Show HN: Skill for structured deep research with Claude Code and Obsidian (github.com)

A new Claude Code skill has been introduced to enhance structured deep research within Obsidian, enabling users to efficiently organize information in an interconnected format. By simply inputting a topic or a deep research report, the AI generates atomic notes, entity profiles, and comparison tables, seamlessly integrating them with existing content in the user's Obsidian vault. This tool is inspired by the Zettelkasten methodology, which emphasizes meticulous organization and connectivity among notes, requiring each entry to link to an index page and at least one other note. This innovation is significant for the AI/ML community as it fosters deeper knowledge retention and retrieval through structured note-taking, which is crucial for comprehensive research workflows. The skill automates the decomposition of reports into manageable parts, while its built-in tagging system helps users identify the confidence level of AI-generated notes before validation. With features allowing the agent to follow source URLs and continuously build on prior sessions, this tool enhances collaboration and the iterative nature of research, supporting scholars, developers, and data scientists in deepening their understanding of complex topics.