Academic Deep Research logo

Academic Deep Research

Community
lxyeternal
academic-deep-research

Transparent, rigorous research with full methodology — not a black-box API wrapper. Conducts exhaustive investigation through mandated 2-cycle research per theme, APA 7th citations, evidence hierarchy, and 3 user checkpoints. Self-contained using native OpenClaw tools (web_search, web_fetch, sessions_spawn). Use for literature reviews, competitive intelligence, or any research requiring academic rigor and reproducibility.

Overview

Publisherlxyeternal
RepositoryMalSkillBench
Skill nameacademic-deep-research
Stars
64
Forks
14
Bundled files
1
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.

  • 1 bundled files

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

  • Open source

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

Installation

Install the Academic Deep Research 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/lxyeternal/MalSkillBench/tree/main/Dataset/Skills/benign/academic-deep-research-pro
  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.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/lxyeternal/MalSkillBench.git /tmp/MalSkillBench
mkdir -p .claude/skills
cp -r /tmp/MalSkillBench/Dataset/Skills/benign/academic-deep-research-pro .claude/skills/academic-deep-research
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Academic Deep Research 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 Academic Deep Research 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 Academic Deep Research 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.

Academic Deep Research 🔬

When to Use

Trigger this skill when the user wants:

  • Deep research, exhaustive analysis, or literature review
  • Multi-source verification and evidence hierarchies
  • Academic-style reports with citations

Required Stop Points

  1. Initial engagement: ask 2–3 clarifying questions and confirm understanding.
  2. Research plan: present themes, steps, and deliverables; wait for approval.
  3. Final report: deliver full narrative report with citations.

Minimum Requirements

  • Two full research cycles per theme.
  • Analyze between every tool call.
  • Multiple sources per claim; contradictions addressed.
  • APA 7th in-text citations and reference list.
  • Narrative-only final report (no lists or tables).

References

  • reference/protocol.md — research phases, tool order, and analysis rules
  • reference/writing-style.md — narrative constraints and phase formatting
  • reference/citations-apa.md — citation rules and examples
  • reference/report-template.md — required report structure
  • reference/error-handling.md — gaps, contradictions, failures
  • reference/quality-standards.md — evidence hierarchy and confidence levels
  • reference/parallel-research.md — sessions_spawn workflow
  • quickref.md — short checklist
  • example.md — sample usage

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 Academic Deep Research AI skill do?

Transparent, rigorous research with full methodology — not a black-box API wrapper. Conducts exhaustive investigation through mandated 2-cycle research per theme, APA 7th citations, evidence hierarchy, and 3 user checkpoints. Self-contained using native OpenClaw tools (web_search, web_fetch, sessions_spawn). Use for literature reviews, competitive intelligence, or any research requiring academic rigor and reproducibility.

Why use Academic Deep Research on TypingMind?

Because you install it once and use it with any model. Academic Deep Research 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 Academic Deep Research in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/lxyeternal/MalSkillBench/tree/main/Dataset/Skills/benign/academic-deep-research-pro. 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 Academic Deep Research?

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 Academic Deep Research?

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

Is the Academic Deep Research AI skill free?

It is published on GitHub by lxyeternal. Check the repository for licensing terms. 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