command-development

Semi-automated research assistant for academic research and software development, especially for computer science and AI researchers. Supports Claude Code, Codex CLI, and OpenCode across literature review, coding, experiments, reporting, writing, and project knowledge management.

Branch note: the main branch is the Claude Code workflow. If you use Codex CLI, please see the codex branch. If you use OpenCode, please see the opencode branch.

Recent News

• 2026-04-22: Lightweight core instructions — replaced the large always-on CLAUDE.md / AGENTS.md files with compact core instructions, added Chinese companion files, and kept detailed skills, commands, agents, and workflows as on-demand references to reduce default context overhead.
• 2026-04-15: pubfig and pubtab introduced — introduced pubfig, a Python package for publication-grade scientific figures, and pubtab, a Python package for publication-ready tables and Excel↔LaTeX workflows. Together they provide a cleaner production stack for paper figures, benchmark tables, export control, and final artifact QA.
• 2026-04-15: publication-chart-skill integrated into Claude Scholar — wrapped pubfig + pubtab into publication-chart-skill, added the skill to the repository, and connected it to Claude Scholar's analysis and writing boundaries so publication-grade figure/table work now has an explicit handoff route instead of being mixed into general analysis or prose skills.

Quick Navigation

Section	What it helps with
Why Claude Scholar	Understand the project positioning and target use cases.
Core Workflow	See the end-to-end research pipeline from ideation to publication.
Quick Start	Install Claude Scholar in full, minimal, or selective mode.
Getting Started Scenarios	See a few realistic first-use scenarios after installation.
Integrations	Learn how Zotero and Obsidian fit into the workflow.
Primary Workflows	Browse the main research and development workflows.
Supporting Workflows	See the background systems that strengthen the main workflow.
Documentation	Jump to setup docs, configuration, and templates.
Citation	Cite Claude Scholar in papers, reports, or project docs.

Why Claude Scholar

Claude Scholar is not an end-to-end autonomous research system that tries to replace the researcher.

Its core idea is simple:

human decision-making stays at the center; the assistant accelerates the workflow around it.

That means Claude Scholar is designed to help with the heavy, repetitive, and structure-sensitive parts of research — literature organization, note-taking, experiment analysis, reporting, and writing support — while still keeping the key judgments in human hands:

• which problem is worth pursuing,
• which papers actually matter,
• which hypotheses are worth testing,
• which results are convincing,
• and what should be written, submitted, or abandoned.

In other words, Claude Scholar is a semi-automated research assistant, not a “fully automated scientist.”

Who This Is For

Claude Scholar is especially well-suited to:

• computer science researchers who move between literature review, coding, experiments, and paper writing,
• AI / ML researchers who need one assistant workflow spanning ideation, implementation, analysis, reporting, and rebuttal,
• research engineers and graduate students who want stronger workflow structure without giving up human judgment,
• and software-heavy academic projects that benefit from Zotero, Obsidian, CLI automation, and reproducible project memory.

It can still help in other research settings, but its current workflow design is most aligned with computer science, AI, and adjacent computational research.

Core Workflow

• Ideation: turn a vague topic into concrete questions, research gaps, and an initial plan.
• Literature: search, import, organize, and read papers through Zotero collections.
• Paper notes: convert papers into structured reading notes and reusable claims.
• Knowledge base: route durable knowledge into Obsidian across Papers / Knowledge / Experiments / Results / Writing, with round-level experiment reports stored under Results/Reports/.
• Experiments: track hypotheses, experiment lines, run history, findings, and next actions.
• Analysis: generate strict statistics, real scientific figures, and analysis artifacts with results-analysis.
• Reporting: produce a complete post-experiment report with results-report, then write it back into Obsidian.
• Writing and publication: carry stable findings into literature reviews, papers, rebuttals, slides, posters, and promotion.

Quick Start

Requirements

• Claude Code
• Git
• (Optional) Python + uv for Python development
• (Optional) Zotero + Galaxy-Dawn/zotero-mcp for literature workflows
• (Optional) Obsidian for project knowledge-base workflows

Option 1: Full Installation (Recommended)

git clone https://github.com/Galaxy-Dawn/claude-scholar.git /tmp/claude-scholar
bash /tmp/claude-scholar/scripts/setup.sh

Windows: please use Git Bash or WSL to run the installer.

