Template-driven pipeline orchestration running Claude Code CLI agents with visual designer.
79 specialized agents. 12,000+ lines of production-grade code. Infinite possibilities.
A sophisticated architecture designed for scalability, resilience, and real-time performance. Windows Electron frontend, WSL Node.js proxy, and multi-agent Claude Code instances.
Professional desktop client with real-time visual pipeline designer
1,592 lines of pipeline orchestration logic
Data-driven template system orchestrating Claude Code CLI instances
Super Agentification isn't just another automation tool—it's a paradigm shift in how we orchestrate Claude Code CLI agents.
JSON-based pipeline templates define complex multi-agent workflows with stages, agents, connections, and conditional routing—no code required.
Engaging narrative updates with 5 distinct styles (Excited, Focused, Concerned, Triumphant, Critical) provide context-aware progress reporting.
DAG-based execution with intelligent routing—agents can make decisions that determine the next stage in complex 22+ stage pipelines.
Real screenshots from production usage—showcasing templates, progress reporting, and the engaging commentator system.
Complete view of the standalone pipeline designer showing the visual canvas, template library, agent sidebar, and execution panel with real-time progress tracking.
The foundational 4-stage validation pipeline: Planning → Review → Execution → Validation. Notice the conditional connections enabling rejection loops and approval paths.
Real-time execution view showing the commentator system providing engaging updates with mood-aware styling (Excited, Focused, Triumphant) as stages complete.
The Task Planner agent creating a structured execution plan with UNDERSTANDING, APPROACH, STEPS, TEST_CONSIDERATIONS, EVIDENCE, and CONFIDENCE sections.
The Discerning Expert agent performing parallel evaluation of the plan—one of three experts competing in "Gladiator Mode" to provide the best review.
Pipeline configuration screen showing template selection, agent library, and the visual designer ready for custom workflow creation.
Concrete measurements that demonstrate technical depth, scalability, and engineering excellence.
Production-grade codebase across proxy server (1.6K), pipeline designer (4.7K), web UI (2.9K), and Electron app (3.2K)
Game Design, Systems Design, Enterprise, Validation, Analysis agents—each with unique capabilities and validation rules
Claude Plus V1, Game Design, Living Game World (22 stages), Thesis Generator, Business Builder, Full-Stack Enterprise, Test Automation
Complex Living Game World pipeline with 22 coordinated stages: world building, systems design, integration, and implementation
Pipeline checkpoints saved every 30 seconds enable crash recovery and seamless reconnection to running pipelines
Extensible template system and pluggable architecture enable unlimited custom workflows for any use case
Clean, well-documented code with advanced patterns and best practices.
// Data-Driven Pipeline Execution (proxy/server.js)
async executePipelineStages(pipeline, userContext, workingDir, ws) {
const results = {};
const stageMap = {};
pipeline.stages.forEach(stage => stageMap[stage.id] = stage);
let currentStageId = pipeline.stages[0]?.id;
let executionCount = 0;
const maxExecutions = 20; // Prevent infinite loops
while (currentStageId && executionCount < maxExecutions) {
const stage = stageMap[currentStageId];
if (!stage) break;
executionCount++;
// Load agent configuration from JSON
const agentPath = path.join(__dirname, '../agents', `${stage.agent}.json`);
const agentConfig = JSON.parse(fs.readFileSync(agentPath, 'utf8'));
let agentPrompt = agentConfig.systemPrompt;
// Auto-inject decision instructions if stage has branches
if (stage.decisions && stage.decisions.length > 0) {
agentPrompt += '\n\nIMPORTANT: End with one of these:\n';
stage.decisions.forEach(d => {
agentPrompt += `- DECISION: ${d.choice} (${d.description})\n`;
});
}
// Execute Claude agent
const result = await this.executeClaudeWithMCP(
stage.agent, agentPrompt, stageInput, workingDir
);
results[stage.id] = result;
// Conditional routing based on agent decision
currentStageId = this.determineNextStage(pipeline, stage.id, result);
}
return results;
}
// Conditional Flow - Decision Extraction & Routing
determineNextStage(pipeline, currentStageId, stageResult) {
const connections = pipeline.flow?.connections || [];
const fromConnections = connections.filter(
conn => conn.from === currentStageId
);
if (fromConnections.length === 0) return null; // Pipeline ends
// Extract "DECISION: VALUE" from agent output
const decision = this.extractDecision(stageResult);
// Match condition string against extracted decision
for (const connection of fromConnections) {
const condition = typeof connection.condition === 'object'
? connection.condition.value
: connection.condition;
// Auto-complete: plan_complete, execution_complete
if (condition && condition.endsWith('_complete')) {
return connection.to;
}
// Decision routing: APPROVED, REJECTED, etc.
if (decision && condition &&
decision.toUpperCase() === condition.toUpperCase()) {
return connection.to;
}
}
return fromConnections[0].to; // Default fallback
}
Super Agentification demonstrates advanced systems engineering, Claude Code CLI agent orchestration, and production-grade code quality. Let's discuss how this expertise can transform your organization.