antigravity-awesome-skills

Email infrastructure for AI agents. Create accounts, send/receive emails, manage webhooks, and inspect billing balance via the AgentMail API.

Manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) in an explicitly authorized workspace.

Manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) in an explicitly authorized workspace.

Rules for when an agent should recall from long-term memory before acting and when it should save decisions, corrections and failures afterwards. Works with any memory backend.

A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).

Design tenant-scoped memory, retrieval and retention for agents. Use when planning RAG, conversation history, vector stores or remembering across sessions.

Systematic improvement of existing agents through performance analysis, prompt engineering, and continuous iteration.

Optimize multi-agent systems with coordinated profiling, workload distribution, and cost-aware orchestration. Use when improving agent performance, throughput, or reliability.

Meta-skill que orquestra todos os agentes do ecossistema. Scan automatico de skills, match por capacidades, coordenacao de workflows multi-skill e registry management.

Create, revise, or audit AGENTS.md files from repository evidence, verified commands, and correctly scoped instructions without overwriting maintainer intent.

Build container-based Foundry Agents with Azure AI Projects SDK (HostedAgentDefinition). Use when creating hosted agents with custom container images in Azure AI Foundry.

Tools are how AI agents interact with the world. A well-designed tool is the difference between an agent that works and one that hallucinates, fails silently, or wastes tokens. This skill covers tool design from schema to error handling.

AI agent development workflow for building autonomous agents, multi-agent systems, and agent orchestration with CrewAI, LangGraph, and custom agents.

Expert in designing and building autonomous AI agents. Masters tool use, memory systems, planning strategies, and multi-agent orchestration.

AI驱动的综合健康分析系统，整合多维度健康数据、识别异常模式、整理风险因素、提供一般性健康信息。支持智能问答和AI健康报告生成。

Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations.

Convert human-written CLAUDE.md into AI-native structured-label format. Propose and evaluate structured-label rewrites while preserving rule meaning; benefits require measured evidence.

AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.

Design and evaluate LLM product features, retrieval, validated outputs, latency, and cost controls.

Build production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs.