This release fixes the long-standing issue where Task agents would not reliably persist learning data. Now learnings are captured automatically. ## Major Feature: Automatic Learning Capture - New `scripts/hooks/capture-task-learning.js` PostToolUse hook - Captures agent type, task output, duration, token usage - Calculates reward based on output quality indicators - Stores to `learning_experiences` table in memory.db - Deduplication: skips if agent already stored via MCP (60s window) - Updated `aqe init` to copy hook scripts to user projects - New phase: "Hook Scripts" in initialization pipeline - Settings.json includes automatic learning capture hook ## Clean QE-Only Configuration - Removed all claude-flow and agentdb dependencies from QE agents - Updated settings.json with clean AQE env vars - Removed agentdb.db references (deprecated) - All persistence unified to `.agentic-qe/memory.db` ## Agent Learning Instructions Audit - Added MANDATORY `<learning_protocol>` sections to all 30 QE agents - 19 main QE agents updated - 11 QE subagents updated - Instructions include: query past learnings, store experiences, store patterns ## Files Changed - 30 agent/subagent .md files with learning protocols - scripts/hooks/capture-task-learning.js (new) - src/cli/init/claude-config.ts - clean QE-only hooks - src/cli/init/helpers.ts - copyHookScripts() function - src/cli/init/index.ts - Hook Scripts phase - .claude/settings.json - removed claude-flow hooks - Version bumped to 2.3.0 in all required files 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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Claude Code Configuration - Agentic QE Fleet
⚠️ CRITICAL POLICIES
Integrity Rule (ABSOLUTE)
- ❌ NO shortcuts - do the work properly or don't do it
- ❌ NO fake data - use real data, real tests, real results
- ❌ NO false claims - only report what actually works and is verified
- ✅ ALWAYS implement all code/tests with proper implementation
- ✅ ALWAYS verify before claiming success
- ✅ ALWAYS use real database queries, not mocks, for integration tests
- ✅ ALWAYS run actual tests, not assume they pass
We value the quality we deliver to our users.
Git Operations
- ❌ NEVER auto-commit/push without explicit user request
- ✅ ALWAYS wait for: "commit this" or "push to main"
- 📋 Full policy: docs/policies/git-operations.md
Release Verification
- ❌ NEVER release without
aqe initverification - ✅ ALWAYS test at least one agent with real database queries
- 📋 Full checklist: docs/policies/release-verification.md
Test Execution
- ❌ NEVER run
npm test(OOM risk in DevPod/Codespaces) - ✅ ALWAYS use batched scripts:
npm run test:unit,npm run test:integration - 📋 Full policy: docs/policies/test-execution.md
File Organization
- ❌ NEVER save working files to root folder
- ✅ ALWAYS use:
/docs,/tests,/src,/scripts,/examples
Release Process
- ❌ NEVER commit directly to main - use feature branches with PRs
- ❌ NEVER forget package-lock.json when updating versions
- ✅ ALWAYS use
mcp__agentic-qe__memory_storewithpersist: truefor learnings (NOTclaude-flow)
Version Update Checklist (all files to update):
package.json- version fieldpackage-lock.json- runnpm install --package-lock-onlyREADME.md- Version badge (line 12)CHANGELOG.md- Add new version section with changessrc/mcp/server-instructions.ts-SERVER_VERSIONconstantsrc/core/memory/HNSWVectorMemory.ts- version ingetImplementationInfo()
Skip: .claude/agents/sparc/specification.md - FR-X.X.X are feature requirement IDs, NOT versions
Release Workflow:
git checkout -b release/vX.X.X # 1. Create branch
# Update all version files above # 2. Update versions
npm run test:fast # 3. Run tests
git commit -m "chore(release): bump version to vX.X.X"
git push -u origin release/vX.X.X # 4. Push branch
gh pr create # 5. Create PR to main
# Wait for CI and review # 6. Review
# Merge PR # 7. Merge
git tag vX.X.X && git push origin vX.X.X # 8. Tag
gh release create vX.X.X # 9. GitHub release
npm publish --access public # 10. npm publish
🤖 Agentic QE Fleet Quick Reference
19 QE Agents: Test generation, coverage analysis, performance, security, flaky detection, QX analysis
11 QE Subagents: TDD specialists, code reviewers, integration testers
41 QE Skills: agentic-quality-engineering, tdd-london-chicago, api-testing-patterns, six-thinking-hats, brutal-honesty-review, sherlock-review, cicd-pipeline-qe-orchestrator, accessibility-testing, shift-left-testing, testability-scoring (contributed by @fndlalit)
8 Slash Commands: /aqe-execute, /aqe-generate, /aqe-coverage, /aqe-quality
📚 Complete Documentation
- Agent Reference - All 19 main agents + 11 subagents with capabilities and usage
- Skills Reference - All 41 QE skills organized by category
- Usage Guide - Complete usage examples and workflows
🎯 Quick Start
Spawn agents:
Task("Generate tests", "Create test suite for UserService", "qe-test-generator")
Task("Analyze coverage", "Find gaps using O(log n)", "qe-coverage-analyzer")
Check learning status:
aqe learn status --agent test-gen
aqe patterns list --framework jest
💡 Key Principles
- Use Task tool for agent execution (not just MCP)
- Batch all operations in single messages (TodoWrite, file ops, etc.)
