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Litbase

OrganizationPopular
aipoch
litbase

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

Overview

Publisheraipoch
Repositorymedical-research-skills
Skill namelitbase
Stars
1.9K
Forks
188
Bundled files
43
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 43 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by aipoch on GitHub. Read the source before you install it.

Installation

Install the Litbase AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/aipoch/medical-research-skills/tree/main/awesome-med-research-skills/Evidence%20Insight/litbase
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Use it in TypingMind

Enable Litbase in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Litbase on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Litbase is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Source: https://github.com/aipoch/medical-research-skills

LitBase

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.


Quick Start

Step 1 — Edit config.json with your research folder path:

json
{
  "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.


Commands

CommandWhen to useWhat it does
/setupFirst useGuided research profile setup; auto-configures environment
/feedDailyUpdates search terms → searches Semantic Scholar → recommends papers
/readPer paperSubmit a PDF path, DOI, or abstract → generates 4-section structured note
/discuss [keyword]Deep diveLocate a paper note by author/title/keyword and discuss; auto-records insights
/recapWeekly reviewReading overview, framework completeness map, next-step recommendations
/updateDirection shiftSync research direction changes to memory and search terms
/syncMaintenanceCross-document consistency check; literature integrity audit
/proposeProposal stageSynthesizes reading notes into a Research Foundation Document (RFD) for downstream protocol design

Note Structure

Each paper analysis is structured in four sections:

SectionContent
I. Paper WeightJournal/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 HighlightsMethodological innovation / critique of systemic problems / significance of the research object
III. Transferable ElementsTheory 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 PaperLiterature review positioning, suggested citation phrases (English), methodological precedent, research motivation

Research Foundation Document (RFD)

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.


Capability Tiers

LitBase adapts to its runtime environment automatically:

TierEnvironmentPDF readingPaper searchNotes storageState persistence
AWeb Claude, any LLM chatNative uploadWebSearch / WebFetchArtifact outputSession card (paste at session start)
BManus, file-capable agentsClaude Read toolWebFetch → S2 APIFile systemMEMORY.md
COpenClaw / Claude CodeClaude Read tool (+ optional pdftotext)WebFetch → S2 API (+ optional Python)File systemClaude persistent memory

Dependencies

DependencyPurposeRequired?
Python (stdlib)Runs paper search and metadata scriptsOptional — WebFetch fallback available
pdftotext (poppler)PDF text extractionOptional — Claude native PDF reading available
Claude CodeExecutes skill commandsRequired for Tier C

No API key required for Semantic Scholar. An optional free key raises rate limits.


Literature Integrity

All commands follow the rules in LITERATURE_HARD_RULES.md:

  • No fabricated PMIDs, DOIs, titles, authors, citation counts, or study data.
  • All citations in notes and proposals must be traceable to user-provided papers.
  • Unverifiable claims are labeled explicitly rather than omitted silently.

File Structure

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

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Litbase AI skill do?

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

Why use Litbase on TypingMind?

Because you install it once and use it with any model. Litbase is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Litbase in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/aipoch/medical-research-skills/tree/main/awesome-med-research-skills/Evidence%20Insight/litbase. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Litbase?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Litbase?

As many as you like. As long as a model supports skills, you can use Litbase with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Litbase AI skill free?

Yes. It is published on GitHub by aipoch under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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