Skill UI

This guide details the UseCase pattern, an architectural pattern used to encapsulate specific business operations within the Webiny framework. Learn how to define UseCases as injectable dependencies, manage input and output using the structured Result<T, E> type, and implement robust, domain-specific error handling. Mastering this pattern is crucial for building highly modular, testable, and maintainable backend APIs.

This comprehensive guide provides structured troubleshooting and error handling advice for developers integrating with the Workhuman Social Recognition and Rewards APIs. It covers critical API concepts, including OAuth 2.0 authentication, managing point-based nominations, and synchronizing data with major HRIS systems like Workday and SAP SuccessFactors. Use this resource when building complex HR workflows or integrating Workhuman into platforms like Slack or Teams.

This skill provides a comprehensive, structured process for creating and documenting new AI agent skills. It guides the user through gathering requirements, drafting structured files (like SKILL.md, REFERENCE.md), and optimizing descriptions to ensure the agent can correctly identify and utilize the new capability. Use when you need to build, write, or refine a complex, functional skill module for an AI agent.

This professional writing assistant specializes in creating clear, compelling, and highly structured documentation for Product Managers (PMs). It helps users draft, refine, and polish various deliverables—including product briefs, status updates, and executive emails—by adhering to best practices like leading with conclusions, maintaining extreme conciseness, and tailoring the tone to the specific audience (e.g., engineering team vs. executive leadership).

This skill is designed for tackling complex, multi-step software development tasks. It generates highly detailed, structured implementation plans that strictly adhere to best practices like TDD, YAGNI, and DRY. The plan breaks down features into small, atomic, executable tasks, specifying required file changes, writing initial failing tests, implementing minimum necessary code, and committing. It ensures the resulting plan is ready for efficient, autonomous execution by AI agents or human teams.

XcodeBuildMCP is a unified skill set designed to streamline the entire mobile and desktop development lifecycle. It replaces raw command-line tools like xcodebuild, xcrun, and simctl, providing structured workflows for iOS, macOS, watchOS, tvOS, and visionOS. Capabilities include project discovery, managing simulator and physical device workflows, advanced UI automation (gestures, view inspection), robust logging, and deep debugging using LLDB. It simplifies complex build, test, and run operations across multiple platforms.

This skill provides comprehensive capabilities for creating, editing, and managing professional presentations within the Lark (Feishu) ecosystem. It supports advanced content generation workflows, utilizing XML protocols, template searching, and layout linting to ensure high-quality, structured visual output. Ideal for automating report generation, slide decks, and structured corporate communications.

This powerful compiler ingests heterogeneous research inputs, including PDF papers, code repositories, experiment logs, and raw notes. It transforms this diverse data into a comprehensive, structured Agent-Native Research Artifact (ARA). The system extracts core knowledge atoms, builds cognitive maps (claims, concepts, heuristics), and generates a verifiable, executable knowledge package for advanced AI consumption and research iteration.

This tool functions as a post-task epilogue, designed to audit and record the entire research journey. It scans the conversation history at the end of a coding or research session to extract critical research artifacts, including decisions, experiments, dead ends, claims, heuristics, and major pivots. It systematically writes this provenance data into the structured `ara/` directory, ensuring a faithful and auditable trace of how the project truly evolved.

This framework enforces high output quality, intellectual honesty, and continuous improvement across all AppSec agents. It mandates structured processes, including self-critique loops, anti-rationalization guards, and self-reflection quality gates (≥8 scoring). Applicable during code review, SAST, SCA, and threat modeling, it ensures rigorous and verifiable security analysis.

A comprehensive guide for connecting resource-constrained microcontrollers (like Arduino) to Azure IoT Hub and IoT Edge. It provides structured patterns for secure provisioning, handling intermittent networks (store-and-forward), robust telemetry transmission (MQTT over TLS), and implementing local edge decision-making for industrial and field deployments.

This tool assists engineers in transforming vague work logs into structured, evidence-backed impact statements for professional documentation. It uniquely mines Copilot CLI session logs, git commits, and GitHub PRs to reconstruct forgotten work. It enforces a mandatory 'Action → Result → Evidence' impact contract, making it indispensable for preparing performance reviews, promotion packets, and self-assessments.