Use this agent for any n8n development task - frontend (Vue 3), backend (Node.js/TypeScript), workflow engine, node creation, or full-stack features. The agent automatically applies n8n conventions and best practices. Examples: user: 'Add a new button to the workflow editor' assistant: 'I'll use the developer agent to…
Use this agent proactively when a Linear issue is created, updated, or needs comprehensive analysis. This agent performs thorough issue investigation and triage including root cause analysis, severity assessment, and implementation scope identification.
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
Reviews code for project guideline compliance, bugs, and quality issues. Use after writing code, before commits, or before PRs. Specify files to review or defaults to unstaged git changes. High-confidence issues only (80+) to minimize noise.
Comprehensive codebase exploration - finds WHERE code lives AND shows HOW it's implemented. Use when you need to locate files, understand directory structure, AND extract actual code patterns. Combines file finding with pattern extraction in one pass.
Autonomous code quality agent that scans for rule violations, fixes them in an isolated worktree, runs validation, creates a PR, and updates memory with findings for future runs.
This document describes how the unified three-layer Device Agent architecture is implemented across different platforms. While the core framework (State, Processor, Command layers) remains consistent, each platform implements specialized agents optimized for their native control mechanisms and hierarchies.…
Device Agents are the execution engines of UFO3's multi-device orchestration system. Each device agent operates as an autonomous, intelligent controller that translates high-level user intentions into low-level system commands. The architecture is designed for extensibility, safety, and scalability across…
Device agents in UFO are partitioned into server and client components, separating high-level orchestration from low-level execution. This architecture enables safe, scalable, and flexible task execution across heterogeneous devices through the Agent Interaction Protocol (AIP).
The planning agent ecosystem consists of five specialized agents that work together to transform feature requirements into actionable implementation plans.
Repository-specific testing traps you cannot learn from the test runner alone. Executable gate ownership lives in scripts/check-affected/ and scripts/gate/.