Skill UI

Automates capturing chat insights into structured Notion pages by extracting key concepts, organizing content by type, and linking newly created entries into the right wikis and databases for easy discovery.

Handles Obsidian Flavored Markdown with wikilinks, embeds, callouts, properties, tags, and other vault-specific syntax, letting you author or edit notes that fully leverage Obsidian features.

This deep-dive tool automates the complex process of migrating notes and knowledge bases from various platforms (such as Notion, Evernote, Roam, etc.) into Obsidian. It handles critical conversions like stripping platform-specific UUIDs, converting internal links to optimized Obsidian wikilinks ([[...]]), and correctly formatting attachments and YAML frontmatter, ensuring a seamless transition and preserving the structural integrity of your knowledge base.

Creates new Feishu Cloud Docs from Lark-flavored Markdown, letting you optionally target folders, wiki nodes, or knowledge spaces while ensuring structured, rich, and visually varied content.

Fetches Feishu cloud document content as Lark-flavored Markdown, extracts media tokens, and guides invoking feishu_doc_media to download images, files, and whiteboards while handling wiki token resolution.

Creates and edits Obsidian Flavored Markdown, covering frontmatter, wikilinks, embeds, callouts, math, diagrams, and other vault-specific syntax so notes render correctly when working in Obsidian or referencing its features.

This skill manages a persistent, structured personal knowledge base (Wiki). It provides core operations for ingesting external articles, synthesizing insights from conversations, and querying stored knowledge. By maintaining structured files, index lists, and cross-references, it helps build a comprehensive knowledge graph, ensuring all insights are captured and easily retrievable.

This comprehensive skill is designed to retrieve content from various Feishu cloud documents, returning the raw Markdown format. It provides advanced logic for handling Wiki URLs by first determining the actual document type (Docx, Sheet, Bitable) before calling the appropriate specialized tool. Furthermore, it guides the user on how to separately download and process embedded media like images, files, and whiteboards using dedicated media tools.

This skill transforms an LLM into a disciplined wiki maintainer for Obsidian. It moves beyond simple RAG by incrementally ingesting sources (papers, notes, articles) to build a persistent, interlinked "Second Brain." The LLM manages cross-references, updates core concepts, and maintains an evolving knowledge graph, ensuring that knowledge compounds over time rather than being re-derived on every query. Ideal for deep research, personal knowledge management (PKM), and building comprehensive internal wikis.

This skill guides the identification and search for specialized crew members (such as production controllers, costume designers, music directors) in South Asian cinema. It is essential when a question focuses on technical roles rather than just the director or lead actors. By using specific search queries on reliable databases (like IMDb or Wikipedia) after identifying the film, users can efficiently locate detailed production credits.

A comprehensive guide and workflow for managing a personal knowledge vault using Obsidian. It details best practices for structuring notes in a flat file system, utilizing index notes, and leveraging wikilinking syntax ([[wikilinks]]) for robust connectivity. Includes command-line methods (grep/find) for efficient searching, note creation, and finding related backlinks across the entire vault, ensuring organized, interconnected learning.

Render ARIS Markdown or JSON artifacts such as IDEA_REPORT, AUTO_REVIEW, KILL_ARGUMENT and research-wiki state into polished single-file HTML reports for human reading, with sticky TOC, math, callouts, score progressions and source drift detection.