claude-scholar

mcp
SUMMARY

Semi-automated research assistant for academic research and software development. Supports Claude Code, OpenCode, and Codex CLI across ideation, coding, experiments, writing, and publication.

README.md
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Language: English | 中文

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

  • 2026-03-18: Results reporting, writing memory, and workflow cleanup — split post-experiment work into results-analysis for strict statistics, real scientific figures, analysis-report / stats-appendix / figure-catalog, and results-report for decision-oriented post-experiment reports with Obsidian write-back; removed the redundant data-analyst entrypoint, made /analyze-results the default one-shot command for analysis + report generation, introduced a global paper-miner writing memory with the new /mine-writing-patterns command, wired ml-paper-writing and review-response to read that shared memory, refreshed the README around human-centered semi-automation, and updated the project logo.
  • 2026-03-17: Obsidian project knowledge base — filesystem-first project knowledge base with project import, repo-bound auto-sync, durable knowledge routed across Papers / Knowledge / Experiments / Results / Writing, round-level experiment reports stored under Results/Reports/, and no MCP requirement.
  • 2026-02-26: Zotero MCP Web API mode — remote Zotero access, DOI/arXiv/URL import, collection management, item updates, and safer setup guidance across Claude Code, Codex CLI, and OpenCode.
View older changelog
  • 2026-02-25: Codex CLI support — added codex branch supporting OpenAI Codex CLI with config.toml, 40 skills, 14 agents, and sandbox security
  • 2026-02-23: Added setup.sh installer — backup-aware incremental updates for existing ~/.claude, auto-backup settings.json, additive hooks/mcpServers/plugins merge
  • 2026-02-21: OpenCode support — Claude Scholar now supports OpenCode as an alternative CLI; switch to the opencode branch for OpenCode-compatible configuration
  • 2026-02-20: Bilingual config — translated CLAUDE.md to English for international readability; added CLAUDE.zh-CN.md as Chinese backup; Chinese users can switch with cp CLAUDE.zh-CN.md CLAUDE.md
  • 2026-02-15: Zotero MCP integration — added /zotero-review and /zotero-notes commands, updated research-ideation skill with Zotero integration guide, enhanced literature-reviewer agent with Zotero MCP support for automated paper import, collection management, full-text reading, and citation export
  • 2026-02-14: Hooks optimization — restructured security-guard to two-tier system (Block + Confirm), skill-forced-eval now groups skills into 6 categories with silent scan mode, session-start limits display to top 5, session-summary adds 30-day log auto-cleanup, stop-summary shows separate added/modified/deleted counts; removed deprecated shell scripts (lib/common.sh, lib/platform.sh)
  • 2026-02-11: Major update — added 10 new skills (research-ideation, results-analysis, citation-verification, review-response, paper-self-review, post-acceptance, daily-coding, frontend-design, ui-ux-pro-max, web-design-reviewer), 7 new agents, 8 research workflow commands, 2 new rules (security, experiment-reproducibility); restructured CLAUDE.md; 89 files changed
  • 2026-01-26: Rewrote all Hooks to cross-platform Node.js; completely rewrote README; expanded ML paper writing knowledge base; merged PR #1 (cross-platform support)
  • 2026-01-25: Project open-sourced, v1.0.0 released with 25 skills (architecture-design, bug-detective, git-workflow, kaggle-learner, scientific-writing, etc.), 2 agents (paper-miner, kaggle-miner), 30+ commands (including SuperClaude suite), 5 Shell Hooks, and 2 rules (coding-style, agents)

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.
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

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.

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.

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.

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

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:

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


For data science, AI research, and academic writing.

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

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