Transform lengthy academic papers into concise, structured 250-word abstracts.
日本語の概要は準備中です。原文の説明を表示しています。
Academic paper reading and research development system for biomedical researchers. Finds papers via Semantic Scholar, reads with structured notes, tracks discussion insights, and synthesizes literature into a Research Foundation Document (RFD) for downstream protocol design skills. 8 commands: /setup /feed /read /discuss /recap /update /sync /propose
インストールする前に、エージェントに与えられる指示の中身を確認できます。
An academic paper reading and research development system running inside Claude Code (or any compatible agent environment). Built for biomedical researchers who want to find papers, build structured reading notes, track discussion insights, and ultimately synthesize their literature base into a research proposal.
Paper source: Semantic Scholar — free, no login required, 200M+ papers across all disciplines.
Step 1 — Edit config.json with your research folder path:
{
"data_dir": "/path/to/your/research/folder",
"s2_api_key": "optional — leave empty to use free tier",
"mode": "auto"
}
Step 2 — Open this folder in Claude Code, then type /setup.
The setup command configures everything automatically — no terminal commands needed.
| Command | When to use | What it does |
|---|---|---|
/setup | First use | Guided research profile setup; auto-configures environment |
/feed | Daily | Updates search terms → searches Semantic Scholar → recommends papers |
/read | Per paper | Submit a PDF path, DOI, or abstract → generates 4-section structured note |
/discuss [keyword] | Deep dive | Locate a paper note by author/title/keyword and discuss; auto-records insights |
/recap | Weekly review | Reading overview, framework completeness map, next-step recommendations |
/update | Direction shift | Sync research direction changes to memory and search terms |
/sync | Maintenance | Cross-document consistency check; literature integrity audit |
/propose | Proposal stage | Synthesizes reading notes into a Research Foundation Document (RFD) for downstream protocol design |
Each paper analysis is structured in four sections:
| Section | Content |
|---|---|
| I. Paper Weight | Journal/conference rank, IF, database indexing (SSCI/Scopus/etc.), Q-rank; each author's institution, position, h-index; citation count and yearly average; overall assessment |
| II. Paper Highlights | Methodological innovation / critique of systemic problems / significance of the research object |
| III. Transferable Elements | Theory framework, method details, conceptual tools — each tagged to which part of the user's own paper it can support |
| IV. How to Use in Your Paper | Literature review positioning, suggested citation phrases (English), methodological precedent, research motivation |
The /propose command generates an RFD — a structured synthesis of the user's accumulated literature base. It serves as a standardized upstream input to any downstream protocol design skill.
RFD sections: Study Population & Clinical Context → Focused Research Question (P/E/C/O/D/T) → Theoretical Framework & Mechanistic Basis → Methodological Precedents → Identified Research Gaps → Literature Source Index.
All citations in the RFD are sourced exclusively from the user's confirmed reading list. No fabricated references.
LitBase adapts to its runtime environment automatically:
| Tier | Environment | PDF reading | Paper search | Notes storage | State persistence |
|---|---|---|---|---|---|
| A | Web Claude, any LLM chat | Native upload | WebSearch / WebFetch | Artifact output | Session card (paste at session start) |
| B | Manus, file-capable agents | Claude Read tool | WebFetch → S2 API | File system | MEMORY.md |
| C | OpenClaw / Claude Code | Claude Read tool (+ optional pdftotext) | WebFetch → S2 API (+ optional Python) | File system | Claude persistent memory |
| Dependency | Purpose | Required? |
|---|---|---|
| Python (stdlib) | Runs paper search and metadata scripts | Optional — WebFetch fallback available |
| pdftotext (poppler) | PDF text extraction | Optional — Claude native PDF reading available |
| Claude Code | Executes skill commands | Required for Tier C |
No API key required for Semantic Scholar. An optional free key raises rate limits.
All commands follow the rules in LITERATURE_HARD_RULES.md:
litbase/
├── SKILL.md ← skill manifest (this file)
└── core/ ← open this folder in Claude Code
├── CLAUDE.md ← project rules (auto-loaded)
├── README.md
├── config.json ← user config (data_dir, API key, mode)
├── search_config.json ← search terms (maintained by Claude)
├── settings.local.json ← Claude Code permissions template
├── install.sh ← optional manual setup script
├── commands/
│ ├── setup.md
│ ├── feed.md
│ ├── read.md
│ ├── discuss.md
│ ├── recap.md
│ ├── update.md
│ ├── sync.md
│ └── propose.md
├── references/
│ ├── LITERATURE_HARD_RULES.md
│ └── SESSION_CARD_TEMPLATE.md
├── scripts/
│ ├── recommend.py ← optional: Semantic Scholar search
│ ├── lookup_paper.py ← optional: paper metadata query
│ └── rename_pdfs.py ← optional: PDF batch rename
├── memory/
│ └── MEMORY.md
└── notes/
└── WORKFLOW.md
data_dir/ ← path set in config.json
notes/
reading_list.md
YYYY-MM-DD/
recommendations.md
Author_Year_Keywords/
Author_Year_Keywords.pdf
Author_Year_Keywords.md
recaps/
YYYY-MM-DD_recap.md
proposal/
YYYY-MM-DD_RFD.md
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Transform lengthy academic papers into concise, structured 250-word abstracts.
日本語の概要は準備中です。原文の説明を表示しています。
Precision editing tool that reduces abstract word count through intelligent compression techniques, maintaining scientific rigor while meeting strict journal and conference requirements.
日本語の概要は準備中です。原文の説明を表示しています。
Refines long medical academic texts into SCI-style unstructured Chinese and English abstracts; use when you need to condense drafts/reports/summaries into bilingual abstracts and generate Summary_Report.md.
日本語の概要は準備中です。原文の説明を表示しています。
Generates submission-ready Elsevier/SCI Highlights from manuscript text or extracted PDF/DOCX/TXT content. Use when a user needs 3-5 concise, evidence-grounded highlight bullets for a research paper, review, meta-analysis, case report, or bioinformatics manuscript.
日本語の概要は準備中です。原文の説明を表示しています。
Generates complete FAERS pharmacovigilance study designs for multi-drug or class-level safety comparison inside one predefined SOC or AE family using active comparators, disproportionality analysis, subgroup characterization, and reviewer-facing evidence control.
日本語の概要は準備中です。原文の説明を表示しています。
Analyze data with `adme-property-predictor` using a reproducible workflow, explicit validation, and structured outputs for review-ready interpretation.
日本語の概要は準備中です。原文の説明を表示しています。