oh-my-agent: Portable Multi-Agent Harness

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Ever wished your AI assistant had coworkers? That's what oh-my-agent does.

Instead of one AI doing everything (and getting confused halfway through), oh-my-agent splits work across specialized agents — frontend, backend, architecture, QA, PM, DB, mobile, infra, debug, design, and more. Each one knows its domain deeply, has its own tools and checklists, and stays in its lane.

Works with all major AI IDEs: Antigravity, Claude Code, Codex, Cursor, Grok Build, Kimi Code, OpenCode, Pi, Qwen Code, and more.

Quick Start

# macOS / Linux — auto-installs bun, uv & serena if missing
curl -fsSL https://raw.githubusercontent.com/first-fluke/oh-my-agent/main/cli/install.sh | bash

# Windows (PowerShell) — auto-installs bun, uv & serena if missing
irm https://raw.githubusercontent.com/first-fluke/oh-my-agent/main/cli/install.ps1 | iex

# Or manual (any OS, requires bun + uv + serena)
bunx oh-my-agent@latest

Install via Agent Package Manager

Not to be confused with oma-observability's APM (Application Performance Monitoring).

# All skills, deployed to every detected runtime
# (.claude, .cursor, .codex, .opencode, .github, .agents)
apm install first-fluke/oh-my-agent

# A single skill
apm install first-fluke/oh-my-agent/.agents/skills/oma-frontend

APM ships skills only. For workflows, rules, oma-config.yaml, keyword-detection hooks, and the oma agent:spawn CLI, use bunx oh-my-agent@latest. Pick one distribution per project to avoid drift.

Pick a preset and you're ready:

| Preset | What You Get | |--------|-------------| | All | Every agent and skill | | Backend | architecture + backend + brainstorm + db + debug + dev-workflow + pm + qa + scm | | Content | academic-writer + design + image + scm + translator + voice | | DevOps | architecture + brainstorm + debug + dev-workflow + observability + pm + qa + scm + tf-infra | | Frontend | architecture + brainstorm + debug + design + frontend + pm + qa + scm | | Fullstack | architecture + backend + brainstorm + db + debug + design + dev-workflow + frontend + mobile + pm + qa + scm + tf-infra | | Fullstack Mobile | architecture + backend + brainstorm + db + debug + design + dev-workflow + mobile + pm + qa + scm | | Fullstack Web | architecture + backend + brainstorm + db + debug + design + dev-workflow + frontend + pm + qa + scm | | Mobile | architecture + brainstorm + debug + mobile + pm + qa + scm | | Research | academic-writer + hwp + market + pdf + scholar + scm + search + translator |

Works With Every Agent

oh-my-agent keeps .agents/ as the single source of truth and projects it into each runtime's native layout, so every supported tool shares the same skills, workflows, and rules.

Your Agent Team

| Agent | What They Do | |-------|-------------| | oma-academic-writer | Drafts, revises, and audits academic prose to publication quality. | | oma-architecture | Weighs architecture tradeoffs and draws module boundaries, with ADR/ATAM/CBAM analysis. | | oma-backend | Builds and secures your APIs in Python, Node.js, or Rust. | | oma-brainstorm | Explores ideas with you before you commit to building. | | oma-db | Designs your schema, migrations, indexes, and vector stores. | | oma-debug | Finds the root cause, fixes the bug, and writes a regression test. | | oma-deepsec | Scans your code for security holes and blocks risky pull requests. | | oma-design | Builds design systems with tokens, accessibility, and responsive layouts. | | oma-dev-workflow | Automates your CI/CD, releases, and monorepo tasks. | | oma-docs | Checks your docs for broken references and flags ones a code change touched. | | oma-frontend | Builds your UI with React/Next.js, TypeScript, Tailwind CSS v4, and shadcn/ui. | | oma-hwp | Converts HWP, HWPX, and HWPML files to Markdown. | | oma-image | Generates images through several AI providers at once. | | oma-market | Researches your market from community signals and frames it with SWOT, 5F, and PESTEL. | | oma-mobile | Builds cross-platform mobile apps with Flutter. | | oma-observability | Routes observability work across metrics, logs, traces, SLOs, and incident forensics. | | oma-orchestrator | Runs multiple agents in parallel from the CLI. | | oma-pdf | Converts PDF files to Markdown. | | oma-pm | Plans tasks, breaks down requirements, and defines API contracts. | | oma-qa | Reviews your code for OWASP security, performance, and accessibility issues. | | oma-recap | Recaps your conversation history into themed work summaries. | | oma-refactor | Refactors code without changing its behavior, using hotspot targeting, characterization-test safety nets, and refactor-only commits. | | oma-scholar | Searches academic literature and helps you run peer review. | | oma-scm | Manages your branches, merges, worktrees, and Conventional Commits. | | oma-search | Routes each query to the best source and scores how much you can trust the result. | | oma-slide | Generates distinctive, animation-rich HTML presentation decks and exports to PDF/PNG/PPTX. | | oma-tf-infra | Provisions multi-cloud infrastructure with Terraform. | | oma-translator | Translates between languages so it reads like a native wrote it. | | oma-video | Generates short-form, explainer, and demo videos through a key-optional Remotion pipeline. | | oma-voice | Generates voiceovers and transcribes audio on-device, no cloud needed. |

