Migrated from design-system-swarm with fresh git history.
Old project history preserved in /home/overbits/apps/design-system-swarm
Core components:
- MCP Server (Python FastAPI with mcp 1.23.1)
- Claude Plugin (agents, commands, skills, strategies, hooks, core)
- DSS Backend (dss-mvp1 - token translation, Figma sync)
- Admin UI (Node.js/React)
- Server (Node.js/Express)
- Storybook integration (dss-mvp1/.storybook)
Self-contained configuration:
- All paths relative or use DSS_BASE_PATH=/home/overbits/dss
- PYTHONPATH configured for dss-mvp1 and dss-claude-plugin
- .env file with all configuration
- Claude plugin uses ${CLAUDE_PLUGIN_ROOT} for portability
Migration completed: $(date)
🤖 Clean migration with full functionality preserved
12 KiB
Zen Workflow Orchestration Tools
Purpose: Chain Zen AI tools together in intelligent pipelines for complex decision-making and implementation
Created: December 6, 2025 Status: Implemented in MCP, ready to use
Overview
The Zen workflow orchestration tools automatically execute multi-step AI pipelines:
Review → Brainstorm → Consensus → Gemini 3 Decides → Implement
This automates the decision-making process for complex features, refactoring, and architectural decisions.
Available Tools
1. dss_smart_implement (Full Pipeline)
Purpose: Complete implementation workflow with all steps
Pipeline:
- Review - Analyze existing code with codereview
- Brainstorm - Generate 3-5 solution approaches with chat
- Consensus - Multi-model evaluation (GPT-5.1, Gemini-2.5-Pro, Claude Sonnet 4.5)
- Decide - Gemini 3 Pro makes final decision
- Implement - Returns implementation plan
Usage:
// From Claude Code MCP:
Use tool: dss_smart_implement
Parameters:
{
"task_description": "Add dark mode toggle to dashboard",
"context_files": [
"/home/overbits/dss/admin-ui/index.html",
"/home/overbits/dss/admin-ui/js/core/app.js"
],
"requirements": "Must persist user preference, support system theme",
"skip_review": false
}
Returns:
{
"workflow_id": "uuid-here",
"status": "completed",
"steps": [
{"step": "review", "status": "completed", "result": {...}},
{"step": "brainstorm", "status": "completed", "result": {...}},
{"step": "consensus", "status": "completed", "result": {...}},
{"step": "decide", "status": "completed", "result": {...}},
{"step": "implement", "status": "ready", "plan": "..."}
],
"final_implementation": "Detailed implementation plan...",
"decision_rationale": "Consensus analysis and reasoning...",
"continuation_id": "continuation-id-here"
}
When to Use:
- Complex features requiring architectural decisions
- Refactoring that affects multiple components
- Security-sensitive implementations
- Performance optimizations
- Major UI/UX changes
2. dss_review_brainstorm_decide (Simplified Pipeline)
Purpose: Faster workflow without consensus step
Pipeline:
- Review existing code
- Brainstorm solutions
- Gemini 3 decides
Usage:
Use tool: dss_review_brainstorm_decide
Parameters:
{
"issue_description": "Fix memory leak in browser logger",
"context_files": [
"/home/overbits/dss/admin-ui/js/core/browser-logger.js"
]
}
When to Use:
- Bug fixes
- Smaller features
- Quick decisions needed
- Time-sensitive tasks
3. dss_consensus_implement (Green-field Pipeline)
Purpose: New feature implementation without review
Pipeline:
- Brainstorm approaches
- Multi-model consensus
- Implementation plan
Usage:
Use tool: dss_consensus_implement
Parameters:
{
"feature_description": "Add user authentication with OAuth",
"evaluation_models": ["gpt-5.1", "gemini-2.5-pro", "claude-sonnet-4-5"],
"decide_model": "gemini-3-pro-preview"
}
When to Use:
- New features (no existing code)
- Green-field development
- Prototype implementations
- Architecture design
4. dss_workflow_status (Status Check)
Purpose: Check status of running workflow
Usage:
Use tool: dss_workflow_status
Parameters:
{
"workflow_id": "uuid-from-previous-call"
}
Returns:
{
"workflow_id": "uuid",
"type": "smart_implement",
"status": "in_progress|completed|failed",
"task": "Original task description",
"steps": [...],
"started_at": "2025-12-06T...",
"completed_at": "2025-12-06T...",
"error": null
}
Workflow States
Status Values
- in_progress: Workflow currently executing
- completed: All steps finished successfully
- failed: Workflow encountered error
Step Statuses
- completed: Step finished successfully
- ready: Step ready to execute (for implement step)
- failed: Step encountered error
How Context is Maintained
All workflows use Zen's continuation_id feature to maintain context across steps:
- Step 1 (Review) creates continuation_id
- Step 2 (Brainstorm) receives continuation_id, sees all context from Step 1
- Step 3 (Consensus) receives continuation_id, sees context from Steps 1 & 2
- And so on...
This ensures each step has full context from previous steps without re-sending data.
