Agent BuildKit Architecture

Enterprise autonomous agent platform with BAR (BuildKit Agent Runtime)

Overview

Agent BuildKit is an enterprise autonomous agent platform that provides sequential thinking workflows, GitLab CE integration, Phoenix Arize observability, and Kubernetes-based OSSA deployment. It serves as the foundation for distributed AI agent orchestration across the LLM Platform ecosystem.

Version: 0.1.2 OSSA Compliance: v0.1.9-alpha.1 License: MIT

BAR Runtime Architecture

BAR (BuildKit Agent Runtime) is the core execution environment consisting of four integrated subsystems:

graph TB
    subgraph "BAR Runtime"
        ROE[ROE<br/>Runtime Orchestration Engine]
        VORTEX[VORTEX v3<br/>Vector Operations & Streaming]
        QITS[QITS<br/>Quality Intelligence Testing]
        SWARM[SWARM<br/>Resource Manager]
    end

    subgraph "Agent Types"
        Governors[Governors<br/>TDD, Version Sync, Branch Policy]
        Workers[Workers<br/>Test Gen, API Builder, Doc Sync]
        Critics[Critics<br/>Security, Performance, Review]
        Observers[Observers<br/>Roadmap, Metrics, Health]
    end

    subgraph "Infrastructure"
        K8s[Kubernetes Cluster]
        GitLab[GitLab CE]
        Phoenix[Phoenix Arize]
        Mesh[Agent Mesh]
    end

    ROE --> Governors
    ROE --> Workers
    ROE --> Critics
    ROE --> Observers

    VORTEX --> ROE
    QITS --> Workers
    SWARM --> K8s

    Governors --> GitLab
    Workers --> Mesh
    Critics --> Phoenix
    Observers --> Phoenix

Core Components

ROE (Runtime Orchestration Engine)

Purpose: Multi-agent coordination, resource allocation, and dependency resolution

Key Features

• Workflow Definition: YAML-based workflow specifications
• Agent Coordination: Parallel and sequential task execution
• Dependency Resolution: Automatic dependency graph construction
• Resource Allocation: Intelligent resource distribution via SWARM
• Event-Driven: React to GitLab webhooks, timers, and external events

Architecture

graph LR
    subgraph "ROE Core"
        Parser[Workflow Parser]
        Scheduler[Task Scheduler]
        Executor[Agent Executor]
        Monitor[State Monitor]
    end

    subgraph "Workflow Storage"
        GitLab[(GitLab Repos)]
        Config[(Config Store)]
    end

    subgraph "Execution Layer"
        Agents[Agent Pool]
        SWARM[SWARM Manager]
    end

    Parser --> Scheduler
    Scheduler --> Executor
    Executor --> Monitor
    Monitor --> Scheduler

    GitLab --> Parser
    Config --> Parser

    Executor --> Agents
    Executor --> SWARM

Workflow Example

# .gitlab/workflows/feature-workflow.yml
name: Feature Development Workflow
version: 0.1.0
trigger:
  - event: issue.created
    labels: [feature]

stages:
  - name: api-design
    agent: api-first-enforcer
    dependencies: []
    outputs:
      - openapi-spec.yaml

  - name: test-generation
    agent: test-generator
    dependencies: [api-design]
    inputs:
      - openapi-spec.yaml
    outputs:
      - tests/

  - name: implementation
    agent: api-builder
    dependencies: [test-generation]
    inputs:
      - openapi-spec.yaml
      - tests/
    outputs:
      - src/

  - name: quality-gate
    agent: quality-gate-enforcer
    dependencies: [implementation]
    conditions:
      - coverage >= 80%
      - phpcs violations == 0

ROE API

// Create workflow
const workflow = await roe.createWorkflow({
  name: 'distributed-deployment',
  localAgents: ['tdd-enforcer', 'api-builder'],
  remoteAgents: [
    'ossa://production/deployer',
    'ossa://staging/validator'
  ],
  coordinationStrategy: 'event-driven',
  fallbackLocal: true
})

