Skill UI

This skill provides comprehensive management for multiple local Command Line Interface (CLI) agents. It allows users to start, stop, monitor, and assign tasks to these agents, running them in separate tmux sessions for parallel execution. It is ideal for complex, scheduled workflows requiring multi-agent coordination, task monitoring, and log tailing, making it invaluable for advanced automation setups.

An expert system for designing and implementing advanced AI context architectures. It specializes in integrating intelligent memory systems, vector databases, and knowledge graphs to ensure AI applications maintain coherent, relevant, and scalable state across complex, multi-agent workflows. Essential for enterprise RAG implementation and stateful AI development.

Manages Firebase/Firestore CRUD, queries, batch jobs, and security for applications while extending to A2A agent messaging, MCP server integration, and Cloud Run coordination for advanced workflows.

This powerful skill manages Git worktrees to enable safe, isolated parallel feature development. It standardizes branch isolation, automatically allocates unique network ports, and synchronizes environments, allowing multiple agents or terminal sessions to work on different branches simultaneously without conflicts. It also provides mechanisms for detecting and safely cleaning up stale worktrees.

This agent functions as a Senior Product Manager expert, providing comprehensive support across the entire product lifecycle. It utilizes over 30 proven PM frameworks (e.g., RICE, MoSCoW) and includes 12 templates and 32 essential SaaS metrics with exact formulas. It is designed for structured analysis, assisting with strategy definition, market discovery, roadmap planning, and data-driven decision-making.

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.

This agent provides structured summarization for academic papers, reports, and articles. It goes beyond simple summarizing by extracting key findings, generating comparative matrices across multiple sources, and producing properly formatted citations (APA, IEEE, etc.). It is designed for analysts, product managers, and researchers who need actionable, deep insights from dense documentation.

Automatically reverse-engineers any codebase (frontend, backend, or fullstack) into a comprehensive Product Requirements Document (PRD). It analyzes complex elements like routes, components, API integrations, state management, and business logic across major stacks (React, Vue, Next.js, Django, FastAPI). The resulting PRD is detailed enough for both product managers (understanding 'what') and engineers/AI agents (understanding 'how' to reconstruct the system).

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 provides a comprehensive playbook for setting up and orchestrating multi-agent systems using the standalone Antigravity 2.0 Agent Manager alongside the Antigravity IDE. It guides developers on creating a dual-window workspace to coordinate specialized AI agents (e.g., front-end, back-end, QA) to work in parallel on a single codebase, significantly boosting development efficiency and managing concurrent code changes.

This skill provides comprehensive management for Opencode's permission system. It allows users to review currently always-allowed commands, suggest safe read-only commands, and configure granular access controls using allow/deny/ask patterns. It is essential for optimizing security, performing system audits, and managing the operational scope of the agent.

This library manages the entire lifecycle of bounded AI agent feedback loops. It allows users to find existing workflows from a catalog, adapt established loops by modifying parameters or tools, or design entirely new, structured iterative processes through a guided interview. It emphasizes safety by enforcing explicit checks, stop rules, guardrails, and measurable terminal states, preventing endless, uncontrolled autonomy.