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Oh My Agent: Cross-Platform Multi-Agent Collaboration Framework, Empowering AI Assistants with Professional Teams

A portable multi-agent collaboration framework that supports running in various AI IDEs such as Antigravity, Claude Code, Cursor, and Codex CLI. It enables collaboration among specialized agents (frontend, backend, QA, PM, etc.) through role division and includes built-in quality gates and code review processes.

多智能体AI IDEClaude CodeCursorCodex智能体协作代码审查工作流编排
Published 2026-04-04 16:16Recent activity 2026-04-04 16:25Estimated read 6 min
Oh My Agent: Cross-Platform Multi-Agent Collaboration Framework, Empowering AI Assistants with Professional Teams
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Section 01

Oh My Agent: Cross-Platform Multi-Agent Collaboration Framework (Main Guide)

Oh My Agent is a portable multi-agent collaboration framework supporting Antigravity, Claude Code, Cursor, Codex CLI and other AI IDEs. It simulates real engineering teams through role specialization (PM, frontend, backend, QA, etc.) and includes built-in quality gates and code review processes. Its core goal is to address the limitations of single-agent AI programming assistants in complex projects.

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Section 02

Background: Limitations of Single-Agent AI Assistants

Current mainstream AI programming assistants use a single-agent mode, which works for simple tasks but faces challenges in complex projects:

  1. Domain knowledge dispersion: General models lack depth in specific fields.
  2. Context overload: Difficult to maintain a global view in limited context windows.
  3. Quality issues: No systematic review mechanism leads to potential vulnerabilities or non-compliance.
  4. Low collaboration efficiency: Manual coordination of multiple perspectives is tedious and error-prone.
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Section 03

Core Methods: Role Specialization & Portable Design

  1. Role specialization: Abstracted into specialized agents (oma-pm, oma-frontend, oma-backend, oma-db, oma-qa, etc.) with clear responsibilities.
  2. Portable .agents directory: Stores agent definitions, skills, and workflows in the project root (version-controlled), enabling cross-IDE compatibility, team consistency, and environment consistency.
  3. Double-layer skill design: Domain skills (depth in specific areas, loaded on demand) and common skills (shared, saving ~75% token consumption).
  4. Workflow orchestration: Sequential (coordinate), parallel (orchestrate), and ultrawork (5-stage quality workflow with 11 gates).
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Section 04

Key Features: Quality Assurance & Interaction Methods

  1. Quality gates: Charter preflight (check project charter before tasks), automated review (OWASP scan, performance audit, accessibility check, code style verification), and structured debug workflow.
  2. Interaction methods: Natural language trigger (keywords like 'plan'/'review'/'debug'), slash commands (e.g., /plan, /coordinate, /review), and CLI tool (oma: doctor, dashboard, spawn agents).
  3. Multi-vendor support: Configure different models for agents (Claude/Codex for frontend, Gemini for brainstorming, Qwen for QA).
  4. Observability: Terminal/Web panels show agent status, progress, token consumption, and logs.
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Section 05

Application Scenarios

  1. Full-stack project development: Use Fullstack preset for PM planning, backend/frontend development, DB design, and QA review.
  2. Infrastructure as Code: DevOps preset with Terraform agent for multi-cloud configuration and CI/CD management.
  3. Code review & refactoring: /review for pre-submit checks, /debug for legacy code analysis.
  4. Multi-language projects: oma-translator for multi-language documentation and internationalization code.
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Section 06

Limitations & Challenges

  1. Configuration complexity: Requires understanding agent roles and collaboration for full potential; overkill for simple tasks.
  2. IDE compatibility: Advanced features may be limited in some IDEs due to API differences.
  3. Token consumption: Higher than single-agent (optimized via double-layer skills but still significant).
  4. Debug difficulty: Harder to locate issues in multi-agent workflows.
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Section 07

Conclusion & Outlook

Oh My Agent represents the evolution of AI-assisted programming from single assistants to team collaboration. It solves single-agent bottlenecks in complex projects and ensures practicality and reliability through portable design and quality gates. For teams needing high-quality code and handling complex projects, it is a worthy solution. Future prospects: Wider application as the AI IDE ecosystem matures, forming new human-AI collaboration paradigms.