The installer is backup-aware and incremental-update friendly:

• updates repo-managed skills/commands/agents/rules/hooks/scripts/CLAUDE*.md,
• backs up overwritten files to ~/.claude/.claude-scholar-backups/<timestamp>/,
• backs up settings.json to settings.json.bak,
• preserves an existing ~/.claude/CLAUDE.md and installs the repo-managed version as ~/.claude/CLAUDE.scholar.md,
• preserves an existing ~/.claude/CLAUDE.zh-CN.md and installs the repo-managed version as ~/.claude/CLAUDE.zh-CN.scholar.md,
• preserves your existing env, model/provider settings, API keys, permissions, and current mcpServers values,
• adds missing hook entries instead of replacing your entire hook set.

Important CLAUDE note: if you already maintain your own ~/.claude/CLAUDE.md or ~/.claude/CLAUDE.zh-CN.md, review ~/.claude/CLAUDE.scholar.md and ~/.claude/CLAUDE.zh-CN.scholar.md after installation and manually merge the Claude Scholar sections you want into your own files. Do not assume the sidecar files are applied automatically.

To update later:

cd /tmp/claude-scholar
git pull --ff-only
bash scripts/setup.sh

Option 2: Minimal Installation

Install only a small research-focused subset:

git clone https://github.com/Galaxy-Dawn/claude-scholar.git /tmp/claude-scholar
mkdir -p ~/.claude/hooks ~/.claude/skills
cp /tmp/claude-scholar/hooks/*.js ~/.claude/hooks/
cp -r /tmp/claude-scholar/skills/ml-paper-writing ~/.claude/skills/
cp -r /tmp/claude-scholar/skills/research-ideation ~/.claude/skills/
cp -r /tmp/claude-scholar/skills/results-analysis ~/.claude/skills/
cp -r /tmp/claude-scholar/skills/results-report ~/.claude/skills/
cp -r /tmp/claude-scholar/skills/review-response ~/.claude/skills/
cp -r /tmp/claude-scholar/skills/writing-anti-ai ~/.claude/skills/
cp -r /tmp/claude-scholar/skills/git-workflow ~/.claude/skills/
cp -r /tmp/claude-scholar/skills/bug-detective ~/.claude/skills/

Post-install: minimal/manual install does not auto-merge settings.json; copy only the hooks or MCP entries you want from settings.json.template. If you already have your own ~/.claude/CLAUDE.md or ~/.claude/CLAUDE.zh-CN.md, also merge the relevant sections from this repo's Claude files into yours instead of blindly overwriting them.

Option 3: Selective Installation

Copy only the parts you need:

git clone https://github.com/Galaxy-Dawn/claude-scholar.git /tmp/claude-scholar
cd /tmp/claude-scholar

cp hooks/*.js ~/.claude/hooks/
cp -r skills/latex-conference-template-organizer ~/.claude/skills/
cp -r skills/architecture-design ~/.claude/skills/
cp agents/paper-miner.md ~/.claude/agents/
cp rules/coding-style.md ~/.claude/rules/
cp rules/agents.md ~/.claude/rules/

Post-install: selective/manual install does not auto-merge settings.json; copy only the hooks or MCP entries you actually want from settings.json.template. If you already have your own ~/.claude/CLAUDE.md or ~/.claude/CLAUDE.zh-CN.md, merge the relevant sections from this repo's Claude files into yours instead of blindly overwriting them.

Option 4: Plugin Marketplace Installation

Step 1: Install the Plugin

/plugin marketplace add Galaxy-Dawn/claude-scholar
/plugin install claude-scholar@claude-scholar

This auto-loads all skills, commands, agents, and hooks. During installation, you can choose the scope: user (all projects) or project (single project).

Step 2: Install Rules (Required)

Claude Code plugins cannot distribute rules automatically. Install them manually:

git clone https://github.com/Galaxy-Dawn/claude-scholar.git /tmp/claude-scholar

# User-level (all projects)
mkdir -p ~/.claude/rules
cp /tmp/claude-scholar/rules/*.md ~/.claude/rules/

# Or project-level (current project only)
mkdir -p .claude/rules
cp /tmp/claude-scholar/rules/*.md .claude/rules/

Post-install: plugin installation does not auto-load CLAUDE.md or configure settings.json; if you already have your own ~/.claude/CLAUDE.md or ~/.claude/CLAUDE.zh-CN.md, merge the relevant Claude Scholar sections into yours instead of assuming the plugin applies them automatically. If you need Zotero MCP or other integrations, see the Integrations section for manual setup.

Getting Started Scenarios

After installation, the simplest way to begin is to describe your task in natural language. You do not need to memorize the whole system first. Below are a few realistic starting points.

1. Start a New Research Topic

You can say:

Help me start research on [your topic]. I want a literature-grounded plan, the key open questions, and the next concrete steps.

