claude-scholar — What is it?

Galaxy-Dawn/claude-scholar is a semi-automated research assistant designed to streamline academic research and software development processes, particularly for computer science and AI researchers.

⭐ 3,161 Stars 🍴 285 Forks Python Author: Galaxy-Dawn
Source: per README View on GitHub →

Why it matters

Claude Scholar is gaining attention due to its focus on enhancing productivity for researchers and developers by integrating various research and coding tools, such as Claude Code, Codex CLI, and OpenCode. Its unique approach of augmenting human decision-making with automation addresses the pain points of time-consuming research processes and the need for efficient knowledge management.

Source: Synthesis of README and project traits

Core Features

Integration with Claude Code, Codex CLI, and OpenCode

Supports ideation, coding, experiments, writing, and publication through seamless integration with these tools, providing a comprehensive research and development environment.

Source: per README
Skill-based architecture

Utilizes a skill-based architecture that allows for modular and extensible functionality, enabling users to add or remove features as needed.

Source: per README
Project knowledge management

Incorporates Obsidian for project knowledge management, facilitating human-first navigation and organization of research materials.

Source: per README

Architecture

The architecture is inferred to be modular, with a skill-based approach to functionality. Key components include integration with external tools, a knowledge management system, and a flexible configuration for various research workflows. The code tree indicates a separation into modules such as agents, commands, and setup configurations.

Source: Code tree

Project Knowledge Graph

Knowledge graph: project (center) + core features (inner hexagons) + key dependencies (outer chips) Not enough information.Not enough inf… Integration with Claude Code, Codex CLI, and OpenCodeIntegration with Cl… Skill-based architectureSkill-based archite… Project knowledge managementProject knowledge m… claude-scholar Project Core feature Key dependency

Center: project; inner ring: core feature modules; outer ring: key dependencies. Auto-generated from core_features and tech_stack.key_deps.

Tech Stack

LanguagePythonFrameworkNot enough information.
Not enough information.
Not enough information.
Source: Dependency files + code tree

Quick Start

To install Claude Scholar, run the following command: ./setup.sh For a minimal installation, use: ./setup.sh --minimal For a selective installation, specify the desired components with the --components flag.
Source: README Installation/Quick Start

Use Cases

Claude Scholar is suitable for computer science and AI researchers who require assistance with literature review, coding, experiments, writing, and publication. It is useful in scenarios such as automating research workflows, managing project knowledge, and enhancing productivity in academic research and software development.

Source: README

Strengths & Limitations

Strengths

  • Strength 1: Enhances productivity in academic research and software development.
  • Strength 2: Modular and extensible architecture allows for customization.
  • Strength 3: Integrates with key research and coding tools.

Limitations

  • Limitation 1: The project is still in development and may have bugs or incomplete features.
  • Limitation 2: The complexity of the system may require a learning curve for new users.
Source: Synthesis of README, code structure and dependencies

Latest Release

v1.0.0 (2026-02-25): Initial release with a comprehensive Claude Code configuration for academic research and software development.

Source: GitHub Releases

Verdict

Claude Scholar is a promising project for researchers and developers seeking to automate and streamline their workflows. Its integration of various research and coding tools and its focus on enhancing human decision-making make it a valuable tool for those in the fields of computer science and AI.

Transparency Notice
This page is auto-generated by AI (a large language model) from the following public materials: GitHub README, code tree, dependency files and release notes. Analyzed at: 2026-05-23 00:09. Quality score: 85/100.

Data sources: README, GitHub API, dependency files