multi-agent-workflow
Skill1 starsChanged 8 months agoMITView on GitHub
Guide for coordinating PM, Frontend, Backend, Mobile, and QA agents on complex projects via CLI
4 other projects use a version of this.
Adopted by
Most recently taken up by
- XiaoZ-0218/multi-agent-workflowtheir own version, first seen Oct 11, 2026
- ANAMIZED/NeedRailtheir own version, first seen Aug 27, 2026
- ANAMIZED/SuperAgenticMCPtheir own version, first seen Aug 18, 2026
- Minions-Land/Soup_Drinkingtheir own version, first seen Apr 5, 2026
Other versions4 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 4
- Minions-Land/Soup_Drinking★ 4same name
- ANAMIZED/NeedRail★ 1same name
- ANAMIZED/SuperAgenticMCP★ 1same name
- XiaoZ-0218/multi-agent-workflow★ 1same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
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The file
We split this skill into the rules it gives an agent
7 rules. About 0 are common, 5 are distinctive, and 2 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈5
Distinctive · estimate
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 22
Always start with PM Agent for task decomposition
- Distinctive: line 27
Always use Serena MCP tools as the primary method for code exploration and modification
- Distinctive: line 28
Never skip steps in the workflow — follow each step sequentially without omission
- Very specific: line 40
Use spawn-agent.sh for each task
- Very specific: line 53
Use memory read tool to poll progress-{agent}.md files
- Distinctive: line 54
Verify API contracts align between agents
- Distinctive: line 55
Ensure shared data models are consistent
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Multi-Agent Workflow Guide
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
Core Rules
- 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 user-preferences.yaml
- Spawn all same-priority tasks in parallel using background processes
# Example: spawn backend and frontend in parallel
oh-my-ag agent:spawn backend "task description" session-id -w ./backend &
oh-my-ag agent:spawn frontend "task description" session-id -w ./frontend &
waitStep 3: Monitor & Coordinate
- Use memory read tool to poll
progress-{agent}.mdfiles - 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
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
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Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