// Execute workflow
const execution = await roe.executeWorkflow(workflow.id, {
  inputs: { issueId: 123 }
})

// Monitor progress
roe.on('task.completed', (task) => {
  console.log(`Task ${task.name} completed with status: ${task.status}`)
})

VORTEX v3 (Vector Operations & Real-Time Streaming)

Purpose: Real-time event processing, streaming operations, and memory management

Key Features

• Real-Time Streaming: Sub-100ms updates to clients
• Vector Operations: Efficient vector transformations and searches
• Memory Management: Intelligent caching and eviction
• Event Processing: High-throughput event ingestion
• WebSocket Support: Bidirectional streaming

Architecture

graph TB
    subgraph "Input Layer"
        Events[Event Sources]
        Agents[Agent Updates]
        Metrics[Metric Streams]
    end

    subgraph "VORTEX Core"
        Ingest[Event Ingestion]
        Transform[Stream Transform]
        Buffer[Memory Buffer]
        Broadcast[Event Broadcast]
    end

    subgraph "Output Layer"
        WS[WebSocket Clients]
        Storage[Vector Store]
        Analytics[Analytics Engine]
    end

    Events --> Ingest
    Agents --> Ingest
    Metrics --> Ingest

    Ingest --> Transform
    Transform --> Buffer
    Buffer --> Broadcast

    Broadcast --> WS
    Broadcast --> Storage
    Broadcast --> Analytics

VORTEX API

// Initialize VORTEX stream
const stream = vortex.createStream({
  source: 'agent-executions',
  transform: 'realtime',
  buffer: { size: 1000, ttl: 60000 }
})

// Subscribe to stream
stream.subscribe({
  filter: { agentType: 'worker' },
  onData: (event) => {
    console.log(`Agent ${event.agentId}: ${event.status}`)
  },
  onError: (error) => {
    console.error('Stream error:', error)
  }
})

// Publish to stream
await vortex.publish('agent-executions', {
  agentId: 'tdd-enforcer-001',
  status: 'completed',
  result: { coverage: 85 }
})

Streaming Example

// Voice agent workflow with VORTEX integration
async function handleVoiceCommand(audio: Buffer) {
  const stream = vortex.createStream({
    source: 'voice-workflow',
    realtime: true
  })

  // Stream updates to user
  stream.subscribe({
    onData: (update) => {
      tts.speak(update.message)
    }
  })

  // Process workflow stages
  const workflow = await roe.executeWorkflow('voice-feature', {
    inputs: { audio }
  })

  // VORTEX streams each stage update
  // User hears: "Tests generated"
  // User hears: "Implementation complete"
  // User hears: "Created auth API with TDD, 85% coverage, OSSA-compliant"
}

QITS (Quality Intelligence Testing System)

Purpose: AI-powered test generation, mutation testing, and security scanning

Key Features

• AI Test Generation: LLM-powered test case creation
• Mutation Testing: Automatic mutation score calculation
• Security Scanning: OWASP Top 10 vulnerability detection
• Coverage Analysis: Multi-dimensional coverage tracking
• Quality Scoring: Automated quality gate evaluation

Architecture

graph TB
    subgraph "Input Analysis"
        Code[Source Code]
        Spec[OpenAPI Specs]
        Existing[Existing Tests]
    end

    subgraph "QITS Core"
        LLM[LLM Test Generator]
        Mutation[Mutation Engine]
        Security[Security Scanner]
        Coverage[Coverage Analyzer]
    end

    subgraph "Test Execution"
        Runner[Test Runner]
        Report[Report Generator]
        Gate[Quality Gate]
    end

    Code --> LLM
    Spec --> LLM
    Existing --> LLM

    LLM --> Runner
    Code --> Mutation
    Mutation --> Runner
    Code --> Security
    Security --> Report

    Runner --> Coverage
    Coverage --> Report
    Report --> Gate

QITS API

// Generate tests with AI
const tests = await qits.generateTests({
  sourceFile: 'src/api/users.ts',
  openapiSpec: 'specs/users.yaml',
  coverageTarget: 80,
  includeEdgeCases: true
})

