custom-workers

Custom Workers

Build composable background analysis workers with 24 phase executors and 6 presets.

Quick Start

# List available presets
npx ruvector workers presets

# List available phase executors
npx ruvector workers phases

# Create a custom worker from preset
npx ruvector workers create my-scanner --preset security-scan

# Run the worker
npx ruvector workers run my-scanner --path ./src

Available Presets

Phase Executors (24 total)

Discovery Phases

• file-discovery - Find files matching patterns
• pattern-discovery - Discover code patterns
• dependency-discovery - Map dependencies
• api-discovery - Find API endpoints

Analysis Phases

• static-analysis - AST-based code analysis
• complexity-analysis - Cyclomatic complexity
• security-analysis - Security vulnerability scan
• performance-analysis - Performance bottlenecks
• import-analysis - Import/export mapping
• type-analysis - TypeScript type extraction

Pattern Phases

• pattern-extraction - Extract code patterns
• todo-extraction - Find TODOs/FIXMEs
• secret-detection - Detect hardcoded secrets
• code-smell-detection - Identify code smells

Build Phases

• graph-build - Build code graph
• call-graph - Function call graph
• dependency-graph - Dependency graph

Learning Phases

• vectorization - Convert to vectors
• embedding-generation - ONNX embeddings (384d)
• pattern-storage - Store in VectorDB
• sona-training - SONA reinforcement learning

Output Phases

• summarization - Generate summary
• report-generation - Create report
• indexing - Index for search

YAML Configuration

Create workers.yaml in your project:

version: '1.0'
workers:
  - name: auth-scanner
    triggers: [auth-scan, scan-auth]
    phases:
      - type: file-discovery
        config:
          patterns: ["**/auth/**", "**/login/**"]
      - type: security-analysis
      - type: secret-detection
      - type: report-generation
    capabilities:
      onnxEmbeddings: true
      vectorDb: true

  - name: api-documenter
    triggers: [api-docs, document-api]
    phases:
      - type: file-discovery
        config:
          patterns: ["**/routes/**", "**/api/**"]
      - type: api-discovery
      - type: type-analysis
      - type: report-generation

Load configuration:

npx ruvector workers load-config --file workers.yaml

CLI Commands

# Core commands
npx ruvector workers presets       # List presets
npx ruvector workers phases        # List phases
npx ruvector workers create <name> --preset <preset>
npx ruvector workers run <name> --path <path>

# Configuration
npx ruvector workers init-config   # Generate workers.yaml
npx ruvector workers load-config   # Load from workers.yaml
npx ruvector workers custom        # List registered workers

# Monitoring
npx ruvector workers status        # Worker status
npx ruvector workers results       # Analysis results
npx ruvector workers stats         # Statistics

MCP Tools

Available via ruvector MCP server:

Capabilities

Workers can use these capabilities:

• ONNX Embeddings: Real transformer embeddings (all-MiniLM-L6-v2, 384d, SIMD)
• VectorDB: Store and search embeddings with HNSW indexing
• SONA Learning: Self-Organizing Neural Architecture for pattern learning
• ReasoningBank: Trajectory tracking and meta-learning

Integration with Hooks

Workers auto-dispatch on UserPromptSubmit via trigger keywords:

• Type "audit this code" → triggers audit worker
• Type "security scan" → triggers security worker
• Type "learn patterns" → triggers learning worker

Example: Security Scanner

# Create from security-scan preset
npx ruvector workers create security-checker --preset security-scan --triggers "security,vuln,cve"

# Run on source
npx ruvector workers run security-checker --path ./src

# View results
npx ruvector workers results

Example: Custom Learning Worker

# workers.yaml
workers:
  - name: code-learner
    triggers: [learn, pattern-learn]
    phases:
      - type: file-discovery
        config:
          patterns: ["**/*.ts", "**/*.js"]
          exclude: ["node_modules/**"]
      - type: static-analysis
      - type: pattern-extraction
      - type: embedding-generation
      - type: pattern-storage
      - type: sona-training
    capabilities:
      onnxEmbeddings: true
      vectorDb: true
      sonaLearning: true