learning-coordinator
## When to Use
- Need to check learning stage of a pattern or correction
- Want to identify emerging patterns from repeated corrections
- Need to coordinate promotion/demotion of patterns across memory tiers
- Integrating with correction‑logger and preference‑tracker for learning workflows
## Architecture
### NeverOnce 增强功能
- ✅ **有效性反馈集成**:从增强correction-logger获取有效性分数,跟踪修正使用历史
- ✅ **动态阶段转换算法**:基于有效性的自动阶段提升/降级
- 高有效性模式 → 加速确认
- 低有效性模式 → 自动降级或标记
- ✅ **反馈循环监控**:跟踪模式有效性趋势,识别高/低效学习模式
- ✅ **学习速度计算**:基于有效性和反馈趋势的学习速度评估
- ✅ **增强报告生成**:模式有效性报告、反馈循环统计、学习进度跟踪
- ✅ **自动调整规则**:基于置信度的自动阶段调整,减少人工干预
### 增强算法
1. **阶段置信度计算**:
```
confidence = (repetition_count * 0.4) + (effectiveness_score * 0.4) + (time_factor * 0.2)
```
2. **学习速度评估**:
```
learning_speed = (help_ratio * 0.6) + (effectiveness_trend * 0.4)
```
3. **自动调整阈值**:
- 自动提升: confidence ≥ 0.8
- 自动降级: effectiveness ≤ 0.2
### 集成说明
- **依赖**: 增强correction-logger v2.0.0+(可选,但推荐)
- **数据源**: 从纠正记录器获取有效性分数和反馈历史
- **兼容性**: 原有API完全兼容,新增增强方法可选使用
The plugin provides a `LearningCoordinator` class that:
1. **Monitors learning signals** – watches corrections and preferences via their respective adapters.
2. **Manages learning stages** – tracks patterns through stages: tentative, emerging, pending, confirmed, archived.
3. **Coordinates promotion/demotion** – applies rules for when to move patterns between stages and tiers.
4. **Exposes learning statistics** – reports on learning progress and pattern evolution.
The plugin does not store its own data; it relies on existing adapters (correction‑logger, preference‑tracker) and the learning‑rules file (`learning.md`).
## Installation
```bash
clawhub install learning-coordinator
```
Or manually copy the plugin directory to your workspace skills folder.
## Configuration
Default configuration loads the learning rules file and references other adapters:
```yaml
learning_rules_file: ~/self-improving/learning.md
correction_adapter: "correction_logger"
preference_adapter: "preference_tracker"
auto_create: true
```
## API Reference
### LearningCoordinator Class
```python
from learning_coordinator import LearningCoordinator
coordinator = LearningCoordinator(config=None)
# Get learning statistics
stats = coordinator.get_learning_stats()
# Check emerging patterns
emerging = coordinator.get_emerging_patterns(threshold=2)
# Promote a pattern (after user confirmation)
result = coordinator.promote_pattern(correction_ids=[1, 2, 3], new_status="confirmed")
# Get stage counts
stage_counts = coordinator.get_stage_counts()
# Health check
health = coordinator.health_check()
```
### Adapter Interface
The plugin includes a `LearningCoordinatorAdapter` that conforms to the star‑architecture `MemoryAdapter` base class, providing:
- `health_check()` – reports availability of required adapters and rule file
- `get_stats()` – returns learning statistics (stage counts, promotion rates, etc.)
- `search(query, limit=10)` – searches across learning rules and pattern descriptions
- `sync()` – ensures coordinator state is in sync (no‑op for this plugin)
- `get_learning_stats()`, `get_emerging_patterns()`, `promote_pattern()` – convenience methods
## Integration with Star Architecture
Once installed and its adapter is registered in the star‑architecture registry, other plugins can query learning coordination via the adapter factory:
```python
from integration.adapter_factory import AdapterFactory
factory = AdapterFactory()
coordinator_adapter = factory.get_adapter("learning_coordinator")
if coordinator_adapter:
stats = coordinator_adapter.get_learning_stats()
emerging = coordinator_adapter.get_emerging_patterns(threshold=2)
```
## Learning Rules
The plugin reads the `learning.md` file (see SIPA skill) to obtain:
- **Trigger definitions** – what counts as a learning signal
- **Confirmation flow** – how and when to ask for user confirmation
- **Stage evolution** – rules for moving between stages
- **Anti‑patterns** – what not to learn
The file is treated as read‑only; modifications must be made manually.
## Troubleshooting
**Missing adapters** – If correction‑logger or preference‑tracker adapters are unavailable, the coordinator will operate with limited functionality.
**Rule file not found** – If `learning.md` does not exist, the plugin will create a minimal version based on the SIPA skill's default content.
**Permission errors** – Ensure the process has read access to the learning rules file.
## Related Plugins
- **correction‑logger** – logs user corrections and system improvements
- **preference‑tracker** – manages user preferences and patterns
- **heartbeat‑manager** – manages heartbeat state and logs
- **reflection‑logger** – logs self‑reflection entries
## Version History
- **v0.1.0** – Initial split from SIPA skill, basic coordination, star‑architecture adapter.
## 错误码
| 错误码 | 描述 | 解决方案 |
|--------|------|----------|
| E001 | 未知错误 | 检查日志,联系开发者 |
| E002 | 配置错误 | 验证配置文件格式 |
| E003 | 依赖缺失 | 安装所需依赖包 |
标签
skill
ai