- Test with actual databases, not mocks
- Document only what actually works
Claude Flow Integration (Preserved from original CLAUDE.md)
🚨 CRITICAL: CONCURRENT EXECUTION & FILE MANAGEMENT
ABSOLUTE RULES:
- ALL operations MUST be concurrent/parallel in a single message
- NEVER save working files, text/mds and tests to the root folder
- ALWAYS organize files in appropriate subdirectories
- USE CLAUDE CODE'S TASK TOOL for spawning agents concurrently, not just MCP
⚡ GOLDEN RULE: "1 MESSAGE = ALL RELATED OPERATIONS"
MANDATORY PATTERNS:
- TodoWrite: ALWAYS batch ALL todos in ONE call (5-10+ todos minimum)
- Task tool (Claude Code): ALWAYS spawn ALL agents in ONE message with full instructions
- File operations: ALWAYS batch ALL reads/writes/edits in ONE message
- Bash commands: ALWAYS batch ALL terminal operations in ONE message
- Memory operations: ALWAYS batch ALL memory store/retrieve in ONE message
🎯 CRITICAL: Claude Code Task Tool for Claude Flow Agent Execution
Claude Code's Task tool is the PRIMARY way to spawn Claude Flow agents:
// ✅ CORRECT: Use Claude Code's Task tool for parallel agent execution
[Single Message]:
Task("Research agent", "Analyze requirements and patterns...", "researcher")
Task("Coder agent", "Implement core features...", "coder")
Task("Tester agent", "Create comprehensive tests...", "tester")
Task("Reviewer agent", "Review code quality...", "reviewer")
Task("Architect agent", "Design system architecture...", "system-architect")
Claude Flow MCP tools are ONLY for coordination setup:
mcp__claude-flow__swarm_init- Initialize coordination topologymcp__claude-flow__agent_spawn- Define agent types for coordinationmcp__claude-flow__task_orchestrate- Orchestrate high-level workflows
📁 File Organization Rules
NEVER save to root folder. Use these directories:
/src- Source code files/tests- Test files/docs- Documentation and markdown files/config- Configuration files/scripts- Utility scripts/examples- Example code
Project Overview
This project uses SPARC (Specification, Pseudocode, Architecture, Refinement, Completion) methodology with Claude-Flow orchestration for systematic Test-Driven Development.
SPARC Commands
Core Commands
npx claude-flow sparc modes- List available modesnpx claude-flow sparc run <mode> "<task>"- Execute specific modenpx claude-flow sparc tdd "<feature>"- Run complete TDD workflownpx claude-flow sparc info <mode>- Get mode details
Batchtools Commands
npx claude-flow sparc batch <modes> "<task>"- Parallel executionnpx claude-flow sparc pipeline "<task>"- Full pipeline processingnpx claude-flow sparc concurrent <mode> "<tasks-file>"- Multi-task processing
Build Commands
npm run build- Build projectnpm run test- Run testsnpm run lint- Lintingnpm run typecheck- Type checking
SPARC Workflow Phases
- Specification - Requirements analysis (
sparc run spec-pseudocode) - Pseudocode - Algorithm design (
sparc run spec-pseudocode) - Architecture - System design (
sparc run architect) - Refinement - TDD implementation (
sparc tdd) - Completion - Integration (
sparc run integration)
Code Style & Best Practices
- Modular Design: Files under 500 lines
- Environment Safety: Never hardcode secrets
- Test-First: Write tests before implementation
- Clean Architecture: Separate concerns
- Documentation: Keep updated
🚀 Claude Flow Available Agents (54 Total)
Core Development
coder, reviewer, tester, planner, researcher
Swarm Coordination
hierarchical-coordinator, mesh-coordinator, adaptive-coordinator, collective-intelligence-coordinator, swarm-memory-manager
Consensus & Distributed
byzantine-coordinator, raft-manager, gossip-coordinator, consensus-builder, crdt-synchronizer, quorum-manager, security-manager
Performance & Optimization
perf-analyzer, performance-benchmarker, task-orchestrator, memory-coordinator, smart-agent
GitHub & Repository
github-modes, pr-manager, code-review-swarm, issue-tracker, release-manager, workflow-automation, project-board-sync, repo-architect, multi-repo-swarm
SPARC Methodology
sparc-coord, sparc-coder, specification, pseudocode, architecture, refinement
Specialized Development
backend-dev, mobile-dev, ml-developer, cicd-engineer, api-docs, system-architect, code-analyzer, base-template-generator
Claude Flow Testing & Validation
tdd-london-swarm, production-validator
Migration & Planning
migration-planner, swarm-init
🎯 Claude Code vs MCP Tools
Claude Code Handles ALL EXECUTION:
- Task tool: Spawn and run agents concurrently for actual work
- File operations (Read, Write, Edit, MultiEdit, Glob, Grep)
- Code generation and programming
- Bash commands and system operations
- Implementation work
- Project navigation and analysis
- TodoWrite and task management
- Git operations
- Package management
- Testing and debugging
MCP Tools ONLY COORDINATE:
- Swarm initialization (topology setup)
- Agent type definitions (coordination patterns)
- Task orchestration (high-level planning)
- Memory management
- Neural features
- Performance tracking
- GitHub integration
KEY: MCP coordinates the strategy, Claude Code's Task tool executes with real agents.
