cognitive-flexibility
Cognitive Flexibility Skill - AI cognitive flexibility with 4 modes. Supports automatic mode switching and metacognitive monitoring. Use when: - Complex reasoning and multi-step thinking needed - Self-assessment and reflection required - Cross-scenario knowledge transfer - Creative problem solving - Task complexity > medium (estimated >2 hours)
Best use case
cognitive-flexibility is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Cognitive Flexibility Skill - AI cognitive flexibility with 4 modes. Supports automatic mode switching and metacognitive monitoring. Use when: - Complex reasoning and multi-step thinking needed - Self-assessment and reflection required - Cross-scenario knowledge transfer - Creative problem solving - Task complexity > medium (estimated >2 hours)
Teams using cognitive-flexibility should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/cognitive-flexibility/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How cognitive-flexibility Compares
| Feature / Agent | cognitive-flexibility | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Cognitive Flexibility Skill - AI cognitive flexibility with 4 modes. Supports automatic mode switching and metacognitive monitoring. Use when: - Complex reasoning and multi-step thinking needed - Self-assessment and reflection required - Cross-scenario knowledge transfer - Creative problem solving - Task complexity > medium (estimated >2 hours)
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# Cognitive Flexibility Skill
## Overview
This Skill implements four cognitive modes based on human cognitive science:
| Mode | Name | Driver | Scenario | Core Ability |
|------|------|--------|----------|--------------|
| **OOA** | Experience Mode | Memory-driven | Familiar scenarios | Pattern matching |
| **OODA** | Reasoning Mode | Knowledge-driven | Complex problems | Chain reasoning |
| **OOCA** | Creative Mode | Association-driven | Innovation needs | Analogy generation |
| **OOHA** | Discovery Mode | Hypothesis-driven | Exploration | Hypothesis generation |
## Quick Start
### Basic Usage
```python
from scripts.cognitive_controller import CognitiveController
# Create controller
controller = CognitiveController(confidence_threshold=0.7)
# Execute task (auto mode selection)
task = "Analyze user feedback data"
result = await controller.process(task, tools=tools)
# View result
print(f"Mode: {result['mode']}")
print(f"Answer: {result['answer']}")
print(f"Confidence: {result['assessment']['overall_score']:.2f}")
```
### Manual Mode Selection
```python
# OODA reasoning mode
from scripts.chain_reasoner import OODAReasoner
reasoner = OODAReasoner()
result = await reasoner.process(task, tools=tools)
# OOA experience mode
from scripts.pattern_matcher import PatternMatcher
matcher = PatternMatcher()
result = await matcher.match(task, tools=tools)
# OOCA creative mode
from scripts.creative_explorer import CreativeExplorer
explorer = CreativeExplorer()
result = await explorer.explore(task)
# OOHA discovery mode
from scripts.hypothesis_generator import HypothesisGenerator
generator = HypothesisGenerator()
result = await generator.discover(task)
```
## Features
- **4 Cognitive Modes**: OOA/OODA/OOCA/OOHA
- **Auto Mode Switching**: Cognitive Controller selects best mode
- **Metacognitive Monitoring**: Self-assessment and confidence scoring
- **Usage Tracking**: Complete usage logs and statistics
- **100% Test Coverage**: All tests passing
## File Structure
```
cognitive-flexibility/
├── scripts/
│ ├── __init__.py
│ ├── chain_reasoner.py # OODA reasoning
│ ├── pattern_matcher.py # OOA pattern matching
│ ├── self_assessor.py # Metacognitive monitoring
│ ├── cognitive_controller.py # Mode switching
│ ├── creative_explorer.py # OOCA creative mode
│ ├── hypothesis_generator.py # OOHA discovery mode
│ └── usage_monitor.py # Usage tracking
├── references/
│ └── ooda-guide.md
├── tests/
│ └── test_cognitive_skills.py
├── SKILL.md
├── README.md
└── MONITORING-GUIDE.md
```
## Testing
```bash
# Run tests
python tests/test_cognitive_skills.py
# Expected output: 6/6 tests passed (100%)
```
## Monitoring
```python
from scripts.usage_monitor import UsageMonitor
monitor = UsageMonitor()
# Get usage stats
stats = monitor.get_stats(days=7)
# Generate report
report = monitor.generate_report(days=7)
print(report)
```
## Requirements
- Python >= 3.8
- OpenClaw >= 2026.3.28
- No external dependencies
## License
MIT License
## Support
- **Documentation**: See README.md and MONITORING-GUIDE.md
- **Issues**: GitHub Issues
- **Community**: Discord #skills-feedback
---
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