What Claude Scholar will typically help with:

• clarify the topic and narrow the research question,
• identify promising literature directions,
• suggest an initial plan or hypothesis list,
• optionally route the work into Zotero or Obsidian if you use them.

2. Review a Zotero Collection

You can say:

Review my Zotero collection on brain foundation models and summarize the main directions, gaps, and promising next steps.

Typical output:

• paper grouping by theme,
• a short literature synthesis,
• gap analysis,
• candidate research directions worth pursuing next.

3. Analyze Finished Experiment Results

You can say:

Analyze the results in this experiment folder, check what changed across runs, and write a decision-oriented summary.

Typical output:

• metric comparison,
• ablation or error-analysis suggestions,
• a result summary that highlights what is solid, what is weak, and what to run next.

4. Draft a Paper or Rebuttal Section

You can say:

Help me draft the related work section for this project based on the current findings and paper notes.

or:

Help me write a rebuttal draft for these reviewer comments.

Typical output:

• a structured section draft,
• improved argument flow,
• clearer claims and evidence mapping,
• follow-up points that still need support or verification.

Practical Notes

• Start with one concrete task, not a vague request for "everything."
• If you already maintain your own local CLAUDE.md files, merge the Claude Scholar sections you want into them instead of assuming sidecar files apply automatically.
• Zotero and Obsidian are optional, but they become much more useful when you want durable literature notes or project memory rather than one-off chat output.

Platform Support

Claude Scholar is maintained for:

• Claude Code — the primary installation target.
• Codex CLI — supported workflow and documentation are available in this repo ecosystem.
• OpenCode — supported as an alternative CLI workflow.

The top-level workflow is the same: research, coding, experiments, reporting, and project knowledge management.

Integrations

Zotero

Use Zotero when you want Claude Scholar to help with:

• paper import via DOI / arXiv / URL,
• collection-based reading workflows,
• full-text access through Zotero MCP,
• detailed paper notes and literature synthesis.

See MCP_SETUP.md.

Obsidian

Use Obsidian when you want Claude Scholar to maintain a filesystem-first research knowledge base:

• Papers/
• Experiments/
• Results/
• Results/Reports/
• Writing/
• Daily/

See OBSIDIAN_SETUP.md.

Primary Workflows

Complete academic research lifecycle — 7 stages from idea to publication.

1. Research Ideation (Zotero-Integrated)

End-to-end research startup from idea generation to literature management.

Type	Name	One-line explanation
Skill	research-ideation	Turn vague topics into structured questions, gap analysis, and an initial research plan.
Agent	literature-reviewer	Search, classify, and synthesize papers into an actionable literature picture.
Command	/research-init	Start a new topic from literature search to Zotero organization and proposal drafting.
Command	/zotero-review	Review an existing Zotero collection and generate a structured literature synthesis.
Command	/zotero-notes	Batch-read a Zotero collection and create structured paper reading notes.

How it works

• 5W1H Brainstorming: turn a vague topic into structured questions (What / Why / Who / When / Where / How).
• Literature Search & Import: search papers, extract DOI/arXiv/URLs, import them into Zotero, and organize them into themed collections.
• PDF & Full Text: attach PDFs when available, read full text when possible, and fall back to abstract-level analysis when necessary.
• Gap Analysis: identify literature, methodological, application, interdisciplinary, or temporal gaps.
• Research Question & Planning: convert the review into concrete questions, initial hypotheses, and next-step planning.

Typical output

• literature review notes
• structured Zotero collection
• project proposal / research direction draft

2. ML Project Development

Maintainable ML project structure for experiment code and iteration.

Type	Name	One-line explanation
Skill	architecture-design	Define maintainable ML project structure when new registrable components or modules are introduced.
Skill	git-workflow	Enforce branch hygiene, commit conventions, and safer collaboration workflows.
Skill	bug-detective	Debug stack traces, shell failures, and code-path issues systematically.
Agent	code-reviewer	Review modified code for correctness, maintainability, and implementation quality.
Agent	dev-planner	Break complex engineering work into concrete implementation steps.
Command	/plan	Create or refine an implementation plan before coding.
Command	/commit	Prepare a conventional commit for the current changes.
Command	/code-review	Run a focused review on the current code changes.
Command	/tdd	Drive feature work through small, test-backed implementation steps.

How it works

• Structure: use Factory / Registry patterns for new ML components when appropriate.
• Code Quality: keep files maintainable, typed, and config-driven.
• Debugging: inspect stack traces, shell failures, and code-path issues systematically.
• Git Discipline: use branch hygiene, conventional commits, and safer merge/rebase workflows.