// Run mutation testing
const mutationScore = await qits.mutationTest({
  sourceFiles: ['src/**/*.ts'],
  testFiles: ['tests/**/*.test.ts'],
  operators: ['arithmetic', 'conditional', 'logical']
})

// Security scan
const vulnerabilities = await qits.securityScan({
  targets: ['src/', 'config/'],
  standards: ['OWASP Top 10', 'CWE'],
  severity: 'medium'
})

// Quality gate evaluation
const gateResult = await qits.evaluateGate({
  coverage: 85,
  mutationScore: 75,
  vulnerabilities: vulnerabilities.filter(v => v.severity === 'critical').length
})

Test Generation Example

// Input: OpenAPI spec
const spec = `
openapi: 3.1.0
paths:
  /api/users/{id}:
    get:
      parameters:
        - name: id
          schema:
            type: integer
      responses:
        '200':
          description: User found
        '404':
          description: User not found
`

// Output: Generated tests
const tests = await qits.generateTests({ spec })

// Generated test file:
/*
describe('GET /api/users/{id}', () => {
  it('should return user when ID exists', async () => {
    const response = await request.get('/api/users/1')
    expect(response.status).toBe(200)
    expect(response.body).toHaveProperty('id', 1)
  })

  it('should return 404 when ID does not exist', async () => {
    const response = await request.get('/api/users/999999')
    expect(response.status).toBe(404)
  })

  it('should return 400 when ID is invalid', async () => {
    const response = await request.get('/api/users/invalid')
    expect(response.status).toBe(400)
  })
})
*/

SWARM (Scalable Workflow & Agent Resource Manager)

Purpose: Dynamic agent scaling, workflow orchestration, and intelligent load balancing

Key Features

• Auto-Scaling: CPU/memory-based agent scaling
• Load Balancing: Intelligent task distribution
• Resource Limits: Per-agent CPU/memory limits
• Health Monitoring: Agent health checks and failover
• Cost Optimization: Resource usage optimization

Architecture

graph TB
    subgraph "Resource Monitoring"
        CPU[CPU Metrics]
        Memory[Memory Metrics]
        Queue[Task Queue Depth]
    end

    subgraph "SWARM Core"
        Scheduler[Task Scheduler]
        Scaler[Auto Scaler]
        LB[Load Balancer]
        Health[Health Monitor]
    end

    subgraph "Agent Pool"
        Running[Running Agents]
        Idle[Idle Agents]
        Starting[Starting Agents]
    end

    CPU --> Scaler
    Memory --> Scaler
    Queue --> Scheduler

    Scaler --> Running
    Scaler --> Starting
    Scheduler --> LB
    LB --> Running
    Health --> Running
    Health --> Idle

SWARM API

// Configure auto-scaling
await swarm.configureScaling({
  minReplicas: 1,
  maxReplicas: 10,
  targetCPU: 70,
  targetMemory: 80,
  scaleUpCooldown: 60,
  scaleDownCooldown: 300
})

// Spawn agent with resources
const agent = await swarm.spawnAgent({
  type: 'tdd-enforcer',
  resources: {
    cpu: '500m',
    memory: '512Mi',
    limits: {
      cpu: '1000m',
      memory: '1Gi'
    }
  }
})

// Load balancing strategy
await swarm.setLoadBalancing({
  strategy: 'least-loaded',
  healthCheckInterval: 10000,
  failureThreshold: 3
})

// Monitor resource usage
const metrics = await swarm.getMetrics({
  agentType: 'worker',
  period: '1h'
})

Scaling Example

// Create tasks requiring agent swarm
const tasks = [
  { file: 'src/api/users.ts', type: 'test-generation' },
  { file: 'src/api/posts.ts', type: 'test-generation' },
  { file: 'src/api/comments.ts', type: 'test-generation' },
  // ... 100 more files
]

// SWARM automatically scales agents based on queue depth
await swarm.createTasks({
  tasks,
  runtime: 'kubernetes',
  scaling: {
    minAgents: 2,
    maxAgents: 20,
    tasksPerAgent: 5
  }
})

// SWARM spawns 20 agents (100 tasks / 5 per agent)
// As tasks complete, SWARM scales down to minAgents

Agent Types

Governors (Policy Enforcement)

Ensure compliance with development standards and policies.

