workflow-orchestrator
npx skills add https://github.com/wojons/skills --skill workflow-orchestrator
Agent 安装分布
Skill 文档
Workflow Orchestrator
Design, configure, and execute AI-driven development workflows (Ralph loops) that iterate until tasks complete successfully using configurable patterns, multi-agent coordination, and intelligent stop conditions.
When to use me
Use this skill when:
- Building complex features requiring multiple AI agent passes
- Implementing automated development workflows with verification steps
- Coordinating parallel AI agents for different aspects of a task
- Creating self-correcting loops that iterate until success criteria met
- Designing workflow patterns for team consistency
- Need to orchestrate multiple AI agents in sequence or parallel
- Want to implement “Ralph loops” (AI workflows that feed failures back into input)
What I do
1. Workflow Pattern Selection
- Analyze task requirements to recommend optimal workflow patterns
- Match complexity levels with appropriate workflow types
- Compare trade-offs between speed, cost, control, and quality
- Select from proven patterns (simple, verified, planned, parallel, custom)
2. Configuration Generation
- Generate YAML configurations for workflow execution
- Define agent roles and responsibilities (builder, verifier, planner, merger)
- Set success criteria and stop conditions for automated completion
- Configure iteration limits and escape hatches for safety
- Specify tool permissions and model selections per agent
3. Multi-Agent Coordination
- Sequence agents for linear workflows (build â verify â plan)
- Parallelize agents for concurrent execution
- Merge results from multiple agent perspectives
- Handle failures and retries with intelligent routing
- Implement steering patterns (linear, conditional, parallel, unblocking)
4. Ralph Loop Implementation
- Create feedback loops where failures inform subsequent attempts
- Implement stop hooks to detect completion promises (
<promise>...</promise>) - Build contextual pressure cookers that iterate toward success
- Manage iteration limits to prevent infinite loops
- Track progress and telemetry across workflow executions
5. Integration & Tooling
- OpenCode server integration for HTTP-based workflows
- SSE event streaming for real-time monitoring
- TUI/UI dashboards for workflow visualization
- Git hook integration for automated quality gates
- Cost tracking and budgeting across agent executions
Workflow Patterns
Pattern 1: Builder Only (Simple)
Single Agent â Build â [Success?] â Done
â No
Retry (max iterations)
Best for: Simple tasks, bug fixes, small features
Agents: 1 (builder)
Control: Low, Cost: Low, Speed: High
Pattern 2: Build + Verify
Builder â [Success?] â Verifier â [Pass?] â Done
â No â No
Retry Feedback â Builder
Best for: Quality-critical work, production code
Agents: 2 (builder, verifier)
Control: Medium, Cost: Medium, Speed: Medium
Pattern 3: Build + Verify + Plan
Planner â Builder â Verifier â [Pass?] â Done
â No
Feedback â Planner
Best for: Complex features, architectural changes
Agents: 3+ (planner, builder, verifier)
Control: High, Cost: High, Speed: Low
Pattern 4: Multi-Agent Pipeline
[Agent A] â [Merge]
[Agent B] â [Results] â Done
[Agent C] â
Best for: Multiple perspectives, comprehensive solutions
Agents: 3+ parallel agents
Control: High, Cost: High, Speed: Medium
Pattern 5: Custom Workflow
User-defined sequence of agents with custom routing logic.