3. Experiment Analysis

Strict analysis of experimental results with scientific figures and report-ready artifacts.

Type	Name	One-line explanation
Skill	results-analysis	Produce a strict analysis bundle with rigorous statistics, real scientific figures, and analysis artifacts.
Skill	results-report	Turn analysis artifacts into a complete post-experiment report with decisions, limitations, and next actions.
Command	/analyze-results	Run the full experiment workflow in one shot: strict analysis first, then final report generation.

How it works

• Data Processing: read experiment logs, metrics files, and result directories.
• Statistical Testing: run strict statistical checks such as t-test / ANOVA / Wilcoxon where appropriate.
• Visualization: generate real scientific figures with interpretation guidance, not just vague plotting suggestions.
• Ablation & Comparison: analyze component contribution, performance tradeoffs, and stability.
• Post-Experiment Reporting: turn the analysis bundle into a full retrospective report with conclusions, limitations, and next actions.

Typical output

• analysis-report.md
• stats-appendix.md
• figure-catalog.md
• figures/
• post-experiment summary report in Obsidian Results/Reports/

4. Paper Writing

Systematic academic writing from structure setup to draft refinement.

Type	Name	One-line explanation
Skill	ml-paper-writing	Draft publication-oriented ML/AI papers from repo context, evidence, and literature.
Skill	citation-verification	Check references, metadata, and claim-citation alignment to prevent citation mistakes.
Skill	writing-anti-ai	Reduce robotic phrasing and improve clarity, rhythm, and human academic tone.
Skill	latex-conference-template-organizer	Clean messy conference templates into an Overleaf-ready writing structure.
Agent	paper-miner	Mine strong papers for reusable writing patterns, structure, and venue expectations.
Command	/mine-writing-patterns	Read a paper and merge reusable writing knowledge into the global paper-miner writing memory.

How it works

• Template Preparation: clean conference templates into an Overleaf-ready structure.
• Citation Verification: verify references, metadata, and claim-citation alignment.
• Systematic Writing: draft sections from repo context, experiment evidence, and literature notes.
• Style Refinement: reduce robotic phrasing and improve rhythm, clarity, and tone.

5. Paper Self-Review

Quality assurance before submission.

Type	Name	One-line explanation
Skill	paper-self-review	Audit structure, logic, citations, figures, and compliance before submission.

How it works

• Structure Check: logical flow, section balance, and narrative coherence.
• Logic Validation: claim-evidence alignment, assumption clarity, and argument consistency.
• Citation Audit: reference correctness and completeness.
• Figure Quality: caption completeness, readability, and accessibility.
• Compliance: page limits, formatting, and disclosure requirements.

6. Submission & Rebuttal

Submission preparation and review response workflow.

Type	Name	One-line explanation
Skill	review-response	Structure reviewer comments into an evidence-based rebuttal workflow.
Agent	rebuttal-writer	Draft professional, respectful, and strategically organized rebuttal text.
Command	/rebuttal	Generate a complete rebuttal draft from review comments and evidence.

How it works

• Pre-submission Checks: venue-specific formatting, anonymization, and checklist requirements.
• Review Analysis: classify reviewer comments into actionable categories.
• Response Strategy: decide whether to accept, defend, clarify, or propose new experiments.
• Rebuttal Writing: generate structured, evidence-based responses with professional tone.

7. Post-Acceptance Processing

Conference preparation and research promotion after acceptance.

Type	Name	One-line explanation
Skill	post-acceptance	Support talks, posters, and research promotion after acceptance.
Command	/presentation	Generate presentation structure and speaking guidance for the accepted work.
Command	/poster	Organize the work into poster-ready content and layout guidance.
Command	/promote	Draft public-facing promotion content such as summaries, posts, or threads.

How it works

• Presentation: prepare talk structure and slide guidance.
• Poster: organize content into poster-ready layout and hierarchy.
• Promotion: generate social media, blog, or summary material for broader communication.

Supporting Workflows

These workflows run in the background to strengthen the primary workflows.

Obsidian Project Knowledge Base

Use Obsidian as the durable sink for project knowledge, not just as a note dump.