TDD Enforcer

manifest:
  name: tdd-enforcer
  type: governor
  capabilities:
    - test-validation
    - coverage-enforcement
  rules:
    - tests-before-code
    - 80-percent-coverage
    - red-green-refactor

Responsibilities: - Validate RED-GREEN-REFACTOR cycle - Enforce 80%+ test coverage - Prevent untested code from merging - Generate coverage reports

Version Sync Governor

manifest:
  name: version-sync
  type: governor
  capabilities:
    - version-management
    - changelog-generation
  rules:
    - semver-compliance
    - changelog-required

Responsibilities: - Maintain semantic versioning - Sync versions across packages - Generate changelogs - Validate version bumps

Branch Policy Governor

manifest:
  name: branch-policy
  type: governor
  capabilities:
    - branch-validation
    - naming-enforcement
  rules:
    - __REBUILD-pattern
    - feature-prefix

Responsibilities: - Enforce branch naming conventions - Validate workflow phases (API-first, TDD, Implementation) - Prevent direct commits to main/master - Ensure issue linkage

Workers (Task Execution)

Execute specific development tasks.

Test Generator

manifest:
  name: test-generator
  type: worker
  capabilities:
    - ai-test-generation
    - contract-testing
  dependencies:
    - qits
    - llm-gateway

Responsibilities: - Generate test cases from OpenAPI specs - Create unit, integration, and E2E tests - Implement contract tests - Generate test data

API Builder

manifest:
  name: api-builder
  type: worker
  capabilities:
    - api-implementation
    - openapi-codegen
  dependencies:
    - test-generator

Responsibilities: - Implement API endpoints from specs - Generate boilerplate code - Ensure spec compliance - Pass all generated tests

Doc Synchronizer

manifest:
  name: doc-sync
  type: worker
  capabilities:
    - wiki-sync
    - markdown-generation
  dependencies:
    - gitlab-api

Responsibilities: - Sync documentation to GitLab Wiki - Generate API documentation from specs - Create architecture diagrams - Maintain documentation structure

Critics (Analysis & Review)

Analyze code quality, security, and performance.

Security Auditor

manifest:
  name: security-auditor
  type: critic
  capabilities:
    - vulnerability-scanning
    - dependency-audit
    - secret-detection

Responsibilities: - Scan for OWASP Top 10 vulnerabilities - Audit dependencies for known CVEs - Detect hardcoded secrets - Generate security reports

Performance Monitor

manifest:
  name: performance-monitor
  type: critic
  capabilities:
    - performance-testing
    - regression-detection
  thresholds:
    p99: 1000ms
    throughput: 1000 req/s

Responsibilities: - Run performance benchmarks - Detect performance regressions - Monitor resource usage - Generate performance reports

Observers (Monitoring & Analytics)

Monitor system health and collect metrics.

Roadmap Tracker

manifest:
  name: roadmap-tracker
  type: observer
  capabilities:
    - progress-tracking
    - milestone-monitoring
  integrations:
    - gitlab-issues
    - gitlab-milestones

Responsibilities: - Track roadmap progress - Monitor milestone completion - Generate progress reports - Update project dashboards

Metrics Collector

manifest:
  name: metrics-collector
  type: observer
  capabilities:
    - metric-aggregation
    - time-series-storage
  outputs:
    - prometheus
    - grafana

Responsibilities: - Collect agent metrics - Aggregate workflow statistics - Export to Prometheus - Create Grafana dashboards

OSSA Integration

OSSA Compliance Features

Protocol Implementation

• Full OSSA v0.1.9-alpha.1 support
• Agent registration and discovery
• Protocol validation
• Interoperability testing

