Skill UI

A comprehensive workflow designed to convert unstructured conversational data, meeting notes, and ad-hoc decisions into highly structured, linkable entries within Notion. This tool ensures that all captured knowledge—whether an FAQ, a 'how-to' guide, or a formal decision log—is properly documented, categorized, and linked to maintain a cohesive, searchable knowledge base for easy reuse across teams.

This tool streamlines the entire meeting preparation lifecycle. By integrating Notion context, performing targeted searches, and enriching content with Codex research, users can draft structured agendas, pre-reads, and decision documents. It ensures all necessary background information, owners, timeboxes, and industry insights are compiled for highly effective meetings.

This tool facilitates comprehensive research by pulling relevant information from multiple Notion sources. It synthesizes scattered data into highly structured documentation, such as detailed briefs, comparative analyses, or executive reports. It ensures all claims are supported by accurate inline citations and links, making it ideal for market research, project documentation, or academic reporting where source traceability is critical.

This tool is designed to generate a concise and academically rigorous abstract for completed research papers. By taking the revised body, the function synthesizes the core problem, methodology, key results, and overall significance. It adheres strictly to defined style preferences, audience needs, and outputting a pure LaTeX fragment, ensuring the summary is accurate and professional.

This skill provides current weather conditions, multi-day forecasts, and various format options for any specified location by querying external services like wttr.in or Open-Meteo. It is designed for general weather queries, including daily summaries and weekly forecasts, without requiring an API key.

A dedicated tool for querying Lark Meeting Notes (Notes) details and raw verbatim transcripts. It requires an explicit note_id to function, allowing users to determine the display type, access associated document tokens, and retrieve the original unified transcript. It strictly focuses on note-based retrieval and does not handle searching by title, document body, or meeting ID.

This skill acts as a literature-research assistant, orchestrating a Python CLI to interface with APIs like Semantic Scholar and arXiv. It enables users to search for academic papers by topic, retrieve detailed metadata, perform impact analysis using citation tracking, download PDFs, and extract text content. It streamlines the entire academic research workflow from initial discovery to deep reading.

A crucial post-hoc review skill designed for AI-generated Markdown prose. It audits content against a comprehensive set of 21 stylistic and structural rules using both deterministic mechanical checks and deep semantic judgment. Users can audit a single file to get a detailed scorecard, or compare two drafts (A/B) for regression testing. Furthermore, it can optionally generate a polished, revised copy in a separate file, ensuring the integrity of the original document while significantly improving linguistic quality and adherence to style guides. Ideal for refining AI-written documentation, ...

A protocol for token-efficient, accurate, and structured web research. It guides the model to fetch minimum data when accessing URLs, GitHub repositories, or performing web searches, preventing token waste.

This skill manages and maintains your personal context portfolio, a structured set of markdown files detailing your identity, professional roles, team information, and system configurations. It guides users through first-time setup interviews, detects missing or incomplete information (e.g., TODO placeholders), and facilitates targeted updates when your professional context changes.

This skill provides advanced connection-discovery and semantic search across your personal Apple Notes. It moves beyond simple keyword matching to find related ideas, identify non-obvious 'bridges' between concepts, and synthesize comprehensive summaries of your thoughts. Ideal for knowledge workers looking to recall, analyze, or map their personal knowledge base.

This skill facilitates structured, bidirectional reading and knowledge synthesis for academic texts, theories, and articles. It forces users to first capture the source material's original intent, before critically mapping its relationships, conflicts, and absorptions against the CrossFrame framework. It ensures structured output with clear source boundaries, making it ideal for deep learning and scholarly work.