Configuration Examples
Simple Builder Loop (builder-only.yaml):
workflow:
version: "1.0"
settings:
max_iterations: 20
stop_on_success: true
loop:
agent: builder
task: "Build the requested feature"
stop_condition: "<promise>BUILD_COMPLETE</promise>"
tools:
read: true
write: true
edit: true
bash: true
Build + Verify Loop:
workflow:
version: "1.0"
agents:
builder:
role: "Build the feature"
stop_condition: "<promise>BUILT</promise>"
verifier:
role: "Verify quality and correctness"
stop_condition: "<promise>VERIFIED</promise>"
sequence:
- agent: builder
- agent: verifier
condition: "builder.stop_condition met"
feedback:
verifier_failed: "builder"
Multi-Agent Parallel Workflow:
workflow:
version: "1.0"
agents:
frontend_specialist:
role: "Implement UI components"
backend_specialist:
role: "Implement API and business logic"
qa_specialist:
role: "Test implementation"
parallel:
- frontend_specialist
- backend_specialist
sequence:
- parallel: [frontend_specialist, backend_specialist]
- agent: qa_specialist
merger:
agent: lead_developer
task: "Merge parallel work into cohesive solution"
Examples
# Analyze project and suggest workflow pattern
npm run workflow:analyze -- --task "Add user authentication"
# Generate workflow configuration
npm run workflow:generate -- --pattern build-verify --output auth-workflow.yaml
# Execute workflow
npm run workflow:execute -- --config auth-workflow.yaml --max-iterations 20
# Monitor running workflow
npm run workflow:monitor -- --workflow-id auth-123
# List available patterns
npm run workflow:patterns -- --list
# Create custom workflow from template
npm run workflow:custom -- --agents "planner,builder,verifier" --sequence "sequential"
Output format
Workflow Analysis Report:
Workflow Orchestrator Analysis
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Task: Add user authentication to React/Node.js app
Date: 2026-02-26
Recommended Pattern: Build + Verify + Plan
Rationale: Authentication requires security review, testing, and planning
Pattern Comparison:
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â Pattern â Control â Cost â Speed â Quality â
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â Builder Only â Low â $ â Fast â Medium â
â Build + Verify â Medium â $$ â Medium â High â
â Build+Verify+Planâ High â $$$ â Slow â Highest â
â Multi-Agent â Highest â $$$$ â Medium â Highest â
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Agents Required:
1. Planner (architect authentication flow)
2. Builder (implement components and API)
3. Verifier (security and testing specialist)
Estimated:
- Iterations: 3-5
- Cost: $15-25
- Time: 45-60 minutes
- Success Probability: 85%
Configuration Generated: auth-workflow.yaml
Workflow Configuration:
workflow:
name: "user-authentication"
version: "1.1"
created: "2026-02-26T18:00:00Z"
settings:
max_iterations: 20
stop_on_success: true
escape_hatch: true
cost_limit: 50.00
time_limit_minutes: 120
agents:
planner:
model: "anthropic/claude-sonnet-4-20250514"
temperature: 0.3
role: "Plan authentication architecture"
tools: ["read", "write", "question"]
stop_condition: "<promise>PLAN_COMPLETE</promise>"
builder:
model: "anthropic/claude-sonnet-4-20250514"
temperature: 0.7
role: "Implement authentication components"
tools: ["read", "write", "edit", "bash", "webfetch"]
stop_condition: "<promise>BUILD_COMPLETE</promise>"
verifier:
model: "anthropic/claude-sonnet-4-20250514"
temperature: 0.2
role: "Verify security and functionality"
tools: ["read", "bash", "question"]
stop_condition: "<promise>VERIFIED</promise>"
sequence:
- agent: planner
- agent: builder
condition: "planner.stop_condition met"
- agent: verifier
condition: "builder.stop_condition met"
feedback:
verifier_failed:
target: planner
message: "Verification failed, replan needed"
builder_stuck:
target: planner
message: "Builder stuck, needs guidance"
success_criteria:
- "All tests pass"
- "Security review passed"
- "API endpoints documented"
- "User stories implemented"
telemetry:
track_costs: true
track_iterations: true
track_duration: true
dashboard_url: "http://localhost:3000/dashboard"
Workflow Execution Log:
Workflow Execution: user-authentication
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Status: Running
Start Time: 2026-02-26T18:00:00Z
Current Iteration: 3/20
Cost: $8.75
Duration: 25m 30s
Agent Timeline:
00:00:00 - Planner started
00:05:15 - Planner completed: <promise>PLAN_COMPLETE</promise>
00:05:30 - Builder started
00:15:45 - Builder: Created 12 files, 457 lines
00:20:30 - Builder completed: <promise>BUILD_COMPLETE</promise>
00:20:45 - Verifier started
00:25:30 - Verifier: Running security checks
Current Agent: Verifier
Progress: 75%
Estimated Completion: 00:35:00
Success Criteria Status:
â
Tests passing: 42/42 tests
ð Security review: In progress
ð Documentation: 80% complete
ð¤ User stories: 3/4 implemented
Next: Verifier completion â Workflow success
Notes
- Ralph loops work best with clear success criteria – vague goals lead to infinite loops
- Start simple – use Builder Only pattern for small tasks before scaling up
- Monitor costs – parallel agents and multiple iterations increase expense
- Implement escape hatches – always have manual stop conditions
- Use stop promises (
<promise>...</promise>) for reliable completion detection - Consider feedback mechanisms – failed verification should inform subsequent attempts
- Balance control vs. autonomy – more agents = more control but higher cost/complexity
- Test workflows with simple tasks before applying to critical work
- Document patterns for team consistency and knowledge sharing
- Review telemetry to optimize workflow configurations over time