Use when running comprehensive WCAG accessibility audits with axe-core + pa11y + Lighthouse, generating context-aware remediation, or testing video accessibility. Supports 3-tier browser cascade with graceful degradation.
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Migrate Agentic QE projects from v2 to v3 with zero data loss
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实测评分 未实测
查看安装方法安装前可以查看交给 AI 代理的指令内容。
<default_to_action> When migrating from v2 to v3:
Never delete v2 data without explicit user confirmation. </default_to_action>
# When v3 becomes main release, just update the package
npm install agentic-qe@latest
# Run migration
aqe migrate
# Or use this skill
/aqe-v2-v3-migration
| Component | v2 Location | v3 Location | Auto-Migrate |
|---|---|---|---|
| Memory DB | .agentic-qe/memory.db | .aqe/agentdb/ | Yes |
| Config | .agentic-qe/config.json | .aqe/config.json | Yes |
| Patterns | .agentic-qe/patterns/ | .aqe/reasoning-bank/ | Yes |
| Cache | .agentic-qe/cache/ | .aqe/cache/ | Optional |
| Logs | .agentic-qe/logs/ | .aqe/logs/ | No (fresh start) |
.agentic-qe/ directory)aqe --version (should be 2.x.x)npm run backup (in v2 project)npm install agentic-qe@latestaqe migrateaqe testaqe coverageaqe patterns listv2 Structure: v3 Structure:
├── src/mcp/tools/ ├── src/domains/
│ ├── test-*.ts (40+ tools) │ ├── test-generation/
│ └── ... │ ├── test-execution/
├── src/core/agents/ │ ├── coverage-analysis/
│ ├── mixed agents │ ├── quality-assessment/
│ └── ... │ ├── defect-intelligence/
└── src/core/memory/ │ ├── requirements-validation/
└── scattered impls │ ├── code-intelligence/
│ ├── security-compliance/
│ ├── contract-testing/
│ ├── visual-accessibility/
│ ├── chaos-resilience/
│ └── learning-optimization/
├── src/kernel/
│ ├── event-bus.ts
│ └── coordinator.ts
└── src/mcp/
└── domain-handlers.ts
| v2 API | v3 API | Notes |
|---|---|---|
aqe init | aqe init | Different binary |
aqe.generateTests() | testGeneration.generate() | Domain-based |
aqe.analyzeGaps() | coverageAnalysis.findGaps() | O(log n) now |
memory.store() | agentDB.store() | HNSW-indexed |
patterns.learn() | reasoningBank.record() | With verdicts |
{
"version": "2.8.2",
"memory": {
"path": ".agentic-qe/memory.db",
"type": "sqlite"
},
"agents": {
"enabled": ["test-generator", "coverage-analyzer"]
}
}
{
"version": "3.0.0",
"kernel": {
"eventBus": "in-memory",
"coordinator": "queen"
},
"domains": {
"test-generation": { "enabled": true },
"test-execution": { "enabled": true },
"coverage-analysis": {
"enabled": true,
"algorithm": "hnsw",
"dimensions": 128
}
},
"memory": {
"backend": "agentdb",
"path": ".aqe/agentdb/",
"hnsw": {
"M": 16,
"efConstruction": 200
}
},
"learning": {
"reasoningBank": true,
"sona": true
}
}
// v2: Direct SQLite access
import Database from 'better-sqlite3';
const db = new Database('.agentic-qe/memory.db');
const patterns = db.prepare('SELECT * FROM patterns').all();
// v3: AgentDB with HNSW
import { AgentDB } from 'agentic-qe';
const db = new AgentDB('.aqe/agentdb/');
await db.initialize({ dimensions: 128, M: 16 });
// Migration script transfers and indexes
for (const pattern of v2Patterns) {
await db.store({
key: pattern.id,
value: pattern.data,
embedding: await generateEmbedding(pattern.data),
metadata: { migratedFrom: 'v2', originalId: pattern.id }
});
}
Import Paths
// v2
import { AgenticQE } from 'agentic-qe';
// v3 (when v3 becomes main release, package name is still 'agentic-qe')
import { TestGenerationDomain } from 'agentic-qe/domains';
CLI Commands
# v2
aqe test --parallel
# v3
aqe test --workers=4 --topology=mesh
MCP Server
# v2
claude mcp add aqe -- npx aqe-mcp
# v3 (same CLI name, enhanced capabilities)
claude mcp add aqe -- npx aqe mcp
aqe.runTests() → Use domain-specific methodsIf migration fails or you need to revert:
# 1. v3 does NOT modify v2 data
# Your .agentic-qe/ folder is untouched
# 2. Downgrade to v2
npm install agentic-qe@2.x
rm -rf .aqe/
# 3. Continue using v2
aqe --version # Should show 2.x.x
// Use Task tool to spawn migration agents in parallel
Task({
prompt: "Analyze v2 memory.db and extract all patterns",
subagent_type: "researcher",
description: "Analyze v2 patterns"
});
Task({
prompt: "Convert v2 config to v3 format",
subagent_type: "coder",
description: "Convert config"
});
Task({
prompt: "Validate migration results",
subagent_type: "tester",
description: "Validate migration"
});
| Issue | Cause | Solution |
|---|---|---|
| "Cannot find .agentic-qe/" | No v2 installation | Run aqe init first |
| "Memory migration failed" | Corrupted SQLite | Use backup: npm run backup:restore |
| "HNSW index error" | Dimension mismatch | Set dimensions: 128 in config |
| "Pattern not found" | Not migrated | Re-run: aqe migrate --patterns |
# Run migration with debug output
DEBUG=aqe:migrate aqe migrate
# Check migration logs
cat .aqe/logs/migration.log
[v2-v3-migration] tag| v2 Version | v3 Version | Migration Support |
|---|---|---|
| 2.8.x | 3.0.x | Full |
| 2.7.x | 3.0.x | Full |
| 2.6.x | 3.0.x | Partial (config only) |
| 2.5.x and below | 3.0.x | Manual migration |
Skill Version: 1.0.0 | Last Updated: 2026-01-11
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Use when running comprehensive WCAG accessibility audits with axe-core + pa11y + Lighthouse, generating context-aware remediation, or testing video accessibility. Supports 3-tier browser cascade with graceful degradation.
中文简介正在准备中。当前显示原文说明。
WCAG 2.2 compliance testing, screen reader validation, and inclusive design verification. Use when ensuring legal compliance (ADA, Section 508), testing for disabilities, or building accessible applications for 1 billion disabled users globally.
中文简介正在准备中。当前显示原文说明。
Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
中文简介正在准备中。当前显示原文说明。
Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.
中文简介正在准备中。当前显示原文说明。
Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.
中文简介正在准备中。当前显示原文说明。
Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.
中文简介正在准备中。当前显示原文说明。