Files
Profa 5380421f1e docs: update implementation progress analysis - MCP server 100% complete
- Corrected MCP server implementation status from 0% to 100%
- Added details of 52 MCP tools across 8 categories
- Updated overall progress from 46% to 54% (7/13 areas complete)
- Added MCP server architecture details (357 lines server, 1836 lines tools, 60+ handlers)
- Updated integration metrics: MCP Tools 52/50 (104% - exceeded target)
- Removed MCP server from future work (already production-ready)

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-10-06 17:50:41 +00:00

2.5 KiB

Claude Code Configuration

Project Overview

This project uses Agentic QE Fleet for comprehensive quality engineering.

🚀 AGENTIC QE FLEET - CRITICAL RULES

📦 Project Structure

The AQE implementation is in /agentic-qe/ subfolder by design:

  • This is a modular monorepo pattern
  • Core AQE system is separate from projects using it
  • This allows:
    • Centralized QE agent management
    • Reusability across multiple projects
    • Clean separation of concerns
    • Easy updates and maintenance

🤖 Available QE Agents

  • qe-test-generator: AI-powered test creation with property-based testing
  • qe-test-executor: Parallel test execution with retry logic
  • qe-coverage-analyzer: O(log n) coverage optimization with gap detection
  • qe-quality-gate: Intelligent go/no-go decisions with risk assessment
  • qe-performance-tester: Load testing and bottleneck detection
  • qe-security-scanner: SAST/DAST integration with CVE monitoring

⚡ Agent Usage

Spawn agents via Claude Code Task tool:

Task("Generate tests", "Create comprehensive test suite", "qe-test-generator")
Task("Execute tests", "Run tests in parallel", "qe-test-executor")
Task("Analyze coverage", "Find coverage gaps", "qe-coverage-analyzer")

Or use MCP tools for coordination:

mcp__agentic_qe__fleet_init({ topology: "hierarchical" })
mcp__agentic_qe__test_generate({ framework: "jest", coverage: 0.95 })

🎯 Best Practices

  1. Initialize Fleet First: Run aqe init before using agents
  2. Use Parallel Execution: Spawn multiple agents in single messages
  3. Leverage Memory: Agents share state via Claude Flow memory
  4. Monitor Progress: Check agent status with aqe status
  5. Claude Flow Integration: Agents use hooks for coordination

⚠️ Common Pitfalls

  • Don't expect agents in root .claude/agents/ - they're in project's .claude/agents/
  • Real vs Mock: aqe init creates real agents (not mocked demos)
  • Hooks are intentional: Agents coordinate via Claude Flow hooks
  • Memory is shared: All agents can access aqe/* memory keys

🔧 Commands

  • aqe init - Initialize AQE fleet in current project
  • aqe status - Show fleet status
  • aqe test <module> - Generate tests for a module
  • aqe coverage - Analyze test coverage
  • aqe quality - Run quality gate check
  • aqe agent spawn --name <agent> - Spawn specific agent
  • aqe agent execute --name <agent> --task "<task>" - Execute task

Agentic QE Fleet - Enterprise-grade quality engineering powered by AI and sublinear algorithms