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omo - Multi-Agent Orchestration

OmO is a multi-agent orchestration skill that routes tasks to specialized agents based on risk signals.

Installation

python install.py --module omo

Usage

/omo <your task>

Agent Hierarchy

Agent Role Backend Model
oracle Technical advisor claude claude-opus-4-5
librarian External research claude claude-sonnet-4-5
explore Codebase search opencode grok-code
develop Code implementation codex gpt-5.2
frontend-ui-ux-engineer UI/UX specialist gemini gemini-3-pro
document-writer Documentation gemini gemini-3-flash

Routing Signals (Not Fixed Pipeline)

This skill is routing-first, not a mandatory conveyor belt.

Signal Add Agent
Code location/behavior unclear explore
External library/API usage unclear librarian
Risky change (multi-file, public API, security, perf) oracle
Implementation required develop / frontend-ui-ux-engineer
Documentation needed document-writer

Skipping Heuristics

  • Skip explore when exact file path + line number is known
  • Skip oracle when change is local + low-risk (single area, clear fix)
  • Skip implementation agents when user only wants analysis

Common Recipes

Task Recipe
Explain code explore
Small fix with known location develop directly
Bug fix, location unknown explore → develop
Cross-cutting refactor explore → oracle → develop
External API integration explore + librarian → oracle → develop
UI-only change explore → frontend-ui-ux-engineer
Docs-only change explore → document-writer

Context Pack Template

Every agent invocation includes:

## Original User Request
<original request>

## Context Pack (include anything relevant; write "None" if absent)
- Explore output: <...>
- Librarian output: <...>
- Oracle output: <...>
- Known constraints: <tests to run, time budget, repo conventions>

## Current Task
<specific task description>

## Acceptance Criteria
<clear completion conditions>

Agent Invocation

codeagent-wrapper --agent <agent_name> - <workdir> <<'EOF'
## Original User Request
...

## Context Pack
...

## Current Task
...

## Acceptance Criteria
...
EOF

Timeout: 2 hours.

Examples

# Analysis only
/omo how does this function work?
# → explore

# Bug fix with unknown location
/omo fix the authentication bug
# → explore → develop

# Feature with external API
/omo add Stripe payment integration
# → explore + librarian → oracle → develop

# UI change
/omo redesign the dashboard layout
# → explore → frontend-ui-ux-engineer

Configuration

Agent-model mappings in ~/.codeagent/models.json:

{
  "default_backend": "codex",
  "default_model": "gpt-5.2",
  "agents": {
    "oracle": {
      "backend": "claude",
      "model": "claude-opus-4-5-20251101",
      "yolo": true
    },
    "librarian": {
      "backend": "claude",
      "model": "claude-sonnet-4-5-20250929",
      "yolo": true
    },
    "explore": {
      "backend": "opencode",
      "model": "opencode/grok-code"
    },
    "frontend-ui-ux-engineer": {
      "backend": "gemini",
      "model": "gemini-3-pro-preview"
    },
    "document-writer": {
      "backend": "gemini",
      "model": "gemini-3-flash-preview"
    },
    "develop": {
      "backend": "codex",
      "model": "gpt-5.2",
      "yolo": true,
      "reasoning": "xhigh"
    }
  }
}

Hard Constraints

  1. Never write code yourself - delegate to implementation agents
  2. Always pass context forward - include original request + prior outputs
  3. No direct grep/glob for non-trivial exploration - use explore
  4. No external docs guessing - use librarian
  5. Use fewest agents possible - skipping is normal

Requirements

  • codeagent-wrapper with --agent support
  • Backend CLIs: claude, opencode, codex, gemini