Transparent, rigorous research with full methodology β 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.
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What Academic Deep Research can do for your AI workflow
Transparent, rigorous research directly from your Claude conversation
Works across Claude, Cursor, OpenClaw β install once, use everywhere
Trusted by 17,303+ developers worldwide
One-command installation β no complex setup required
Combine with other skills to build powerful multi-step AI workflows
Try these prompts with your AI agent after installing Academic Deep Research
Help me get started with Academic Deep Research
Explains what Academic Deep Research does, walks through the setup, and runs a quick demo based on your current project
Use Academic Deep Research to transparent, rigorous research with full methodology β not a black-...
Invokes Academic Deep Research with the right parameters and returns the result directly in the conversation
What can I do with Academic Deep Research in my data & analytics workflow?
Lists the top use cases for Academic Deep Research, with example commands for each scenario
Guides & tutorials for AI skills
Academic Deep Research extends your AI assistant with the ability to transparent, rigorous research with full methodology β 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. Rather than leaving your conversation to handle this manually, you can ask your Claude agent directly β and it will take care of the task end-to-end, using Academic Deep Research as its underlying capability.
Academic Deep Research works across Claude, Cursor, OpenClaw through the Model Context Protocol (MCP) β an open standard that lets AI clients share tools and skills without lock-in. Because MCP is platform-agnostic by design, you install Academic Deep Research once and it becomes available across all your AI clients. Whether you're working in Claude for focused sessions or Cursor for integrated workflows, the skill behaves consistently.
Getting started with Academic Deep Research takes about two minutes. Place the skill at `~/.claude/skills/academic-deep-research/` (personal, all projects) or `.claude/skills/academic-deep-research/` (project-specific), then restart your AI client. From that point, typing `/academic-deep-research` in any conversation activates it, or the AI will use it on its own when it detects a relevant request.
With 17,303 installs, Academic Deep Research has built a substantial following in the Data & Analytics space. That install count reflects consistent demand from developers and teams who've found it genuinely useful. The source code is open on GitHub β you can inspect it, contribute fixes, or fork it to adapt the skill for your specific setup. Like all skills on DiscoverAISkills, it is free to install and use. The broader AI skills ecosystem continues to expand as developers contribute new capabilities across categories like developer tools, data analysis, writing, automation, and more.
Place the skill folder at ~/.claude/skills/academic-deep-research/ for personal use (all projects), or .claude/skills/academic-deep-research/ for project-specific use. Restart your AI client, then invoke with /academic-deep-research or let the AI discover it automatically.
Academic Deep Research supports Claude, Cursor, OpenClaw. It integrates seamlessly with these AI platforms to extend their capabilities.
Academic Deep Research is free to install. Check the repository for licensing information.
Transparent, rigorous research with full methodology β 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.
Select your agent
Option 1: Install via CLI (recommended)
Recommended (no pre-install needed)
npx clawhub@latest --dir ~/.claude/skills install academic-deep-researchOr via clawhub CLI (if already installed)
clawhub --dir ~/.claude/skills install academic-deep-researchβ οΈ Requires Node.js 18+. No Node? Use Option 2 below to download the ZIP instead. Install Node.js β
Option 2: Manual install (no Node required)
Download the ZIP, extract it, and place the folder at the path below. Restart your agent to activate.
Install path
~/.claude/skills/academic-deep-research/π‘Extract and place the folder at the path above, then restart your agent.
Automate my data & analytics tasks using Academic Deep Research
Identifies repetitive steps in your workflow and sets up Academic Deep Research to handle them automatically
MCP vs traditional plugins: what's the difference?
Academic Deep Research is categorized under Data & Analytics. These skills help AI agents perform specialized tasks in this domain.