Skill UI

MolyKit is a comprehensive toolkit designed for building robust, cross-platform AI chat applications. It provides core utilities for integrating large language models (LLMs) like OpenAI, handling real-time SSE streaming responses, and managing complex cross-platform asynchronous patterns (PlatformSend, spawn()). The kit includes ready-to-use widgets for messages, prompt inputs, and avatars, making it ideal for developers creating sophisticated, multilingual chat experiences.

This skill provides best practices for integrating Matrix SDK functionality into Makepad applications. It details the architecture and implementation patterns for building robust, real-time chat clients. Topics include using native Sliding Sync for efficient room updates, managing asynchronous requests (e.g., sending messages, fetching timelines), and handling complex Matrix operations within a Tokio runtime environment.

Varlock is a secure-by-default CLI tool designed to manage and validate sensitive environment variables and secrets during coding sessions, CI/CD, and development workflows. It ensures that credentials, API keys, and passwords are never exposed in logs, terminal output, error messages, or the assistant's context, providing a critical layer of security for modern development practices.

Implements a simplified Signal Protocol stack with X25519 key exchange, HKDF derivation, AES-256-GCM per-message encryption, ratcheting chains, and replay protections so only communicating parties can read messages in secure deployments.

Evaluates WebSocket APIs for auth bypass, CSWSH, injection, DoS, and leakage by intercepting handshakes and messages with Burp Suite plus crafted payloads.

AgentPhone is an API-first platform designed for developers building AI agents with advanced telephony capabilities. It allows agents to manage phone numbers, make/receive voice calls, and handle SMS messages. Developers can utilize hosted mode for simple AI interactions or webhook mode for custom, complex logic, making it ideal for building sophisticated customer support bots or virtual assistants.

This comprehensive guide provides an end-to-end solution for implementing Firebase Cloud Messaging (FCM) in Flutter applications. It covers platform-specific setup for iOS, Android, and Web, detailing how to handle messages in foreground, background, and terminated states. Key topics include managing notification permissions, handling token lifecycles, and implementing reliable cross-platform push notification logic.

Guides disciplined git workflows for AI-assisted teams, covering branch strategies, commit hygiene, descriptive messages, and parallel workstreams to keep changes reviewable and reversible.

Adds samber/oops structured error builders to Go services, giving stack traces, codes, user-friendly messages, panic recovery, and exporter-friendly attributes for observability and diagnostics.

This tool provides command-line capabilities for subscribing to and consuming real-time events from the Lark/Feishu platform. It streams various events (e.g., IM messages, reactions, member changes) as NDJSON, making it ideal for developing Lark bots, implementing real-time message processing pipelines, or powering long-running AI agents. Users can list available event keys, inspect schemas, and consume data with advanced filtering, timeout, and max-event controls.

This tool generates ultra-compressed, standardized commit messages adhering strictly to the Conventional Commits specification. It analyzes code changes (diffs) to extract the core intent, structuring the output into a precise subject line and an optional body. It ensures that commit history remains clean, highly readable, and instantly understandable, significantly reducing noise and maintaining professional version control standards.

This workflow guides developers through generating standardized, descriptive commit messages using the Conventional Commits specification. It provides a structured XML template (including type, scope, description, body, and footer) and integrates directly into the Git workflow, ensuring project history is clean, traceable, and machine-readable. Ideal for maintaining large, collaborative codebases.