A rigorous, multi-cycle research agent that delivers APA-compliant narrative reports through transparent methodology and user checkpoints.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install academic-deep-research-pro
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install academic-deep-research-pro using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Academic Deep Research?
Academic Deep Research is a professional-grade Openclaw Skills module designed for users who require more than just a surface-level summary. Unlike black-box API wrappers, this skill operates with full transparency, utilizing native tools like web_search and sessions_spawn to conduct exhaustive investigations. It is built on a foundation of academic rigor, ensuring that every claim is backed by an evidence hierarchy and verified across multiple sources.
This skill is specifically engineered to handle complex inquiries such as competitive intelligence, deep literature reviews, and evidence-based analysis. By enforcing three mandatory user checkpoints and a two-cycle research minimum per theme, it ensures the final output is reproducible, accurate, and perfectly aligned with the user's scholarly or professional requirements.
Academic Deep Research Use Cases
- Conducting exhaustive literature reviews for academic papers or professional journals.
- Performing deep-dive competitive intelligence with multi-source verification.
- Generating evidence-based reports that require strict APA 7th edition citation formatting.
- Investigating complex topics where contradictions in available data must be identified and addressed.
How Academic Deep Research Works
- Initial Engagement: The agent starts by asking 2-3 clarifying questions to define the scope and specific goals of the research.
- Research Planning: A detailed plan containing themes, steps, and deliverables is presented to the user for formal approval.
- Cyclical Investigation: The agent performs at least two full research cycles for every identified theme, analyzing data between every tool call.
- Evidence Synthesis: Information is filtered through an evidence hierarchy, addressing contradictions and citing multiple sources per claim.
- Final Narrative Delivery: A comprehensive narrative-only report is generated, complete with in-text citations and a full reference list.
Academic Deep Research Setup
To integrate this research capability into your environment, install it via the Openclaw Skills manager:
openclaw install academic-deep-research-pro
Ensure your agent has access to the native toolset, specifically web_search, web_fetch, and sessions_spawn for parallelized research threads.
Academic Deep Research Data Schema & Taxonomy
The skill organizes its findings based on a strict internal taxonomy to ensure reproducibility:
| Data Component | Description |
|---|---|
| Themes | Discrete research categories defined during the planning phase. |
| Evidence Hierarchy | Classification of sources based on reliability and academic weight. |
| Research Cycles | Iterative logs of tool calls and intermediate analyses for each theme. |
| Citations | APA 7th edition compliant metadata mapped to every factual claim. |
| Final Report | A Markdown-formatted narrative document excluding tables or lists for flow. |
Academic Deep Research Advanced Features
- Multi-Agent Parallelism: Leverages sessions_spawn to conduct research on multiple themes simultaneously for faster throughput.
- Mandatory User Checkpoints: Built-in flow control that prevents the agent from proceeding without explicit user validation of the research plan.
- Conflict Resolution: Advanced logic for identifying and documenting contradictions between different web sources.
- Rigorous Citation Engine: Automated mapping of web fetch data to APA 7th edition formatting requirements.
SKILL.md
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