Multi-Agent Workflow Guide
Scheduling
Goal
Guide manual multi-agent coordination for complex work that spans PM, frontend, backend, mobile, and QA responsibilities.
Intent signature
- User wants step-by-step coordination, manual agent spawning, or multi-domain work planning without full automation.
- Task spans multiple specialist agents and requires contract alignment.
When to use
- Complex feature spanning multiple domains (full-stack, mobile)
- Coordination needed between frontend, backend, mobile, and QA
- User wants step-by-step guidance for multi-agent coordination
When NOT to use
- Simple single-domain task -> use the specific agent directly
- User wants automated execution -> use orchestrator
- Quick bug fixes or minor changes
Expected inputs
- Complex feature or project goal
- Required domains and priority tiers
- Workspace/session constraints and API/data contract needs
Expected outputs
- Manual coordination sequence
- PM task decomposition, agent spawn order, monitoring guidance, and QA review step
- API/data contract alignment checkpoints
Dependencies
- PM, frontend, backend, mobile, QA, and orchestrator skills
resources/examples.md
- CLI
oma agent:spawn and progress/result memory conventions
Control-flow features
- Branches by task complexity, priority tiers, dependency ordering, and whether automation is desired
- Spawns independent same-priority tasks in parallel when appropriate
- Monitors progress files and contract alignment
Structural Flow
Entry
- Confirm the task is complex enough for multi-agent coordination.
- Start with PM task decomposition.
- Identify priority tiers and shared contracts.
Scenes
- PREPARE: Define session, domains, and task decomposition needs.
- ACT: Spawn agents by priority with separate workspaces.
- VERIFY: Monitor progress and API/data contract alignment.
- FINALIZE: Run QA review and coordinate remediation.
Transitions
- If task is simple, route to one specialist.
- If user wants automated execution, use orchestrator.
- If QA finds CRITICAL issues, re-spawn responsible agents.
Failure and recovery
- If contracts diverge, pause downstream frontend/mobile work until backend/API contract is reconciled.
- If agent workspaces conflict, split ownership boundaries.
- If progress stalls, inspect progress files and reissue focused instructions.
Exit
- Success: specialist outputs are coordinated and QA-reviewed.
- Partial success: blocked agents, contract conflicts, or QA failures are explicit.
Logical Operations
Actions
| Action |
SSL primitive |
Evidence |
| Read request and domains |
READ |
User prompt and project context |
| Select agent plan |
SELECT |
PM decomposition and priority tiers |
| Spawn agents |
CALL_TOOL |
oma agent:spawn |
| Monitor progress |
READ |
progress-{agent}.md |
| Validate contracts |
VALIDATE |
API/data model alignment |
| Notify coordination status |
NOTIFY |
Final coordination summary |
Tools and instruments
oma agent:spawn, PM/frontend/backend/mobile/QA agents
- Memory/progress/result files
- Serena MCP for exploration and modification when used by specialists
Canonical command path
oma agent:spawn pm "<planning task>" <session-id> -w ./pm
oma agent:spawn backend "<backend task>" <session-id> -w ./backend &
oma agent:spawn frontend "<frontend task>" <session-id> -w ./frontend &
wait
Resource scope
| Scope |
Resource target |
LOCAL_FS |
Progress/result files and workspaces |
PROCESS |
Agent spawn commands |
MEMORY |
Session state and task board |
CODEBASE |
Shared contracts and implementation areas |
Preconditions
- Task requires multiple domains.
- PM decomposition can identify independent priority tiers.
Effects and side effects
- Spawns or guides multiple agents.
- Coordinates workspace ownership and QA feedback.
Guardrails
- Always start with PM Agent for task decomposition
- Spawn independent tasks in parallel (same priority tier)
- Define API contracts before frontend/mobile tasks
- QA review is always the final step
- Assign separate workspaces to avoid file conflicts
- Always use Serena MCP tools as the primary method for code exploration and modification
- Never skip steps in the workflow — follow each step sequentially without omission
Workflow
Step 1: Plan with PM Agent
PM Agent analyzes requirements, selects tech stack, creates task breakdown with priorities.
Step 2: Spawn Agents by Priority
Spawn agents via CLI:
- Use spawn-agent.sh for each task
- CLI selection follows agent_cli_mapping in oma-config.yaml
- Spawn all same-priority tasks in parallel using background processes
# Example: spawn backend and frontend in parallel
oma agent:spawn backend "task description" session-id -w ./backend &
oma agent:spawn frontend "task description" session-id -w ./frontend &
wait
Step 3: Monitor & Coordinate
- Use memory read tool to poll
progress-{agent}.md files
- Verify API contracts align between agents
- Ensure shared data models are consistent
Step 4: QA Review
Spawn QA Agent last to review all deliverables. Address CRITICAL issues by re-spawning agents.
Automated Alternative
For fully automated execution without manual spawning, use the orchestrator skill instead.
