agentuity-cli-profile-show
Show the configuration of a profile
agentuity-cli-profile-use
Switch to a different configuration profile
agentuity-cli-project-auth-generate
Generate SQL schema for Agentuity Auth tables. Use for managing authentication credentials
agentuity-cli-project-auth-init
Set up Agentuity Auth for your project. Requires authentication. Use for managing authentication credentials
agentuity-cli-project-create
Create a new project. Use for project management operations
agentuity-cli-project-delete
Delete a project. Requires authentication. Use for project management operations
agentuity-cli-project-import
Import or register a local project with Agentuity Cloud. Requires authentication. Use for project management operations
agentuity-cli-project-list
List all projects. Requires authentication. Use for project management operations
agentuity-cli-project-show
Show project detail. Requires authentication. Use for project management operations
agentuity-cli-repl
interactive REPL for testing
agentuity-cli-upgrade
Upgrade the CLI to the latest version
agentv-eval-builder
Create and maintain AgentV YAML evaluation files for testing AI agent performance. Use this skill when creating new eval files, adding eval cases, or configuring custom evaluators (code validators or LLM judges) for agent testing workflows.
aggregates
Regla 05: Aggregates y Aggregate Roots. Use when implementing DDD patterns.
aggregating-crypto-news
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agregadores-performance-potencial
Use para implementar serviços de agregação que calculam os eixos de Performance e Potencial a partir de evidências.
agent-workflow-playbook
Guide plan → instrument → execute → validate with explicit checkpoints and questions. Use for ambiguous tasks or when enforcing a consistent agent workflow.
agent-workflow-patterns
AI agent workflow patterns including ReAct agents, multi-agent systems, loop control, tool orchestration, and autonomous agent architectures. Use when building AI agents, implementing workflows, creating autonomous systems, or when user mentions agents, workflows, ReAct, multi-step reasoning, loop control, agent orchestration, or autonomous AI.
agent-memory
Retain and recall work context across sessions. Use when user asks to remember something, recall previous work, or reference past discussions. Triggered by phrases like 'remember this', 'save for later', 'recall', 'what did we discuss about'.
agent-memory-mcp
A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).
agent-memory-systems
Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector stores), and the cognitive architectures that organize them. Key insight: Memory isn't just storage - it's retrieval. A million stored facts mean nothing if you can't find the right one. Chunking, embedding, and retrieval strategies determine whether your agent remembers or forgets. The field is fragm
agent-messaging
Send and receive messages between AI agents using AI Maestro's messaging system. Use this skill when the user asks to "send a message", "check inbox", "read messages", "notify [agent]", "tell [agent]", or any inter-agent communication.
agent-microservices-architect
Distributed systems architect designing scalable microservice ecosystems. Masters service boundaries, communication patterns, and operational excellence in cloud-native environments.
agent-ml-engineer
Expert ML engineer specializing in machine learning model lifecycle, production deployment, and ML system optimization. Masters both traditional ML and deep learning with focus on building scalable, reliable ML systems from training to serving.
agent-mlops-engineer
Expert MLOps engineer specializing in ML infrastructure, platform engineering, and operational excellence for machine learning systems. Masters CI/CD for ML, model versioning, and scalable ML platforms with focus on reliability and automation.
agent-mlops
Production deployment and operationalization of AI agents on Databricks. Use when deploying agents to Model Serving, setting up MLflow logging and tracing for agents, implementing Agent Evaluation frameworks, monitoring agent performance in production, managing agent versions and rollbacks, optimizing agent costs and latency, or establishing CI/CD pipelines for agents. Covers MLflow integration patterns, evaluation best practices, Model Serving configuration, and production monitoring strategies.
agent-mobile-app-developer
Expert mobile app developer specializing in native and cross-platform development for iOS and Android. Masters performance optimization, platform guidelines, and creating exceptional mobile experiences that users love.
agent-mobile-developer
Cross-platform mobile specialist building performant native experiences. Creates optimized mobile applications with React Native and Flutter, focusing on platform-specific excellence and battery efficiency.
agent-model-selection
Guidelines for selecting appropriate AI model (Sonnet vs Haiku) based on task complexity, ensuring cost efficiency while maintaining quality. Use when assigning work.
agent-native-architecture
Build applications where agents are first-class citizens. Use this skill when designing autonomous agents, creating MCP tools, implementing self-modifying systems, or building apps where features are outcomes achieved by agents operating in a loop.
agent-network-engineer
Expert network engineer specializing in cloud and hybrid network architectures, security, and performance optimization. Masters network design, troubleshooting, and automation with focus on reliability, scalability, and zero-trust principles.
agent-nextjs-developer
Expert Next.js developer mastering Next.js 14+ with App Router and full-stack features. Specializes in server components, server actions, performance optimization, and production deployment with focus on building fast, SEO-friendly applications.
agent-nlp-engineer
Expert NLP engineer specializing in natural language processing, understanding, and generation. Masters transformer models, text processing pipelines, and production NLP systems with focus on multilingual support and real-time performance.
agent-o-rama
Layer 4: Learning and Pattern Extraction for Cognitive Surrogate Systems
agent-observability
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agent-ops-api-review
Platform/Language agnostic API delivery and correctness auditor. Use when project contains API endpoints to verify contract alignment, endpoint behavior, and test coverage.
agent-ops-baseline
Create .agent/baseline.md and later compare against it. Use when capturing baseline build/lint/test results or investigating newly introduced findings.
agent-ops-build
Language-aware build orchestration that detects project language and runs appropriate build pipeline
agent-ops-context-map
Analyze the codebase to create a concise, LLM-optimized structured overview in .agent/map.md.
agent-ops-debugging
Systematic debugging approaches for isolating and fixing software defects. Use when something isn't working and the cause is unclear.
agent-ops-docs
Documentation management for README, CHANGELOG, API docs, and user-facing documentation. Use when creating or updating project documentation.
agent-ops-dogfood
Dogfooding discovery agent — establish human-approved project baseline from public docs without code inspection
agent-ops-focus-scan
Analyze issues to identify the next work item and update focus.md. Enforces issue-first workflow and confidence-based batch limits.
agent-ops-git-story
Generate narrative summaries from git history for onboarding, retrospectives, changelogs, and exploration. LLM-enhanced when available, works without LLM too.
agent-ops-git-worktree
Manage git worktrees for isolated development. Create, list, remove, and work in worktrees.
agent-ops-git
Manage git operations safely. Includes stale state detection, branch/commit management. Never pushes without explicit user confirmation.
agent-ops-github
Bidirectional sync between agent-ops issues and GitHub Issues
agent-ops-guide
Interactive workflow guide. Use when user is unsure what to do next, needs help navigating AgentOps, or wants to understand available tools.
agent-ops-housekeeping
Comprehensive project hygiene: archive issues, validate schema, clean clutter, align docs, check git, update ignores.
agent-ops-idea
Capture loosely structured ideas, enrich with research, and create backlog issues. Use when user has a raw concept that needs fleshing out.
agent-ops-impl-details
Extract, plan, or propose implementation details at configurable depth levels (low/normal/extensive). Outputs to reference files for team discussion and handoff.
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