| Agent | What They Do | |-------|-------------| | oma-coordination | Guides manual step-by-step coordination of PM, frontend, backend, mobile, and QA agents. | | oma-skill-creator | Writes and audits new OMA skills in the SSL-lite format. |

How It Works

Just chat. Describe what you want and oh-my-agent figures out which agents to use.

You: "Build a TODO app with user authentication"
→ PM plans the work
→ Backend builds auth API
→ Frontend builds React UI
→ DB designs schema
→ QA reviews everything
→ Done: coordinated, reviewed code

Or use slash commands for structured workflows:

| Step | Command | What It Does | |------|---------|-------------| | 0 | /deepinit | Maps your existing codebase into AGENTS.md, ARCHITECTURE.md, and docs | | 1 | /brainstorm | Explores ideas with you before you commit to building | | 2 | /architecture | Weighs your design tradeoffs and draws clean module boundaries | | 2 | /design | Builds your design system with tokens, accessibility, and responsive layouts | | 2 | /plan | Breaks your feature down into prioritized tasks | | 3 | /work | Builds your feature step by step across multiple agents | | 3 | /orchestrate | Runs multiple agents in parallel to build your feature faster | | 3 | /ultrawork | Builds your feature through five gated quality phases; every review runs in a fresh, isolated reviewer session (cross-context review) | | 3 | /ralph | Repeats /ultrawork until an independent verifier passes every criterion | | 4 | /review | Reviews your code for security, performance, and accessibility issues | | 4 | /deepsec | Runs a deep security scan and blocks risky pull requests | | 5 | /debug | Finds the root cause, fixes the bug, and writes a regression test | | 5 | /docs | Checks your docs for broken references and patches the ones your code changes touched | | 6 | /scm | Manages your branches, merges, and Conventional Commits | | - | /schedule | Schedules an agent job to run on a recurring interval |

Auto-detection: You don't even need slash commands — keywords like "architecture", "plan", "review", and "debug" in your message (in 11 languages!) auto-activate the right workflow. Detection accuracy is measured, not assumed: oma verify triggers scores the detector against a labeled 171-prompt corpus (currently 0% missed-fire, under 10% false-fire) and gates CI on it.

Per-Agent Models

Set model_preset in .agents/oma-config.yaml to choose which AI models each agent uses:

language: en
model_preset: mixed   # antigravity | claude | codex | cursor | kiro | mixed | qwen

# Optional per-agent overrides
agents:
  backend: { model: openai/gpt-5.5, effort: high }

• oma doctor --profile — prints the per-role resolved model matrix
• Full guide: web/docs/guide/per-agent-models.md

Why oh-my-agent?