References
- Workflow examples:
resources/examples.md
1---2name: oma-coordination3description: Guide for coordinating PM, Frontend, Backend, Mobile, and QA agents on complex projects via CLI. Use for manual step-by-step coordination and workflow guidance.4---56# Multi-Agent Workflow Guide78## Scheduling910### Goal11Guide manual multi-agent coordination for complex work that spans PM, frontend, backend, mobile, and QA responsibilities.1213### Intent signature14- User wants step-by-step coordination, manual agent spawning, or multi-domain work planning without full automation.15- Task spans multiple specialist agents and requires contract alignment.1617### When to use1819- Complex feature spanning multiple domains (full-stack, mobile)20- Coordination needed between frontend, backend, mobile, and QA21- User wants step-by-step guidance for multi-agent coordination2223### When NOT to use2425- Simple single-domain task -> use the specific agent directly26- User wants automated execution -> use orchestrator27- Quick bug fixes or minor changes2829### Expected inputs30- Complex feature or project goal31- Required domains and priority tiers32- Workspace/session constraints and API/data contract needs3334### Expected outputs35- Manual coordination sequence36- PM task decomposition, agent spawn order, monitoring guidance, and QA review step37- API/data contract alignment checkpoints3839### Dependencies40- PM, frontend, backend, mobile, QA, and orchestrator skills41- `resources/examples.md`42- CLI `oma agent:spawn` and progress/result memory conventions4344### Control-flow features45- Branches by task complexity, priority tiers, dependency ordering, and whether automation is desired46- Spawns independent same-priority tasks in parallel when appropriate47- Monitors progress files and contract alignment4849## Structural Flow5051### Entry521. Confirm the task is complex enough for multi-agent coordination.532. Start with PM task decomposition.543. Identify priority tiers and shared contracts.5556### Scenes571. **PREPARE**: Define session, domains, and task decomposition needs.582. **ACT**: Spawn agents by priority with separate workspaces.593. **VERIFY**: Monitor progress and API/data contract alignment.604. **FINALIZE**: Run QA review and coordinate remediation.6162### Transitions63- If task is simple, route to one specialist.64- If user wants automated execution, use orchestrator.65- If QA finds CRITICAL issues, re-spawn responsible agents.6667### Failure and recovery68- If contracts diverge, pause downstream frontend/mobile work until backend/API contract is reconciled.69- If agent workspaces conflict, split ownership boundaries.70- If progress stalls, inspect progress files and reissue focused instructions.7172### Exit73- Success: specialist outputs are coordinated and QA-reviewed.74- Partial success: blocked agents, contract conflicts, or QA failures are explicit.7576## Logical Operations7778### Actions79| Action | SSL primitive | Evidence |80|--------|---------------|----------|81| Read request and domains | `READ` | User prompt and project context |82| Select agent plan | `SELECT` | PM decomposition and priority tiers |83| Spawn agents | `CALL_TOOL` | `oma agent:spawn` |84| Monitor progress | `READ` | `progress-{agent}.md` |85| Validate contracts | `VALIDATE` | API/data model alignment |86| Notify coordination status | `NOTIFY` | Final coordination summary |8788### Tools and instruments89- `oma agent:spawn`, PM/frontend/backend/mobile/QA agents90- Memory/progress/result files91- Serena MCP for exploration and modification when used by specialists9293### Canonical command path94```bash95oma agent:spawn pm "<planning task>" <session-id> -w ./pm96oma agent:spawn backend "<backend task>" <session-id> -w ./backend &97oma agent:spawn frontend "<frontend task>" <session-id> -w ./frontend &98wait99```100101### Resource scope102| Scope | Resource target |103|-------|-----------------|104| `LOCAL_FS` | Progress/result files and workspaces |105| `PROCESS` | Agent spawn commands |106| `MEMORY` | Session state and task board |107| `CODEBASE` | Shared contracts and implementation areas |108109### Preconditions110- Task requires multiple domains.111- PM decomposition can identify independent priority tiers.112113### Effects and side effects114- Spawns or guides multiple agents.115- Coordinates workspace ownership and QA feedback.116117### Guardrails1181191. Always start with PM Agent for task decomposition1202. Spawn independent tasks in parallel (same priority tier)1213. Define API contracts before frontend/mobile tasks1224. QA review is always the final step1235. Assign separate workspaces to avoid file conflicts1246. Always use Serena MCP tools as the primary method for code exploration and modification1257. Never skip steps in the workflow — follow each step sequentially without omission126127### Workflow128129### Step 1: Plan with PM Agent130131PM Agent analyzes requirements, selects tech stack, creates task breakdown with priorities.132133### Step 2: Spawn Agents by Priority134135Spawn agents via CLI:1361371. Use spawn-agent.sh for each task1382. CLI selection follows agent_cli_mapping in oma-config.yaml1393. Spawn all same-priority tasks in parallel using background processes140141```bash142# Example: spawn backend and frontend in parallel143oma agent:spawn backend "task description" session-id -w ./backend &144oma agent:spawn frontend "task description" session-id -w ./frontend &145wait146```147148### Step 3: Monitor & Coordinate149150- Use memory read tool to poll `progress-{agent}.md` files151- Verify API contracts align between agents152- Ensure shared data models are consistent153154### Step 4: QA Review155156Spawn QA Agent last to review all deliverables. Address CRITICAL issues by re-spawning agents.157158### Automated Alternative159160For fully automated execution without manual spawning, use the **orchestrator** skill instead.161162## References163164- Workflow examples: `resources/examples.md`