Skill UI

A sophisticated AI system that coordinates multiple specialized agents (e.g., Security Auditors, Performance Analysts, Architecture Specialists) to perform comprehensive, multi-perspective code assessments. It analyzes code context, manages state, and synthesizes conflicting insights to provide deep, holistic reviews for complex software projects.

This skill implements an autonomous, multi-round research review loop, simulating the rigorous peer-review process of top-tier conferences. It iteratively reviews, identifies weaknesses, suggests fixes, and re-reviews a research document using the MiniMax API. The system manages state persistence across multiple rounds, ensuring continuous improvement until a 'ready' assessment is achieved or the maximum round limit is reached. Ideal for academic writing, thesis refinement, or comprehensive project documentation.

Share durable context and handoffs between AI agents like Claude and Codex via the local ECC Memory Vault. Use this skill to save work state, transfer context, resume tasks, or search shared project knowledge across different agent harnesses.

Andru.ia's principal solutions architect skill. Diagnoses workspace state, distinguishes new (Pure Engine) from existing (Evolution) projects, and sets optimal technical roadmap and expert squad for Spanish-language AI projects. Generates tareas.md and plan_implementacion.md artifacts.

Main orchestrator agent that routes tasks across a specialized squad (analyst, architect, builder, reviewer, QA, DevOps). It keeps compressed summaries, stores full artifacts by reference, tracks project state, and conserves its context window.

This skill covers principles for identifying tasks suited to LLM processing, designing effective project architectures, and iterating rapidly using agent-assisted development. It applies to batch pipelines, multi-agent systems, and interactive applications. Key concepts include task-model fit recognition, manual prototyping, pipeline architecture, file system state management, and structured output design for reliable parsing.