Cross-Platform Communication

# Register local agents with OSSA network
buildkit ossa register \
  --agent-id tdd-enforcer-001 \
  --capabilities "testing,validation"

# Discover external OSSA agents
buildkit ossa discover \
  --network production \
  --filter "capabilities=deployment"

# Establish communication bridges
buildkit ossa bridge create \
  --name "legacy-integration" \
  --source "internal-agents" \
  --target "external-ossa-network" \
  --protocol-version "v0.1.9-alpha.1"

Distributed Workflow Orchestration

# Create multi-network workflow
buildkit roe workflows create "distributed-deployment" \
  --local-agents "tdd-enforcer,api-builder" \
  --remote-agents "ossa://production/deployer,ossa://staging/validator" \
  --coordination-strategy "event-driven" \
  --fallback-local

Multi-Vendor Agent Coordination

graph TB
    subgraph "Local BuildKit"
        LTE[TDD Enforcer]
        LAB[API Builder]
        LDS[Doc Sync]
    end

    subgraph "External OSSA Network A"
        ESA[Security Auditor]
        EPT[Performance Tester]
    end

    subgraph "External OSSA Network B"
        EDG[Deployment Governor]
        EMN[Monitoring Agent]
    end

    subgraph "OSSA Bridge Layer"
        BR[Protocol Bridge]
        CM[Compliance Monitor]
        LB[Load Balancer]
    end

    LTE -->|OSSA Protocol| BR
    LAB -->|OSSA Protocol| BR
    LDS -->|OSSA Protocol| BR

    BR -->|Route to Network A| ESA
    BR -->|Route to Network A| EPT
    BR -->|Route to Network B| EDG
    BR -->|Route to Network B| EMN

    CM -->|Validate Compliance| BR
    LB -->|Optimize Routing| BR

API-First Architecture

OpenAPI Specification

30+ REST endpoints documented in OpenAPI 3.1:

• Agent Management: CRUD operations for agents
• Workflow Execution: Start, stop, monitor workflows
• Task Management: Create, assign, complete tasks
• Metrics & Analytics: Query performance metrics
• Health & Status: Service health checks

Contract Testing

# Validate API against OpenAPI spec
npm run test:contract

# Run Dredd contract tests
dredd openapi.yml http://localhost:3000

# Run Schemathesis fuzzing
schemathesis run openapi.yml --base-url http://localhost:3000

CLI Reference

Core Commands

# Agent management
buildkit agents list
buildkit agents create --type worker --name test-generator
buildkit agents deploy --agent-id tdd-enforcer-001

# Workflow management
buildkit roe workflows create feature-workflow.yml
buildkit roe workflows execute --workflow-id 123
buildkit roe workflows status --workflow-id 123

# Quality testing
buildkit qits generate-tests --file src/api/users.ts
buildkit qits mutation-test --src src/ --tests tests/
buildkit qits security-scan --targets src/

# Resource management
buildkit swarm scale --agent-type worker --replicas 10
buildkit swarm metrics --agent-type worker
buildkit swarm health --all

# OSSA operations
buildkit ossa register --agent-id agent-123
buildkit ossa discover --network production
buildkit ossa compliance --validate

Kubernetes Deployment

# Deploy full agent infrastructure
npm run deploy:k8s deploy

# Deploy with custom namespace
npm run deploy:k8s deploy -- -n agents

# Check status
npm run deploy:k8s status

# View logs
npm run deploy:k8s logs -- -d agent-gateway

# Health check
npm run deploy:k8s health

Integration Points

GitLab CE

• OAuth authentication
• Issue tracking
• Merge request automation
• Wiki synchronization
• CI/CD pipelines

Phoenix Arize

• LLM call tracing
• Token usage tracking
• Cost monitoring
• Performance analysis

Agent Mesh

• gRPC communication
• Load balancing
• Health monitoring
• Circuit breaking

Related Documentation

• System Overview - Complete architecture
• Agent Mesh - Coordination layer
• Agent Tracer - Observability
• Kubernetes Deployment
• Golden Workflow