Skill UI

A universal motivation skill that pushes an AI to stop stalling, search and verify proactively, and pursue end-to-end solutions for debugging, research, writing, planning, deployment, and more.

This guide details advanced search techniques for researching musical artists from non-Western regions, including K-pop, Middle Eastern, African, and Latin American genres. It instructs users on moving beyond standard English search terms by incorporating regional keywords, cultural identifiers (like UN Ambassador status), specific platforms (e.g., Coke Studio), and systematic regional branching to find comprehensive information.

This guide teaches targeted verification strategies for historical research. When initial searches suggest a candidate name or figure, do not continue with broad searches. Instead, immediately switch to verifying the candidate against all specific constraints (time period, location, family details, major events) using precise search queries to confirm identity and eliminate false positives.

This technique helps users solve highly complex movie trivia or cinematic research questions that involve multiple, intertwined constraints (such as specific awards, historical eras, directors, or plot elements). Instead of attempting to input all variables at once, it teaches the methodology of decomposing the main question into 2-3 independent, searchable dimensions, ensuring a systematic and accurate search process.

This skill teaches how to dramatically improve the accuracy of historical research queries. When searching for information about a historical figure, rather than relying on generic facts (like era or nationality), users should identify and prioritize the most unique, specific, or niche details—such as a unique object, a rare event, or an uncommon biographical fact. By using these distinctive details as quoted search anchors, the search results become highly targeted, overcoming the limitations of broad, general queries.

This skill teaches the methodology of forming concrete hypotheses about specific entities (such as film titles, director names, or historical events) when presented with constraints. Instead of performing broad, generic searches, users should leverage their world knowledge to narrow down possibilities, turning a wide query into a precise, verifiable search query. This is particularly effective for academic or historical research.

Master the art of writing highly competitive research proposals for major funding bodies, including NSF, NIH, DOE, DARPA, and NSTC. This skill provides comprehensive guidance on structuring technical narratives, developing specific aims, justifying budgets, incorporating broader impact statements, and ensuring compliance with diverse agency-specific guidelines and formatting requirements.

This skill provides a robust, systematic framework for evaluating the rigor of scientific claims and research studies. It guides users in assessing experimental design validity, detecting various biases (selection, confounding, publication), and evaluating statistical evidence. By applying established grading standards like GRADE and Cochrane Risk of Bias, it is essential for conducting systematic literature reviews, peer reviews, and deep scientific critical analysis.

A comprehensive mentor guiding users through the entire lifecycle of academic literature reviews. It teaches systematic search strategies (PICO/PCC), critical appraisal methods, and advanced synthesis techniques. The skill covers searching major English and Chinese databases (e.g., PubMed, Web of Science, CNKI), organizing findings, and effectively utilizing AI research tools like Elicit and Semantic Scholar to build robust, evidence-based research papers.

A specialized technique for locating the full legal birth name of European actors, particularly French actors, who frequently use stage names. This process involves a two-phase search: first, identifying the stage name using general career clues (films, era, director); second, using specific queries like "birth name," "née," or "nom de naissance" to bypass the stage name and find the legal name. Ideal for deep biographical research.

A comprehensive intelligence tool designed for clinical researchers to navigate the complex NIH grant landscape. It utilizes a detailed 6-step intake process (covering research idea, career stage, and data status) to perform a multi-faceted positioning analysis. The system maps research to appropriate NIH institutes using RePORTER data and generates an editable Word document containing actionable mechanism recommendations, submission timelines, and strategic guidance for funding applications.

This tool assists researchers in structuring academic papers by mapping specific claims across different sections (Introduction, Method, Results, Discussion) to required external citations (BibTeX keys). It enforces citation density rules and ensures the correct role alignment (e.g., background, comparison, limitation) before the actual drafting process, guaranteeing that every core claim is properly supported and distributed.