Skill UI

A comprehensive reference guide detailing best practices, rules, and optimizations for building high-performance React Native and Expo applications. It covers critical areas such as list virtualization, complex animations, UI patterns, state management, and monorepo structure, helping developers avoid common pitfalls and maximize app speed and stability.

This tool empowers users to query, filter, and aggregate logs from Datadog directly from the command line using the Composio CLI. It bypasses the graphical UI, providing structured JSON output for complex analysis, cross-service correlation, and automated reporting. Ideal for deep dive investigations, tracking latency regressions, or building scheduled operational digests.

This meta-skill orchestrates complex, multi-step job search workflows, moving beyond simple advice. It is designed for concrete tasks such as tailoring resumes to specific job descriptions (JDs), building complete application packs, preparing for named interviews, comparing multiple job roles, or maintaining an organized application tracker. It focuses on producing reviewable artifacts and never performs automatic applications.

This comprehensive skill provides expert guidance for integrating with Google NotebookLM programmatically, covering both the `nlm` Command Line Interface (CLI) and Measurement/Control Plane (MCP) tools. Use it to automate workflows, manage notebooks, add diverse sources (URLs, YouTube, Drive), and generate various complex content types, such as reports, quizzes, mind maps, and videos. Essential for developers building upon NotebookLM's advanced research capabilities.

This skill provides a comprehensive, step-by-step workflow for building complete Power BI reports from scratch using the pbir CLI. It guides users through model discovery, defining design briefs, visual layout, data validation, and final publishing. Ideal for automating the entire business intelligence (BI) reporting process and ensuring adherence to professional design standards.

Skill for working with Power BI reports using the pbir CLI. It covers exploring, building, managing, formatting, validating, and publishing reports, as well as driving Power BI Desktop for refresh and screenshots, and querying semantic models.

Guidance for designing, building, refreshing, and reviewing Power BI / Analysis Services tabular models from the terminal. Covers star schema, relationships, measures, calculation groups, roles, storage modes, incremental refresh, and model optimization. Routes every operation to the narrowest capable tool: te CLI first, then TOM or MCP, then TMDL. Ensures model quality, performance, and readiness for Copilot/AI.

This skill provides a comprehensive guide for building scalable Retrieval-Augmented Generation (RAG) pipelines and persistent agent memory using Pinecone as the vector database. It covers index setup, embedding large corpuses, implementing dense and hybrid semantic search, and advanced metadata filtering for real-world production systems. Use this for building searchable knowledge bases and context-aware AI agents.

This skill designs and audits the core engineering harness required for reliable AI agent collaboration within a codebase. It establishes critical infrastructure elements such as change tracking, linting rules, CI/CD gates, and standardized documentation, ensuring the repository remains the single source of truth for all intelligent agents. Ideal for setting up complex development workflows.

This skill generates a complete React component structure following the industry-standard Container/Presentation pattern. It automatically scaffolds necessary files, including TypeScript, Storybook, and SCSS styles, ensuring adherence to project conventions. Use this when building new, scalable components, allowing you to properly classify whether the component is UI-focused (Presentation) or logic-heavy (Container).

This skill guides you through a comprehensive, multi-phase interview to capture every necessary detail of a new project idea. It is designed to run BEFORE any code is written, forcing detailed specification gathering across purpose, features, data models, and technical constraints. The output is a clean, self-contained prompt.md file, ensuring subsequent development is based on solid, unambiguous requirements and preventing costly mistakes.

Creates comprehensive, actionable disaster recovery (DR) documents for any service or system. It defines critical recovery targets (RTO/RPO), outlines failure scenario runbooks, specifies backup validation procedures, and establishes testing cadences. Use this tool when building site reliability engineering (SRE) practices or preparing for major system failure simulations.