Skill UI

This skill enables AI-assisted API development workflows. It can generate type-safe API clients, comprehensive documentation, and SDKs for multiple languages (such as Python or TypeScript) directly from OpenAPI/Swagger specifications. It is essential for developers building complex integrations or needing to standardize API usage across multiple platforms.

A powerful agentic workflow for complex software development. Cascade Write mode acts as an autonomous coding agent, allowing users to build features, refactor code across multiple files, run terminal commands, and debug errors—all from a single natural language prompt. Ideal for full-stack development, complex system building, and large-scale code refactoring.

This skill facilitates the rapid installation and comprehensive configuration of essential extensions for the Windsurf IDE. It covers critical development aspects including language support, code linting, formatting, Git integration, and various productivity tools. Use this skill to set up, customize, or upgrade a cohesive and highly productive development workspace.

Automate Workday HR operations from a Claude Code terminal by looking up workers, submitting time off requests, checking absence balances, and validating eligibility with natural language commands.

Automates Zoho Books accounting workflows—creating and managing invoices, tracking bills and payments, looking up contacts, exporting PDFs, and handling multiple organizations—all via natural language commands through the Rube MCP integration.

Combines ESM3 and ESM C protein language models to generate sequences, predict structures, condition functions, and extract embeddings via local or Forge API inference for protein design and engineering workflows.

A comprehensive skill for leveraging massive pre-trained transformer models across diverse AI domains, including Natural Language Processing (NLP), Computer Vision (CV), and Audio. Use this skill for advanced tasks such as text generation, classification, question answering, summarization, object detection, and model fine-tuning on proprietary datasets. It provides streamlined pipelines and granular control for deployment.

Transforms natural-language prompts into Excalidraw JSON diagrams, supporting flowcharts, relationships, mind maps, architecture, DFD, swimlane, class, sequence, and ER views; ideal when users ask to visualize processes or system structures and need editable Excalidraw files.

A powerful tool designed to generate pragmatic CI/CD pipelines by analyzing a project's actual stack (language, runtime, tooling) from its repository files. It automates the creation of foundational pipelines (lint, test, build, deploy) for platforms like GitHub Actions and GitLab CI, ensuring the baseline is reproducible and aligned with existing lockfiles. Ideal for bootstrapping new repositories or migrating existing, brittle pipeline definitions.

This powerful tool helps translate natural language requirements into robust, normalized relational database schemas. It can generate comprehensive schema designs, complete with relationships, constraints, and advanced architectural concerns like multi-tenancy, soft deletes, and audit trails. Furthermore, it automates the generation of database migrations (supporting Prisma, TypeORM, Alembic, etc.), corresponding type definitions (TypeScript/Python), seed data, and Entity-Relationship Diagrams (ERD) using Mermaid.

This skill provides comprehensive techniques for optimizing prompts used with any Large Language Model (LLM). It teaches proven methodologies—including Role definition (R), Context setting (S), Constraints (C), Instructions (I), and Templates (T)—to transform vague inputs into precision-engineered instructions. Users can reliably achieve structured JSON output, implement Chain-of-Thought reasoning, reduce hallucinations, and minimize token usage, ensuring consistent and high-quality results across different AI platforms.

A comprehensive guide to building production-grade evaluation systems for Large Language Models (LLMs). This skill covers advanced methodologies, including Direct Scoring and Pairwise Comparison, alongside critical techniques for mitigating systematic biases (e.g., Position Bias, Length Bias). Learn how to select appropriate metrics and structure prompts to ensure reliable, consistent, and objective quality assessment across various AI applications.