What problem does it solve? Manually writing frontmatter metadata for Obsidian notes is error-prone and often violates vault conventions like wikilink formats and enum values. This Skill demonstrates how to use the para-obsidian LLM utilities to generate frontmatter field suggestions that respect template rules, existing vault context, and Dataview compatibility. ## Core Features & Use Cases - 3-Layer LLM Architecture: Separates constraints (validation rules), prompt building (structured prompts), and orchestration (Ollama calls and response parsing) for testable, reusable AI integrations. - Single-Field Suggestions: Use suggestFieldValues() for interactive commands that propose one field at a time with user confirmation. - Full Note Conversion: Use convertNoteToTemplate() to transform plain notes into PARA-structured notes (project, area, resource, task) with validated frontmatter. - Use Case: Convert a plain note about an AI voice assistant project into a PARA project note with area as a wikilink, status enum, due date, and tags, all validated against existing vault areas and frontmatter rules. ## Quick Start Ask the AI to suggest frontmatter field values for a new project note using the para-obsidian LLM utilities with your vault context and the qwen2.5:7b Ollama model.
