Skill UI

Generates comprehensive and structured developer handoff annotations for any Figma screen or component. This tool transforms raw visual designs into precise, buildable specifications, covering interactions, states (loading, error, success), accessibility requirements, and edge cases, ensuring developers receive everything needed for implementation.

This skill provides querying capabilities for the 1000 Genomes Project dataset, covering 3,202 whole-genome-sequenced individuals on the GRCh38 assembly. It allows users to identify variants within a region, find specific individuals who carry defined genetic variants, or determine the relatedness between two named individuals. Results include allele frequencies (AF), AlphaMissense scores, and various clinical annotations. Use this tool for advanced genomic cohort analysis.

Automatically generates comprehensive API documentation from existing TypeScript or JavaScript source code. It scans public exports, parses detailed JSDoc annotations (including parameters, returns, and throws), and can generate standardized OpenAPI 3.0 specifications for HTTP endpoints, ensuring robust and up-to-date API references.

This guide details the architectural and implementation patterns for building modular applications or microservices using the tinystruct Java framework. It covers core concepts like using the @Action annotation for dual routing (CLI/HTTP), managing request state with Context, and using native Builder for JSON serialization, ensuring a lightweight and structured development environment.

A comprehensive project management guide for preparing and submitting advanced NLP conference papers to EMNLP. It details the entire research lifecycle, including backward planning from ARR deadlines, managing data annotation timelines, coordinating team roles, and making strategic decisions (commit, revise, withdraw) to ensure successful submission.

Predict regulatory features, gene structure, and expression from DNA sequences using hosted transformer DNA language models via REST API or MCP server. Six tasks: promoter, splice, enhancer, chromatin, expression, annotation. No local GPU needed.

This skill guides authors on positioning and framing manuscripts for the Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING). It provides detailed advice on core fit, required evidence (e.g., documentation, licensing, annotation reliability), and rhetorical structure needed to ensure a paper resonates with the specialized audience of language resources and computational linguistics.

This comprehensive guide outlines the rigorous standards for presenting quantitative results in academic economic research. It emphasizes moving beyond mere statistical significance (stars) to provide clear, economically meaningful interpretations, such as magnitudes, shares, rankings, and trends. It also mandates full transparency by requiring detailed annotation of data sources and calculation methodologies, ensuring results are fully reproducible and traceable.

This skill guides the structure and prose for drafting high-level integrative reviews, particularly for publications like the Psychological Bulletin. It ensures the manuscript moves beyond descriptive annotation to become a rigorous, evaluative synthesis. Users must comply with APA 7th edition style and specific reporting standards (MARS for meta-analyses, PRISMA for systematic reviews, and JARS for quantitative work). It provides detailed guidance on structuring the abstract (≤ 250 words), the method section, results, and discussion to meet expert reviewer expectations.

Scanpy is a powerful, scalable Python toolkit built on AnnData for comprehensive single-cell RNA-seq data analysis. It supports the complete biological workflow, including quality control, normalization, dimensionality reduction (PCA, UMAP, t-SNE), clustering, marker gene identification, and sophisticated cell type annotation, enabling the generation of publication-quality figures.

This skill scaffolds a gold-standard annotation project tailored for evaluating clinical NER and de-identification models (OpenMed). It guides users through defining label schemas, writing rigorous guidelines, configuring annotation tools (like BRAT/Label Studio), generating synthetic clinical text, and creating disciplined, non-leaking train/dev/test splits. It ensures that all committed data are synthetic fixtures for reproducible evaluation.

A comprehensive guide to writing idiomatic, statically typed GDScript for Godot 4.7. This skill covers using the node lifecycle, understanding signal systems, and correctly utilizing annotations like @export and @onready. It is essential for developing new Godot projects or porting existing code from Godot 3.x to the modern 4.x architecture.