Skill UI

A framework for building production-ready, low-latency, multimodal AI agents. It allows developers to orchestrate complex pipelines that seamlessly handle real-time audio, video, and text data. Key capabilities include integrating multiple AI services (LLMs, STT, TTS), managing conversation context, and enabling tool use and function calling for advanced, interactive AI applications.

This skill automates the collection of high-quality technical news from multiple sources like Hacker News and HuggingFace. It uses a multi-agent architecture to scrape, filter, and deduplicate content, generating a curated daily Markdown report. Ideal for staying updated on cutting-edge technology and AI developments without manual searching.

A protocol that provides LLM agents with persistent structural memory of a codebase. It maps the project as a directed graph, tracking not only dependencies (what imports what) but also the 'reasons' (why it connects). This allows agents to understand context, perform impact analysis, and navigate large repositories without loading the entire source code into the context window.

This skill performs a two-model debate review on code pull requests from GitHub, GitLab, or Azure DevOps. It uses two AI agents to argue over code changes before posting a final inline comment. Ideal for thorough pre-merge reviews or local working tree checks. It requires delegate-skills and authenticated access to the version control platform.

A skill for delegating bounded work to AI agents (Codex CLI, Pi, Claude Code, Hermes) while preserving context, ownership, and progress checks. Covers agent selection, prompt formatting for TUI agents, polling strategies, and remote VPS execution.

Design-It routes frontend design tasks to 48 specific UI styles, avoiding generic aesthetics. It triggers for websites, app screens, or UI components requesting a specific aesthetic. The skill guides AI agents to select appropriate color palettes, typography, and layout principles like the 60-30-10 rule. It supports various frameworks including React, Vue, and mobile platforms.

This meta-skill orchestrates design workflows by routing tasks through brainstorming, multi-agent review, and execution readiness checks. It ensures ideas become validated designs before implementation, managing risk assessment and escalation logic. It controls flow between creative and technical skills, preventing costly mistakes by enforcing proper review steps and blocking execution without approval.

Establishes and updates the foundational context for your target developer audience. Analyzes product materials, personas, pain points, and alternatives to create a comprehensive .agents/developer-audience-context.md file. Essential for starting other developer marketing skills to ensure consistent messaging and strategy.

This skill involves testing AI agents for direct prompt injection vulnerabilities where user messages attempt to override system instructions. It focuses on role confusion and instruction hijacking without external content, ensuring agents maintain security boundaries against direct manipulation attempts.

This guide details the comprehensive workflow for distributing a single AI skill across various local agent skill directories (Codex, Claude, Pi, Hermes). It addresses canonical locations, symlink management, and specific synchronization commands to ensure that all agents detect the latest skill version while correctly navigating common development pitfalls.

Ditto mines user words from local coding-agent session logs to create private work, design, and writing profiles. It requires explicit user approval before mining begins and keeps all data local. This skill routes a compatible Ditto runtime to extract patterns from real coding history rather than questionnaires, ensuring privacy and evidence-backed personalization for AI agents.

This guide provides comprehensive templates and best practices for structuring all types of technical documentation. It covers essential formats including README files, REST API endpoints, code comments (JSDoc), Changelogs, Architecture Decision Records (ADR), and AI-optimized documentation. Use these templates to ensure your project documentation is standardized, scannable, and easily consumable by both human developers and AI agents.