Skill UI

A highly structured framework designed for generating, organizing, and transparently prioritizing scientific research concepts. It enforces independent idea generation, explicit assumption labeling, structured discussion, and evidence-aware evaluation, ensuring the creation of robust, proposal-level research directions for early-stage exploration.

This skill provides a systematic framework for evaluating the rigor of scientific claims, research methodology, and evidence quality. It guides users through assessing experimental design validity, identifying various types of biases (e.g., selection, cognitive), and applying established grading frameworks like GRADE or Cochrane Risk of Bias. Ideal for systematic reviews, peer review, and critical analysis of scientific literature.

A comprehensive skill for generating visually engaging, scientifically rigorous slide decks for academic talks. It guides users through planning, structuring content, and ensuring design consistency for conferences, thesis defenses, and research seminars. Supports integrating complex figures and citations into professional PDF presentations.

scVelo is a powerful Python package designed for RNA velocity analysis using single-cell RNA-seq data. It estimates cell state transitions by modeling the kinetics of mRNA splicing—specifically using the ratio of unspliced to spliced mRNA abundances. This allows researchers to reconstruct developmental trajectories and predict cell fates, even when only snapshot data is available, making it a vital complement to standard trajectory inference tools like Scanpy.

SymPy is a powerful Python library designed for exact symbolic computation, allowing users to perform advanced mathematical operations without resorting to floating-point approximations. It provides comprehensive tools for symbolic algebra, differentiation, integration, solving complex equations (linear and non-linear), and handling linear algebra. It is essential for scientific computing, physics modeling, and advanced mathematical research, supporting multiple output formats like LaTeX.

This skill automates the process of transforming high-level product specifications, requirements, and design documents into a detailed, actionable, and executable task plan. It follows a multi-stage workflow, including context loading, parallel research, and two rigorous review gates (Task Plan Review and Task-Graph Sanity Review). The output provides properly sized (1-3 hours), logically sequenced tasks, ensuring every requirement is covered and dependencies are explicitly managed, dramatically improving project planning accuracy.

A comprehensive coach designed to guide students and researchers through the entire scholarly writing lifecycle. This skill covers structuring complex academic works—including research papers (IMRaD), theses, dissertations, grant proposals, and conference abstracts. It teaches fundamental writing principles, proper source integration, avoiding plagiarism, and navigating diverse citation styles (APA, MLA, Chicago, GB/T 7714), helping users develop an independent, professional academic voice.

idea-os is a comprehensive, five-phase pipeline designed to transform a raw, abstract idea into a fully structured, build-ready plan. It guides users through Triage, Clarification, Deep Research, detailed PRD creation (including non-goals and metrics), and finally, a phased execution plan. The system adapts its complexity and vocabulary to the user's sophistication level, providing everything from foundational market analysis to actionable technical stack recommendations.

This skill performs a zero-context verification audit, ensuring that every quantitative claim, comparison, and scope statement within a research paper precisely matches the provided raw result files. It is designed to eliminate confirmation bias, catching discrepancies such as incorrect rounding, cherry-picked best seeds, or misreported performance deltas before publication. Ideal for validating paper-to-evidence fidelity.

This advanced skill is an end-to-end tool for transforming complex research topics into professional, visualized knowledge graph PDFs. It automatically conducts multi-round web searches, extracts key entities, structures related knowledge, and designs the optimal visualization (supporting Graphviz, PlantUML, etc.). Ideal for deep academic analysis, mapping character relationships, or visualizing complex technical architectures where existing structured data is unavailable.

This comprehensive skill guides users through the entire lifecycle of developing AI agent skills. From initial concept (Understand) to structured design, writing the core skill logic, rigorous testing, and final performance optimization. It ensures skills are robust, accurate, and highly triggerable across any domain, including engineering, content creation, and research.

This tool functions as a post-task epilogue, designed to audit and record the entire research journey. It scans the conversation history at the end of a coding or research session to extract critical research artifacts, including decisions, experiments, dead ends, claims, heuristics, and major pivots. It systematically writes this provenance data into the structured `ara/` directory, ensuring a faithful and auditable trace of how the project truly evolved.