🚀 Quick Setup
# Add MCP servers (Claude Flow required, others optional)
claude mcp add claude-flow npx claude-flow@alpha mcp start
claude mcp add ruv-swarm npx ruv-swarm mcp start # Optional: Enhanced coordination
MCP Tool Categories
Coordination
swarm_init, agent_spawn, task_orchestrate
Monitoring
swarm_status, agent_list, agent_metrics, task_status, task_results
Memory & Neural
memory_usage, neural_status, neural_train, neural_patterns
GitHub Integration
github_swarm, repo_analyze, pr_enhance, issue_triage, code_review
System
benchmark_run, features_detect, swarm_monitor
🚀 Agent Execution Flow with Claude Code
The Correct Pattern:
- Optional: Use MCP tools to set up coordination topology
- REQUIRED: Use Claude Code's Task tool to spawn agents that do actual work
- REQUIRED: Each agent runs hooks for coordination
- REQUIRED: Batch all operations in single messages
Example Full-Stack Development:
// Single message with all agent spawning via Claude Code's Task tool
[Parallel Agent Execution]:
Task("Backend Developer", "Build REST API with Express. Use hooks for coordination.", "backend-dev")
Task("Frontend Developer", "Create React UI. Coordinate with backend via memory.", "coder")
Task("Database Architect", "Design PostgreSQL schema. Store schema in memory.", "code-analyzer")
Task("Test Engineer", "Write Jest tests. Check memory for API contracts.", "tester")
Task("DevOps Engineer", "Setup Docker and CI/CD. Document in memory.", "cicd-engineer")
Task("Security Auditor", "Review authentication. Report findings via hooks.", "reviewer")
// All todos batched together
TodoWrite { todos: [...8-10 todos...] }
// All file operations together
Write "backend/server.js"
Write "frontend/App.jsx"
Write "database/schema.sql"
📋 Claude Flow Agent Coordination Protocol
Every Claude Flow Agent Spawned via Task Tool MUST:
1️⃣ BEFORE Work:
npx claude-flow@alpha hooks pre-task --description "[task]"
npx claude-flow@alpha hooks session-restore --session-id "swarm-[id]"
2️⃣ DURING Work:
npx claude-flow@alpha hooks post-edit --file "[file]" --memory-key "swarm/[agent]/[step]"
npx claude-flow@alpha hooks notify --message "[what was done]"
3️⃣ AFTER Work:
npx claude-flow@alpha hooks post-task --task-id "[task]"
npx claude-flow@alpha hooks session-end --export-metrics true
🎯 Claude Flow Concurrent Execution Examples
✅ Claude Flow CORRECT WORKFLOW: MCP Coordinates, Claude Code Executes
// Step 1: MCP tools set up coordination (optional, for complex tasks)
[Single Message - Coordination Setup]:
mcp__claude-flow__swarm_init { topology: "mesh", maxAgents: 6 }
mcp__claude-flow__agent_spawn { type: "researcher" }
mcp__claude-flow__agent_spawn { type: "coder" }
mcp__claude-flow__agent_spawn { type: "tester" }
// Step 2: Claude Code Task tool spawns ACTUAL agents that do the work
[Single Message - Parallel Agent Execution]:
// Claude Code's Task tool spawns real agents concurrently
Task("Research agent", "Analyze API requirements and best practices. Check memory for prior decisions.", "researcher")
Task("Coder agent", "Implement REST endpoints with authentication. Coordinate via hooks.", "coder")
Task("Database agent", "Design and implement database schema. Store decisions in memory.", "code-analyzer")
Task("Tester agent", "Create comprehensive test suite with 90% coverage.", "tester")
Task("Reviewer agent", "Review code quality and security. Document findings.", "reviewer")
// Batch ALL todos in ONE call
TodoWrite { todos: [
{id: "1", content: "Research API patterns", status: "in_progress", priority: "high"},
{id: "2", content: "Design database schema", status: "in_progress", priority: "high"},
{id: "3", content: "Implement authentication", status: "pending", priority: "high"},
{id: "4", content: "Build REST endpoints", status: "pending", priority: "high"},
