Skill UI

Structured manuscript and grant review guidance that walks reviewers through methodology, statistics, reporting compliance, and constructive feedback for rigorous scientific evaluation across disciplines.

Build a production-ready, AI-powered data collection agent for any public source (job boards, prices, news, etc.). This agent automatically scrapes data, enriches it using free LLMs (like Gemini Flash), and stores the results in databases such as Notion, Sheets, or Supabase. It runs on a free schedule using GitHub Actions and learns from user feedback, making it ideal for continuous data monitoring and tracking.

This skill provides comprehensive management for annotation schemas (configs) and human review workflows (queues) within the Arize platform. It supports defining categorical, continuous, and freeform label types. Users can programmatically apply these annotations to project spans and datasets using the Python SDK, facilitating structured human feedback loops and improving model monitoring.

The Paperzilla skill provides direct command-line access to interact with Paperzilla data. Users can fetch the latest research recommendations, summarize canonical papers in markdown format, view project feeds, leave feedback, and export data in various formats (JSON, Atom). It is essential for researchers needing structured insights into academic projects and literature.

Gtars offers local genomic interval models, set algebra, overlap/count operations, consensus and coverage, tokenization, fragment processing, and refget/BEDbase planning across Python, Rust, and CLI.

This guide covers advanced retrieval strategies that significantly boost search quality beyond basic vector similarity search. Techniques include Hybrid Search (combining dense and sparse indexing), Reranking (improving result order), Relevance Feedback (guiding search with iterative user scores), and Maximal Marginal Relevance (MMR) for diversity. Use these methods when standard search results lack relevance, miss critical keywords, or exhibit poor precision.

This skill provides a comprehensive framework for evaluating Power BI reports. It assesses report quality, usage adoption rates, performance metrics, and structural integrity across different lifecycle stages (development, testing, active use). It analyzes usage data, audience reach, and performance bottlenecks, generating actionable feedback and optimization recommendations to ensure reports are effective and maintainable.

Build a production-ready, AI-powered data collection agent for any public source (job boards, prices, news, etc.). This agent automatically scrapes data, enriches it using free LLMs (like Gemini Flash), and stores the results in databases such as Notion, Sheets, or Supabase. It runs on a free schedule using GitHub Actions and learns from user feedback, making it ideal for continuous data monitoring and tracking.

A comprehensive guide for academic researchers responding to R&R or conditional acceptance decisions for the American Economic Journal: Applied Economics (AEJ: Applied). This skill structures the response-to-referees letter and revision plan, emphasizing the triage of reviewer comments, adherence to editor priorities (especially concerning identification and robustness), and maintaining a professional, evidence-based tone. It helps authors transform critical feedback into a concrete, actionable revision strategy.

A comprehensive guide for authors submitting to high-level academic journals, specifically detailing how to construct a point-by-point rebuttal letter after receiving R&R (Revision & Resubmission) feedback. Covers advanced econometric topics, identifying common reviewer critiques (e.g., parallel trends, robustness checks, endogeneity), and structuring professional, evidence-based revisions.

A comprehensive guide on structuring and writing the 'Related Work' section for elite computer vision conferences like CVPR. It addresses the high velocity of academic literature, teaching advanced methods like defining explicit technical deltas, structuring arguments by research question, maintaining citation hygiene, and handling complex reviewer feedback on originality and concurrency.

A comprehensive project management guide for submitting database systems papers to EDBT. It details the complexities of the multiple-cycle rolling publication model, covering everything from initial evidence lock and cycle selection to the five-step review arc (Submission, Author Feedback, Revision, etc.). Use this to backward-plan your research timeline and manage the entire academic publishing process.