree/main/.opencode/skills/deep-research
Command: npx skills add https://github.com/Embers-of-the-Fire/agent-research-skills-opencode --skill deep-research-embers-of-the-fire

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires PyMuPDF, and includes scripts (resource) and references (resource) components.

What problem does it solve?

Conducts structured, six-phase literature reviews to produce organized notes, a curated paper database, and a synthesized final report, enabling reproducible research workflows.

Core Features & Use Cases

  • Phase-driven workflow that outputs phase-specific artifacts (frontier.md, survey.md, deep_dive.md, code_repos.md, synthesis.md, gaps.md, report.md, references.bib) in an output directory.
  • Automated note extraction, paper database management, and BibTeX generation to support citation-rich storytelling.
  • Use Case: A team performs a comprehensive survey of a topic, then writes a publishable synthesis with traceable sources.

Quick Start

Run the six-phase workflow using the provided scripts to move from frontier to final report.

Frequently Asked Questions about deep-research

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

FAQPage Schema
How do I automate a literature review and generate a report with traceable sources?

Automate a literature review by executing a phase-based workflow that outputs structured notes, a curated paper database, and a synthesized final report. This enforces phase gates to ensure reproducible research with traceable sources.

What is the best way to manage a paper database and produce BibTeX citations for an academic research report?

Manage a paper database and produce BibTeX citations by using an automated literature review workflow. It generates a references.bib file alongside phase-specific notes to support citation-rich storytelling and traceable sources.

How does a phase-based workflow structure work for conducting deep-dive academic research analysis?

A phase-based workflow structures academic research by guiding six distinct phases: frontier discovery, landscape survey, deep-dive analysis, open-source mapping, synthesis, and final compilation. Each phase outputs specific artifacts to a reproducible directory structure.

Can I use this literature review workflow for frontier discovery and open-source mapping?

Yes, you can use this workflow for frontier discovery and open-source mapping. The six-phase orchestration explicitly supports these stages, generating dedicated artifacts like frontier.md and code_repos.md to document your findings.

Do I need PyMuPDF to run the deep-research literature review workflow?

Yes, you need PyMuPDF to run this literature review workflow. It is a required dependency for the Skill to execute its automated note extraction and phase-based research orchestration successfully.

What are the limitations of using an automated literature review workflow for academic research?

The workflow relies on OpenCode scripts in a specific directory and requires PyMuPDF. It enforces strict phase gates, meaning you must complete each stage sequentially to generate the structured artifacts and final report.