Type	Name	One-line explanation
Skill	obsidian-project-memory	Maintain the project-level Obsidian knowledge base and decide what durable knowledge should be written back.
Skill	obsidian-project-bootstrap	Initialize an Obsidian knowledge base for a new or existing research project.
Skill	obsidian-research-log	Record daily research progress, plans, ideas, and TODOs into the knowledge base.
Skill	obsidian-experiment-log	Capture experiment setup, run history, outcomes, and follow-up actions in Obsidian.
Command	/obsidian-ingest	Ingest a new Markdown file or folder into the correct place in the knowledge base.
Command	/obsidian-note	Manage a single note lifecycle such as lookup, rename, archive, or purge.
Command	/obsidian-views	Generate or refresh optional Obsidian views such as .base files.

How it works

• bind an existing repo to an Obsidian vault,
• route stable knowledge into Papers / Knowledge / Experiments / Results / Writing, with round-level experiment reports stored under Results/Reports/,
• keep Daily/ and project memory updated conservatively,
• ingest new Markdown files into the correct canonical destination,
• optionally generate extra views and canvases.

Note language configuration

Generated and synced Obsidian notes resolve their language with this priority:

1. project config: .claude/project-memory/registry.yaml -> note_language
2. environment variable: OBSIDIAN_NOTE_LANGUAGE
3. default: en

Note: the file is currently named registry.yaml for historical reasons, but its on-disk format is JSON.

Per-project example:

{
  "projects": {
    "my-project": {
      "project_id": "my-project",
      "vault_root": "/path/to/vault/Research/my-project",
      "note_language": "zh-CN"
    }
  }
}

English and Chinese section headings remain mutually compatible during sync, so older notes in either language can still be updated safely after switching configuration.

Automated Enforcement Workflow

Cross-platform hooks automate routine workflow checks and reminders.

Hooks

• skill-forced-eval.js
• session-start.js
• session-summary.js
• stop-summary.js
• security-guard.js

How it works

• Before prompts: evaluate applicable skills and surface relevant workflow hints.
• At session start: show Git state, available commands, and project-memory context.
• At session end/stop: summarize work and remind the user about minimum maintenance tasks.
• Security: block catastrophic commands and require confirmation for dangerous but legitimate ones.

Knowledge Extraction Workflow

Specialized agents can mine reusable knowledge from papers and competitions.

Type	Name	One-line explanation
Agent	paper-miner	Extract reusable writing knowledge, structure patterns, and venue heuristics from strong papers.
Agent	kaggle-miner	Extract engineering practices and solution patterns from strong Kaggle workflows.

How it works

• extract writing patterns, venue expectations, and rebuttal strategies from papers,
• extract engineering patterns and solution structure from Kaggle workflows,
• feed those insights back into skills and reference material.

Skill Evolution System

Claude Scholar also contains a self-improvement loop for its own skills.

Type	Name	One-line explanation
Skill	skill-development	Create new skills with clear triggers, structure, and progressive disclosure.
Skill	skill-quality-reviewer	Review skills across content quality, organization, style, and structural integrity.
Skill	skill-improver	Apply structured improvement plans to evolve existing skills.

How it works

• create new skills with clear trigger descriptions,
• review them across quality dimensions,
• apply structured improvements and iterate.

Documentation

• MCP_SETUP.md — Zotero/browser MCP setup
• OBSIDIAN_SETUP.md — Obsidian knowledge base workflow
• CLAUDE.md — lightweight Claude Code core instructions
• CLAUDE.zh-CN.md — Chinese companion for the lightweight core instructions
• settings.json.template — optional settings template for hooks/plugins/MCP

Project Rules

Claude Scholar includes project rules for:

• coding style,
• agent orchestration,
• security,
• experiment reproducibility.

These are reflected in the shipped rules and in CLAUDE.md.

Contributing

Issues, PRs, and workflow improvements are welcome.

If you propose changes to installer behavior, Zotero workflows, or Obsidian routing, please include:

• the user scenario,
• the current limitation,
• the expected behavior,
• and any compatibility concerns.

License

MIT License.

Citation

If Claude Scholar helps your research or engineering workflow, you can cite the repository as:

@misc{claude_scholar_2026,
  title        = {Claude Scholar: Semi-automated research assistant for academic research and software development},
  author       = {Gaorui Zhang},
  year         = {2026},
  howpublished = {\url{https://github.com/Galaxy-Dawn/claude-scholar}},
  note         = {GitHub repository}
}

Acknowledgments

Built with Claude Code CLI and enhanced by the open-source community.

References

This project is inspired by and builds upon excellent work from the community:

• everything-claude-code - Comprehensive resource for Claude Code CLI
• AI-research-SKILLs - Research-focused skills and configurations

These projects provided valuable insights and foundations for the research-oriented features in Claude Scholar.

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For data science, AI research, and academic writing.

Repository: https://github.com/Galaxy-Dawn/claude-scholar