YingClaw v2.0 Released: New Workflow Engine and Multi-Model Routing
YingClaw v2.0 is officially released. This version represents a major leap forward in task execution quality and controllability.
🆕 Key Updates
1. Workflow Engine
v2.0 introduces a mandatory four-stage execution pipeline:
Requirements Clarification → Project Assessment → Plan Confirmation → Parallel Execution
Each stage has clear deliverables, and every step is traceable. No more "the Agent went off the rails and you have no idea what happened."
2. Multi-Model Routing
You can now assign different models to different scenarios:
model_routing:
default: gpt-4o
code_review: claude-opus-4
translation: deepseek-chat
simple_task: llama-3-8b # Local model to save costs
High-frequency simple tasks use cheaper models; complex reasoning uses top-tier models — balancing performance and cost.
3. Memory System Refactored
Upgraded from a single MEMORY.md file to a structured memory database:
core: Permanent core memoriesuser: User preference memoriesdaily: Session notes with 7-day auto-expiry
Query efficiency improved 10x, with semantic search support.
4. Security Policy Upgrades
New command allowlist/blocklist mechanism with granular permission control by directory and command type.
📊 Performance Comparison
| Metric | v1.x | v2.0 |
|---|---|---|
| Complex task completion | 72% | 91% |
| Avg. execution steps | 12.3 | 7.8 |
| Memory usage | 480MB | 320MB |
| Startup time | 3.2s | 1.1s |
📦 How to Upgrade
npm update -g yingclaw
yingclaw --version # Should output v2.0.x
Configuration files are backward-compatible. No additional changes needed.
What's Next
v2.1 roadmap: visual workflow editor, skill marketplace official launch, native WeCom integration. Stay tuned!