Models Used
Default Models by Step
| Step | Model | Reason |
|---|---|---|
| Review | gpt-5.1 | Excellent code analysis |
| Brainstorm | gpt-5.1 | Creative solution generation |
| Consensus (For) | gpt-5.1 | Optimistic evaluation |
| Consensus (Against) | gemini-2.5-pro | Critical evaluation |
| Consensus (Neutral) | claude-sonnet-4-5 | Balanced perspective |
| Final Decision | gemini-3-pro-preview | Best overall reasoning |
Override Models
You can specify different models in dss_consensus_implement:
{
"evaluation_models": ["gpt-5.1-codex", "gemini-3-pro-preview"],
"decide_model": "gpt-5-pro"
}
Example Workflows
Example 1: Add Feature with Full Pipeline
// Step 1: Start workflow
Use tool: dss_smart_implement
{
"task_description": "Add export functionality to browser logger",
"context_files": [
"/home/overbits/dss/admin-ui/js/core/browser-logger.js"
],
"requirements": "Must support JSON and CSV formats, max 10MB export"
}
// Step 2: Receive implementation plan
{
"workflow_id": "abc-123",
"status": "completed",
"final_implementation": "
1. Add exportFormats property to BrowserLogger class
2. Implement exportAsJSON() method
3. Implement exportAsCSV() method with csv-stringify
4. Add format parameter to export() method
5. Add download trigger with file size check
...",
"decision_rationale": "Consensus favored modular approach with separate
format handlers. Gemini 3 confirmed this allows easy addition of new formats."
}
// Step 3: Execute implementation (use Write/Edit tools)
// Follow the implementation plan from the workflow result
Example 2: Quick Bug Fix
// Use simplified workflow for faster turnaround
Use tool: dss_review_brainstorm_decide
{
"issue_description": "Browser logger not capturing fetch errors",
"context_files": [
"/home/overbits/dss/admin-ui/js/core/browser-logger.js"
]
}
// Returns focused fix without full consensus process
Example 3: Check Long-Running Workflow
// Start complex workflow
Use tool: dss_smart_implement
{ ... }
// Returns workflow_id: "abc-123"
// Later, check status
Use tool: dss_workflow_status
{ "workflow_id": "abc-123" }
// See current progress
{
"status": "in_progress",
"steps": [
{"step": "review", "status": "completed"},
{"step": "brainstorm", "status": "completed"},
{"step": "consensus", "status": "in_progress"}
]
}
Performance Characteristics
Execution Times (Estimated)
| Workflow | Steps | Avg Time |
|---|---|---|
| smart_implement | 5 | 3-5 min |
| review_brainstorm_decide | 3 | 1-2 min |
| consensus_implement | 3 | 2-3 min |
Times vary based on:
- Model response times
- Complexity of task
- Number of context files
- Length of code being analyzed
Error Handling
Common Errors
Error: "Workflow not found"
- Cause: Invalid workflow_id
- Solution: Check workflow_id from original call
Error: "Workflow failed: Model timeout"
- Cause: Zen tool took too long to respond
- Solution: Retry with simpler task or fewer context files
Error: "Invalid model specified"
- Cause: Model name not recognized by Zen
- Solution: Use
listmodelstool to see available models
Best Practices
1. Choose Right Workflow
- Full pipeline (smart_implement): Complex features, architecture decisions
- Simplified (review_brainstorm_decide): Bug fixes, quick tasks
- Green-field (consensus_implement): New features, no existing code
2. Provide Good Context
// Good: Specific context files
"context_files": [
"/path/to/exact/file.js",
"/path/to/related/file.css"
]
// Bad: Too broad
"context_files": [
"/entire/project/directory/*"
]
3. Write Clear Descriptions
// Good
"task_description": "Add dark mode toggle that persists user preference
in localStorage and syncs with system theme via matchMedia API"
// Bad
"task_description": "add dark mode"
4. Use Continuation ID
If workflow fails partway through, you can restart with the continuation_id:
// Workflow failed at step 3
{
"workflow_id": "abc-123",
"status": "failed",
"continuation_id": "cont-xyz",
"steps": [
{"step": "review", "status": "completed"},
{"step": "brainstorm", "status": "completed"},
{"step": "consensus", "status": "failed"}
]
}
// Resume manually with zen__consensus using continuation_id
Use tool: mcp__zen__consensus
{
"continuation_id": "cont-xyz",
... // other params
}
Integration with Existing Tools
Combine with DSS Tools
// 1. Use smart_implement to get plan
Use tool: dss_smart_implement
{ "task_description": "Add new component to design system" }
// 2. Use DSS project tools to check existing components
Use tool: dss_list_components
{ "project_id": "main" }
// 3. Implement using Write/Edit tools
// 4. Use DSS tools to verify
Use tool: dss_get_project_summary
Future Enhancements
Planned Features (Not Yet Implemented)
- Auto-implement step (actually writes code)
- Test generation after implementation
- Code review of generated code
- Rollback on failed implementation
- Workflow templates (save common pipelines)
- Background execution (async workflows)
Related Documentation
.dss/MCP_DEBUG_TOOLS_ARCHITECTURE.md- Overall MCP architecture.dss/WORKFLOWS/- Debug workflowstools/dss_mcp/tools/workflow_tools.py- Implementation source- Zen MCP docs for underlying tools
Quick Reference Card
┌─────────────────────────────────────────────────────────────┐
│ Zen Workflow Orchestration - Quick Reference │
├─────────────────────────────────────────────────────────────┤
│ │
│ Full Pipeline (3-5 min): │
│ dss_smart_implement │
│ → Review → Brainstorm → Consensus → Decide → Plan │
│ │
│ Quick Fix (1-2 min): │
│ dss_review_brainstorm_decide │
│ → Review → Brainstorm → Decide │
│ │
│ New Feature (2-3 min): │
│ dss_consensus_implement │
│ → Brainstorm → Consensus → Plan │
│ │
│ Check Status: │
│ dss_workflow_status { workflow_id } │
│ │
└─────────────────────────────────────────────────────────────┘
Status: ✅ Implemented and ready to use
Location: tools/dss_mcp/tools/workflow_tools.py
Registered: DSS MCP Server (will be available after restart)