Files
Dragan Spiridonov dc5dc14ebd feat(learning): use local Nagual instance + add local LLM judge
Switch the cross-project knowledge hub from the cloud endpoint to a
locally-runnable Nagual instance, and add an optional local LLM judge
for scoring pattern quality.

- nagual-client.ts: REST client for a local `nagual serve` instance
  (NAGUAL_URL, default http://localhost:3333); search/recordOutcome/
  promotePattern are all fire-and-forget safe.
- local-judge-client.ts: Ollama-compatible judge (NAGUAL_JUDGE_URL/MODEL)
  blending 0.7*outcome + 0.3*judge_score, with an ambiguous-zone review flag.
- task-hooks.ts: pre-task surfaces Nagual cross-project context for
  complex tasks in relevant QE domains (best-effort, gated on env + length).
- settings.json: add NAGUAL_JUDGE_URL/MODEL; fix invalid mcp allow-rule
  globs (mcp__ruflo__* / mcp__claude-flow__*) and add Bash(rm -rf:*) deny.
- docs: de-reference the cloud hub in favor of a local instance.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-08 11:44:22 +00:00
..

Agentic QE v3 Implementation Documentation

This directory contains all implementation documentation, planning, and research for Agentic QE v3.

Directory Structure

implementation/
├── adrs/                    # Architecture Decision Records
├── architecture/            # Architecture diagrams & analysis
├── planning/                # Master plans & implementation strategies
├── security/                # Security considerations
└── agents/                  # Agent specifications

Document Index

ADRs (Architecture Decision Records)

Document Description
v3-adrs.md All 10 ADRs (001-010) master document

Planning

Document Description
AQE-V3-MASTER-PLAN.md Complete v3 master plan with DDD architecture

Key Concepts

Domain-Driven Design for QE

Agentic QE v3 uses DDD with 13 bounded contexts:

  1. Test Generation - AI-powered test creation
  2. Test Execution - Parallel execution and retry
  3. Coverage Analysis - O(log n) gap detection
  4. Quality Assessment - Quality gates and metrics
  5. Defect Intelligence - Prediction and analysis
  6. Learning Optimization - Pattern learning and transfer
  7. Code Intelligence - Knowledge graph, dependency and impact analysis
  8. Requirements Validation - Acceptance-criteria and BDD validation
  9. Security Compliance - Security scanning and compliance checks
  10. Contract Testing - Consumer/provider contract validation
  11. Visual Accessibility - Visual regression and a11y auditing
  12. Chaos Resilience - Fault injection and resilience testing
  13. Enterprise Integration - SAP/middleware/E2E enterprise flows

Agent Hierarchy

21 specialized v3 agents organized hierarchically:

  • Queen Coordinator (orchestration)
  • Test Generation Group (4 agents)
  • Quality Gates Group (3 agents)
  • Intelligence Group (3 agents)
  • Execution Group (3 agents)
  • Coverage Group (3 agents)
  • Learning Group (4 agents)

Key ADRs

ADR Decision
ADR-001 Adopt DDD for QE bounded contexts
ADR-002 Event-driven domain communication
ADR-003 Sublinear O(log n) coverage analysis
ADR-004 Plugin architecture for extensions
ADR-005 AI-first test generation

Getting Started

# Use v3 DDD skill
Task("Analyze QE architecture",
     "Design DDD bounded contexts for quality engineering",
     "system-architect")

# Use v3 Queen Coordinator
Task("Orchestrate QE workflow",
     "Coordinate full quality engineering workflow",
     "v3-qe-queen-coordinator")

# Use v3 Test Architect
Task("Generate tests",
     "Create AI-powered test suite for UserService",
     "v3-qe-test-architect")

Last Updated: 2026-01-07 Version: 1.0.0