• Portable — .agents/ travels with your project, not trapped in one IDE. oma emit projects the same SSOT into open-standard artifacts — Agent Skills-conformant skill folders, a .claude-plugin/marketplace.json, and AGENTS.md — so oma skills work in any tool that reads the open spec, with a drift check in CI keeping the generated output honest
• Role-based — Agents modeled like a real engineering team, not a pile of prompts
• Token-efficient — Two-layer skill design saves ~75% of tokens (how it works)
• Quality-first — Charter preflight, quality gates, and review workflows built in:
  • oma verify <agent> — a deterministic check battery per agent type: a shared core (scope violation, charter alignment, hardcoded secrets, TODO scan, declared outputs) plus type-specific checks (TypeScript strict, tests, raw SQL, Flutter analyze, inline styles, …)
  • session.quota_cap — per-session token / spawn / per-vendor budget caps in oma-config.yaml; orchestrate Step 5 blocks the next spawn when exceeded
  • ralph workflow — independent JUDGE re-verifies every criterion each iteration to catch silent regressions; heavy-test caching for >30s suites
  • Exploration Loop — after 2 retries, orchestrate spawns hypothesis variants in parallel and keeps the highest-scoring result
  • Monorepo auto-routing — detectWorkspace reads pnpm / nx / turbo / lerna and routes each agent to its workspace
• Multi-vendor — Mix Antigravity, Claude, Codex, Cursor, Kiro, and Qwen per agent type
• Observable — Terminal and web dashboards for real-time monitoring

Architecture

flowchart TD
    subgraph Workflows["Workflows"]
        direction TB
        W0["/brainstorm"]
        W1["/work"]
        W1b["/ultrawork"]
        W2["/orchestrate"]
        W3["/architecture"]
        W4["/plan"]
        W5["/review"]
        W6["/debug"]
        W7["/deepinit"]
        W8["/design"]
    end

    subgraph Orchestration["Orchestration"]
        direction TB
        PM[oma-pm]
        ORC[oma-orchestrator]
    end

    subgraph Domain["Domain Agents"]
        direction TB
        ARC[oma-architecture]
        FE[oma-frontend]
        BE[oma-backend]
        DB[oma-db]
        MB[oma-mobile]
        DES[oma-design]
        TF[oma-tf-infra]
    end

    subgraph Quality["Quality"]
        direction TB
        QA[oma-qa]
        DBG[oma-debug]
    end

    Workflows --> Orchestration
    Orchestration --> Domain
    Domain --> Quality
    Quality --> SCM([oma-scm])

Learn More

• Detailed Documentation — Full technical spec and architecture
• Supported Agents — Agent support matrix across IDEs
• Web Docs — Guides, tutorials, and CLI reference

Sponsors

This project is maintained thanks to our generous sponsors.

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References

• Li, X., Liu, Y., Chen, W., You, B., Di, Z., He, Y., Zheng, S., Choe, K. W., Sun, J., Wang, S., Tao, C., Li, B., Zhao, X., Geng, H., Wu, X., Zhou, J., Chen, X., Xing, H., Li, Y., … Song, D. (2026). SkillsBench: Benchmarking how well agent skills work across diverse tasks (Version 4) [Preprint]. arXiv. https://doi.org/10.48550/arXiv.2602.12670
• Liang, Q., Wang, H., Liang, Z., & Liu, Y. (2026). From skill text to skill structure: The scheduling-structural-logical representation for agent skills (Version 4) [Preprint]. arXiv. https://doi.org/10.48550/arXiv.2604.24026
• Chen, C., Yu, Q., Gu, Y., Huang, Z., Li, H., Liu, H., Liu, S., Liu, J., Peng, D., Wang, J., Yan, Z., Meng, F., Qin, E., Che, C., & Hu, M. (2026). The scaling laws of skills in LLM agent systems (Version 1) [Preprint]. arXiv. https://doi.org/10.48550/arXiv.2605.16508
• Yang, Y., Gong, Z., Huang, W., Yang, Q., Zhou, Z., Huang, Z., Li, Y., Gao, X., Dai, Q., Liu, B., Qiu, K., Yang, Y., Chen, D., Yang, X., & Luo, C. (2026). SkillOpt: Executive strategy for self-evolving agent skills (Version 2) [Preprint]. arXiv. https://doi.org/10.48550/arXiv.2605.23904
• Huang, Z., Xu, J., Yang, Y., Gong, Z., Yang, Q., Tian, M., Wang, X., Lv, C., Gao, X., Dai, Q., Liu, B., Qiu, K., Yang, X., Chen, D., Zheng, X., & Luo, C. (2026). From raw experience to skill consumption: A systematic study of model-generated agent skills [Preprint]. arXiv. https://doi.org/10.48550/arXiv.2605.23899
• Hong, D. B., Imani, A., & Ahmed, I. (2026). From anatomy to smells: An empirical study of SKILL.md in agent skills (Version 2) [Preprint]. arXiv. https://doi.org/10.48550/arXiv.2607.01456

License

MIT