Skill UI

An advanced tool for network intelligence that calculates weighted graph scores to map the optimal path to a target. It identifies potential introducers, measures 'bridge value' across connections, and helps determine whether a connection requires a warm introduction or direct outreach on platforms like X and LinkedIn. Ideal for users needing the raw ranking methodology.

Craft polished demo videos from screenshots or scene descriptions, orchestrating Playwright screenshots, narration via edge-tts, and ffmpeg compositing with clear story beats, pacing, and single-focus scenes so product walkthroughs and marketing teasers feel cinematic.

This skill manages comprehensive software development life cycle operations—including issue triage, PR reviews, version releases, bug fixing, and marketing content generation. It operates using a parallel "agent army" of dynamic agents (10-20 per task), requiring the user to adopt an Engineering Manager (EM) mindset. Key principles involve rigorous citation checking (anti-hallucination) and applying multiple roles (Product Owner, Open Source Contributor, Architect) simultaneously to ensure robust, safe, and user-centric outcomes across all platforms.

This skill analyzes accumulated usage logs from a complex research harness (ARIS) to propose structural optimizations. It identifies areas for improvement in SKILL scripts, default parameters, workflow ordering, and reviewer prompts. It is designed to automate the meta-level engineering process, ensuring that system efficiency is continuously improved based on real-world usage data.

This skill generates highly structured, long-form blog content (800-3000 words) optimized for both SEO ranking and AEO citation requirements. It automatically includes essential elements like a TL;DR summary block, defining sentences, comparison tables, and 5 distinct FAQs. This structure ensures the content is easily digestible, highly authoritative, and optimized for extraction by modern AI engines and search algorithms. Ideal for building topical authority and content clusters.

This skill provides comprehensive automation for managing GitHub workflows across the entire development lifecycle. It covers detailed issue triage, PR review status checks, CI/CD failure debugging, official release management, and security monitoring using the GitHub CLI. Ideal for maintaining open-source project health and streamlining team development processes.

Discover, download, and manage reusable AI agent skills from the AionUI Skills registry, making it easy to augment autonomous assistants with community-built capabilities whenever a task benefits from specialized functionality.

Guides designing stable, well-documented interfaces for APIs, module boundaries, and component props to make correct usage easy and inadvertent mistakes difficult.

Implements an ultra-compressed communication mode by drastically reducing token count while maintaining high technical accuracy. This mode strips filler words, articles, and pleasantries, allowing users to communicate complex technical concepts in the most concise way possible. Ideal for debugging, generating logs, or highly efficient development conversations. Supports multiple intensity levels, including classical Chinese modes.

This guide provides best practices for technical documentation, emphasizing the capture of context (the *why*) rather than just code (the *what*). It details how to write Architecture Decision Records (ADRs) for significant architectural choices, such as database selection, API design, and framework choice. Utilizing ADRs ensures that future engineers and teams understand the original reasoning, constraints, and trade-offs made during development.

Accelerates GitHub cloning, release/raw/archive downloads, and other resource access for Mainland China users by rewriting URLs through githubproxy.cc or fallback ghfast.top, with an optional URL converter script for quick adaptation.

A comprehensive guide for Go developers covering the entire performance measurement lifecycle. Learn how to write rigorous benchmarks using b.Loop(), track memory allocations, run tests with various flags (e.g., -benchmem, -cpuprofile), and analyze results using profiling tools like pprof and benchstat. Ideal for ensuring code stability, detecting regressions, and optimizing critical paths.