Skill UI

This skill demonstrates the multi-model pattern for creating robust and clean API contracts using Pydantic. It guides the creation of separate models for creation requests (Create), updates (Update), responses (Response), and database documents (InDB), ensuring type safety and clear data validation for Python backends. It also covers best practices like handling camelCase aliases and optional fields.

A comprehensive guide for designing and managing document control systems for ISO 13485-compliant Quality Management Systems (QMS), specifically tailored for the medical device industry. This resource covers document numbering, version control, change management workflows, approval processes, and ensures compliance with rigorous standards like 21 CFR Part 11, including electronic signatures and audit trails.

Implements and maintains ISO 13485 QMS for medical device organizations, covering gap analysis, documentation control, internal audits, supplier qualification, and CAPA tracking to keep regulatory programs audit-ready.

Automated quickstart guide generator that kicks in whenever you mention the trigger phrase, offering step-by-step technical documentation guidance, code samples, and validation to ensure API docs, user guides, and architecture notes stay production-ready.

Designs and implements production-grade RAG systems with document chunking, embeddings, vector stores, hybrid search, reranking, and evaluation, ideal for knowledge-grounded AI apps that need semantic retrieval, similarity search, and context augmentation.

Expert in designing and implementing advanced Retrieval-Augmented Generation (RAG) pipelines. This role focuses on optimizing the entire information retrieval process—from document chunking and embedding model selection to vector database architectures and hybrid search strategies. The goal is to bridge the gap between raw knowledge documents and accurate LLM understanding, drastically reducing hallucination and enhancing context relevance for enterprise applications.

This skill functions as an expert technical writer, generating comprehensive and structured README.md documentation for software projects. It meticulously analyzes the codebase, identifying project structure, tech stack, prerequisites, dependencies, and deployment pipelines, ensuring users receive a complete guide for local setup and production deployment.

Auto Readme Generator offers guided documentation workflows for DevOps basics, triggering whenever "readme generator" is mentioned, and delivering best-practice code, configurations, and validations to support version control, containerization, and CI/CD.

This skill specializes in creating exhaustive, searchable, and highly structured technical references. It generates comprehensive API documentation, detailed parameter listings, configuration guides, and schema definitions, ensuring the output serves as the definitive source of truth for any technical system.

Documented workflow for automating Composio Remove Bg tasks via Rube MCP, covering discovery, connection management, schema compliance, and execution patterns to reliably integrate background-removal tooling.

Document outlining how to automate Reply IO operations through Composio’s Reply IO toolkit via Rube MCP, covering setup, tool discovery, execution flows, and best practices to keep schemas and connections in sync.

Defines the Research Engineer role, focused on investigating problems, prototyping solutions, and bridging research with engineering execution even when detailed documents are unavailable.