Skill UI

Evaluates incoming requests, decides if specialized skills are needed, orchestrates optimal combinations, and logs successful pairings in agent-memory while guarding against overusing complex tools on simple tasks.

Open Dynamic Workflows (ODW) is an advanced, open-source engine designed to manage complex coding tasks using multiple AI agents. It operates in three stages: planning the task into parallel subtasks, orchestrating various coding agents (like Codex or Antigravity) to work concurrently, and finally, performing an adversarial verification pass to challenge and validate the combined output before merging. It supports multiple model providers and is ideal for structured, high-reliability software development.

A powerful plugin enabling Claude Code to delegate complex tasks to external AI CLIs (such as OpenAI Codex or Google Antigravity/Gemini) without exiting the conversation. It supports multi-model workflows, allowing users to seek a second opinion, cross-check deep analysis, or delegate side tasks (like research or code review). The core value is that Claude synthesizes the raw outputs, providing a critical review and reconciliation of findings across all consulted models.

This skill guides users to configure and orchestrate parallel AI agents using the standalone Antigravity 2.0 Agent Manager alongside the Antigravity IDE. It covers installation, dual-workspace setup, and coordinating agent execution for front-end and back-end projects. Best practices include enforcing folder-level boundaries to prevent conflicts and using Git for synchronization.

A meta-skill that evaluates task complexity and dynamically selects appropriate specialized skills for AI agents. It prevents overuse of tools on simple tasks, tracks successful skill combinations via memory, and coordinates execution across multiple domains to solve complex problems efficiently.

Open Dynamic Workflows (ODW) is an advanced, open-source engine designed to manage complex coding tasks using multiple AI agents. It operates in three stages: planning the task into parallel subtasks, orchestrating various coding agents (like Codex or Antigravity) to work concurrently, and finally, performing an adversarial verification pass to challenge and validate the combined output before merging. It supports multiple model providers and is ideal for structured, high-reliability software development.

A quota-aware parallel subagent coordination skill for Antigravity 2.0. Decomposes large multi-file tasks into isolated agent missions, manages model selection based on cost, and ensures efficient parallel execution while monitoring quota usage. Ideal for complex projects spanning multiple files and components.