academic-deep-research-clawhub-skill

This Skill addresses the lack of transparency, reproducibility, and rigor in the academic research process. In practice, researchers often spend significant time gathering and filtering information but struggle to ensure the integrity of their methodology and the credibility of their conclusions. The tool enforces mechanisms such as two full research cycles per topic, APA 7 citation formatting, and adherence to evidence hierarchies to guarantee a transparent process and reproducible results.

Usage is straightforward: simply express your deep research need at the start of the conversation. The tool will first clarify the scope with 2-3 questions, then generate a research plan for your approval. It then automatically executes two research cycles, each leveraging native tools like web_search and web_fetch, performing analysis between tool calls, and tracking multiple sources for cross-verification. It delivers a comprehensive narrative report complete with APA 7 in-text citations and a reference list—all without requiring manual tool switching.

It is ideal for scenarios demanding academic rigor, including literature reviews, competitive intelligence analysis, and industry report writing. It particularly benefits users dissatisfied with traditional 'black-box' API wrapper tools who desire full control over the research workflow. Academic researchers, data analysts, and product managers can all leverage it for tasks like writing papers, analyzing market trends, or evaluating competitors.

It is recommended for consistent use in deep research and analysis. Note that it primarily relies on OpenClaw native tools and does not depend on external APIs, so the runtime environment must support these tools (e.g., web search, web fetching). Reports are purely narrative, without lists or tables, making them suitable for publishable academic-style content. Users requiring tabular or bullet-point formats will need to perform additional processing.