Skill UI

Automates FAQ creation within the technical documentation workflow, offering guidance, best practices, sample configurations, and validation to help teams produce clear API docs, user guides, and architecture write‑ups.

This advanced workflow provides comprehensive meeting intelligence by allowing users to search across stored transcripts using keywords and date filters. It integrates the AskFred AI assistant for natural language Q&A over single or cross-meeting data. Furthermore, it aggregates detailed meeting analytics, providing key metrics such as total duration, action items, and top keywords for robust reporting and knowledge retrieval.

Automates flame graph generation during performance testing, guiding users through best practices, sample code, and validation for load, stress, and benchmarking workflows.

Automated assistant for forecast generator tasks in data analytics, guiding through SQL, visualization, statistics, and BI workflows with best practices, ready-to-run code, and validation.

This skill acts as a specialized expert for transitioning codebases across various frameworks, languages, versions, and platforms. It generates detailed migration plans, automated migration scripts, comprehensive risk assessments, and rollback strategies. Use it when upgrading technology stacks or moving code between disparate systems to ensure minimal disruption and maintain core functionality.

This skill outlines the complete workflow for capturing and structuring meeting notes using Granola. It captures audio, transcribes the content, and intelligently merges live user notes with the full transcript. The output is structured into key sections like Summaries, Decisions, and Action Items. Users can also interact with Granola Chat for post-meeting Q&A, making it an essential tool for professional meeting documentation and follow-up.

A specialized AI assistant acting as an expert Haskell engineer. This skill focuses on advanced type systems (GADTs, type families), pure functional architecture, concurrency (STM, async), and high-assurance software design. Use it for building robust, idiomatic, and maintainable Haskell code.

A comprehensive guide and assistant for designing and implementing user interface components (menus, buttons, toolbars) strictly following Apple's Human Interface Guidelines (HIG). It covers best practices for structure, hierarchy, contextual behavior, and platform-specific considerations across iOS, macOS, and visionOS.

Automated guidance for hyperparameter tuning within ML training workflows, offering best practices, production-ready code, and validation across modeling stages like data prep, training, and experiment tracking.

Automated assistant for frontend image optimization walks you through best practices, generates production-ready code and config, and validates results whenever you ask about image optimization patterns or helper workflows.

This skill outlines a comprehensive, multi-agent orchestration workflow designed for sophisticated production issue resolution. It systematically combines AI code assistants, observability platforms (like Sentry/DataDog), and automated techniques (e.g., git bisect, distributed tracing) into a rigorous four-phase process: Issue Analysis, Root Cause Investigation, Fix Implementation, and Verification. It guides best practices for reducing Mean Time To Recovery (MTTR) and improving system resilience in complex, multi-system environments.

Automates invoice generation workflows, guiding business users through setup, best practices, and production-ready configurations whenever they mention invoice generator triggers in requests.