executive-obsidian

To convert Excel executive data into an Obsidian knowledge graph, this Skill uses pandas and openpyxl to extract entities like education and career timelines via LLM, then exports a fully linked Obsidian vault with bidirectional relationship mapping.

Yes, you can use OpenAI, Anthropic, DeepSeek, Zhipu, and Qwen APIs for entity extraction from executive profiles, enabling the pipeline to automatically parse unstructured bios into structured education and career data.

You can build alumni and workplace networks from finance Excel data by running the extraction pipeline, which automatically constructs three-tier professional relationships including current colleagues, former colleagues, and alumni with cross-company traceability.

Yes, the Excel to Obsidian pipeline supports incremental processing and caching, allowing you to resume interrupted runs and cache previously extracted companies to accelerate repeated executions.

The pipeline requires the pandas and openpyxl dependencies to process standard Excel files, extracting structured executive career timelines and qualifications from unstructured personal bios.

A key limitation of using LLM to extract education history from Excel bios is the dependency on external API providers for accurate unstructured data parsing, requiring valid API keys and incurring processing costs for each extraction.