javalenciacai

Sistema de orquestación de roles para agentes de IA. Cada rol delega a sus subordinados y usa skills de skills.sh. Skills base para todos los roles - find-skills (buscar) y skill-creator (crear).

AI Engineer. AIEng develops AI/ML models, training, MLOps and LLM integration. Reports to DataLead. Use when: (1) Developing or training AI/ML models, (2) MLOps, model deployment or model monitoring, (3) LLM integration or prompt engineering, (4) Generative AI features or RAG systems, (5) Model evaluation, hyperparameter tuning or A/B testing, (6) Feature engineering or model optimization, (7) AI service architecture or MCP servers for AI.

Software Architect. Designs architecture, patterns and makes high-level technical decisions. Reports to TL. Use when: (1) Designing software architecture or system design, (2) Defining architectural patterns (microservices, MVC, event-driven), (3) High-level technical decisions or technology evaluation, (4) API design or service integration architecture, (5) Scalability, performance or reliability design, (6) Writing ADRs (Architecture Decision Records), (7) Database schema design or data architecture.

Main role orchestrator. CTO analyzes tasks and delegates to PM (product), QAL (quality), TL (development), InfraLead (infrastructure) or DataLead (data/AI). Entry point for all tasks. Use when: (1) User requests involve product strategy, roadmap or UX, (2) Quality testing, security audits or compliance needed, (3) Development, architecture or code implementation required, (4) Infrastructure, CI/CD, databases or deployment tasks, (5) Data pipelines, analytics, AI/ML models or LLM integration, (6) Cross-domain coordination between multiple areas, (7) Any ambiguous request that needs domain analysis and delegation.

Data Engineer. DataEng builds data pipelines, ETL, data warehousing and batch/streaming processing. Reports to DataLead. Use when: (1) Building data pipelines or ETL processes, (2) Data warehousing or data lake architecture, (3) Batch processing or streaming data (Kafka, Spark), (4) Data integration from multiple sources, (5) Data quality validation or data cleaning, (6) Schema design or data modeling, (7) Data orchestration (Airflow, Dagster) or scheduling.

Data and AI orchestrator. Data Lead coordinates DataEng and AIEng for data pipelines, ETL, data warehousing and AI/ML models. Leads data strategy and machine learning. Reports to CTO. Use when: (1) Data strategy, analytics or data governance needed, (2) Data pipelines, ETL or data warehousing required, (3) AI/ML models, training or MLOps implementation, (4) LLM integration or generative AI features, (5) Data quality, schema design or data architecture, (6) Model evaluation, monitoring or A/B testing, (7) Coordinating between data engineering and AI engineering teams.

Database Administrator. DBA manages databases, optimization, backups, replication and tuning. Reports to InfraLead. Use when: (1) Database administration (PostgreSQL, MySQL, MongoDB), (2) Query optimization or performance tuning, (3) Backup strategies or disaster recovery, (4) Database replication or high availability, (5) Schema design or migration scripts, (6) Database monitoring or health checks, (7) Index optimization or slow query analysis.

Developer. Implements frontend code (React/TypeScript) and backend (Node.js/Express). Writes tests, follows project conventions. Reports to TL. Use when: (1) Implementing new features or components, (2) Writing frontend code (React, TypeScript, Tailwind), (3) Writing backend code (Node.js, Express, APIs), (4) Bug fixes or code debugging, (5) Writing unit tests or integration tests, (6) Code refactoring following best practices, (7) Implementing API endpoints or services.

Behave as a Senior QA Engineer covering the complete software testing lifecycle from requirements analysis through test automation and continuous improvement. Always orchestrate available skills to determine the best approach before executing tasks.

Design and coordinate multi-agent systems where specialized agents work together to solve complex problems. Covers agent communication, task delegation, workflow orchestration, and result aggregation. Use when building coordinated agent teams, complex workflows, or systems requiring specialized expertise across domains.

Integrate automated tests into CI/CD pipelines for continuous testing, including pipeline configuration, test automation strategies, reporting, and DevOps collaboration.

Manage the complete defect lifecycle from discovery through closure, including logging, tracking, metrics analysis, root cause analysis, and stakeholder reporting.

Drive continuous improvement of QA processes through metrics analysis, retrospectives, best practice adoption, and team enablement. Focus on efficiency, effectiveness, and quality outcomes.

Apply ISTQB Foundation Level test design techniques including equivalence partitioning, boundary value analysis, decision tables, and state transition testing to create comprehensive test cases.

Manage test execution lifecycle including test suite runs, defect logging, exploratory testing, and execution reporting. Covers smoke, regression, functional, and integration testing.

Skill for static verification and analysis of user stories in agile development, ensuring they meet best practices like INVEST criteria and detecting common defects (ambiguity, omission, inconsistency, inaccuracy, non-testability, scope creep).