Cognitive Flexibility Release

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)

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

text

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