{id: "5", content: "Write unit tests", status: "pending", priority: "medium"},
{id: "6", content: "Integration tests", status: "pending", priority: "medium"},
{id: "7", content: "API documentation", status: "pending", priority: "low"},
{id: "8", content: "Performance optimization", status: "pending", priority: "low"}
]}
// Parallel file operations
Bash "mkdir -p app/{src,tests,docs,config}"
Write "app/package.json"
Write "app/src/server.js"
Write "app/tests/server.test.js"
Write "app/docs/API.md"
❌ WRONG (Multiple Messages):
Message 1: mcp__claude-flow__swarm_init
Message 2: Task("agent 1")
Message 3: TodoWrite { todos: [single todo] }
Message 4: Write "file.js"
// This breaks parallel coordination!
Hooks Integration
Pre-Operation
- Auto-assign agents by file type
- Validate commands for safety
- Prepare resources automatically
- Optimize topology by complexity
- Cache searches
Post-Operation
- Auto-format code
- Train neural patterns
- Update memory
- Analyze performance
- Track token usage
Session Management
- Generate summaries
- Persist state
- Track metrics
- Restore context
- Export workflows
📊 Visualization Dashboard
Agent activity is automatically visualized in real-time when services are running.
Starting the Visualization
# Terminal 1: Start backend services (WebSocket + REST API)
npx tsx scripts/start-visualization-services.ts
# Terminal 2: Start frontend dashboard
cd frontend && npm run dev
Then open http://localhost:3000 to view the dashboard.
Auto-Emit Events (Hook Integration)
Task agents automatically emit visualization events via Claude Code hooks:
- PreToolUse hook: Emits
agent:spawnedandagent:startedevents when Task tool is invoked - PostToolUse hook: Emits
agent:completedoragent:errorevents when Task completes
No manual action required - just use the Task tool and agents appear in the visualization!
Manual Event Emission
For custom workflows or debugging:
# Emit spawn event with agent type
npx tsx scripts/emit-agent-event.ts spawn <agentId> <agentType>
# Emit start event
npx tsx scripts/emit-agent-event.ts start <agentId>
# Emit completion event with duration (ms)
npx tsx scripts/emit-agent-event.ts complete <agentId> [duration]
# Emit error event
npx tsx scripts/emit-agent-event.ts error <agentId> "Error message"
Programmatic API
import { emitAgentSpawn, emitAgentComplete, emitAgentError } from './src/visualization';
// Emit events in your code
await emitAgentSpawn('my-agent', 'researcher');
await emitAgentComplete('my-agent', 5000);
await emitAgentError('my-agent', 'Something went wrong');
Event Types
| Event | Status | When |
|---|---|---|
agent:spawned |
idle |
Agent created |
agent:started |
running |
Agent begins work |
agent:completed |
completed |
Agent finishes |
agent:error |
error |
Agent fails |
Integration Tips
- Start with basic swarm init
- Scale agents gradually
- Use memory for context
- Monitor progress regularly
- Train patterns from success
- Enable hooks automation
- Use GitHub tools first
Support
- Documentation: https://github.com/ruvnet/claude-flow
- Issues: https://github.com/ruvnet/claude-flow/issues
Remember: Claude Flow coordinates, Claude Code creates!
important-instruction-reminders
Do what has been asked; nothing more, nothing less. NEVER create files unless they're absolutely necessary for achieving your goal. ALWAYS prefer editing an existing file to creating a new one. NEVER proactively create documentation files (*.md) or README files. Only create documentation files if explicitly requested by the User. Never save working files, text/mds and tests to the root folder.
Generated by: Agentic QE Fleet v2.3.0 Initialization Date: 2025-12-08T13:48:54.968Z Fleet Topology: hierarchical
- We always implement all the code/tests, with proper implementation. We value the quality we deliver to our users.