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)

3,891 stars

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

$curl -o ~/.claude/skills/cognitive-flexibility/SKILL.md --create-dirs "https://raw.githubusercontent.com/openclaw/skills/main/skills/alpha963852/cognitive-flexibility/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/cognitive-flexibility/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How cognitive-flexibility Compares

Feature / Agentcognitive-flexibilityStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/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.

Related Guides

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

---

_DaoShi · Cognitive Flexibility Skill v2.1.0_

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