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Cognitive Flexibility Release
作者
Alpha963852
· GitHub ↗
· v2.1.0
· MIT-0
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当前安装
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版本数
在 OpenClaw 中安装
/install cognitive-flexibility
功能描述
Cognitive Flexibility Skill - AI cognitive flexibility with 4 modes. Supports automatic mode switching and metacognitive monitoring. Use when: - Complex reas...
使用说明 (SKILL.md)
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
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
# 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
# Run tests
python tests/test_cognitive_skills.py
# Expected output: 6/6 tests passed (100%)
Monitoring
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
安全使用建议
This skill appears coherent and implements the four cognitive modes as described. Before installing: 1) Confirm the skill source/owner (top-level metadata shows no homepage while the package files reference GitHub/ClawHub URLs); 2) Run the included tests locally (python tests/test_cognitive_skills.py) in a sandbox to validate behavior; 3) Note that the skill will create local logs/feedback files under its directory — review those files for any sensitive data your agent might write; 4) When granting runtime tools to the agent, be intentional: memory_search and local Read/Write are necessary for functionality, but web_search and sessions_send can cause data to be transmitted externally — disable them unless you need external lookups or inter-session messaging; 5) If you plan to publish or run the provided publish scripts, follow token/browser auth guidance carefully and avoid pasting sensitive tokens into logs or public places. If you want extra assurance, inspect the omitted files/tests for network calls or unexpected file system paths before enabling the skill for production workloads.
能力标签
能力评估
Purpose & Capability
The name/description (cognitive flexibility with OOA/OODA/OOCA/OOHA modes) match the included implementation files (reasoner, controller, pattern matcher, self-assessor, usage monitor). There are no unrelated binaries, environment variables, or cloud credentials requested. The allowed tools (memory_search, web_search, Read/Write/Edit) are reasonable for a reasoning/monitoring skill that can consult memory and local files; sessions_send is listed but not used in the shown code.
Instruction Scope
SKILL.md and code instruct the agent to use tools (memory_search, web_search, Read/Write/Edit) and to log usage to local files. The code reads/writes only local files inside the skill (logs/, feedback files) and calls tools.memory_search when provided. There are no instructions to read arbitrary system files or to exfiltrate data to external endpoints. However: the allowed-tools list includes sessions_send and web_search (web_search is referenced in docs as an optional external verification step). If an agent is granted web_search or sessions_send at runtime those tools could transmit context externally — this is a capability the user should choose deliberately.
Install Mechanism
No install specification is provided (instruction-only for the platform) and there are no downloads or third‑party package installs in the manifest. The package includes only Python source that uses standard library modules. This is low-risk from an installation/extraction perspective.
Credentials
The skill declares no required environment variables, no primary credential, and no config paths. Code does not attempt to read process environment or secret files. This is proportionate to the skill's purpose.
Persistence & Privilege
always:false (default) and the skill does not request system-wide persistence. It writes diagnostic and usage logs under the skill's directory (logs/, feedback files) which is normal for monitoring. Autonomous invocation (model invocation enabled) is the platform default and not a unique privilege here.
如何使用
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install cognitive-flexibility - 安装完成后,直接呼叫该 Skill 的名称或使用
/cognitive-flexibility触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v2.1.0
Cognitive Flexibility Skill v2.1.0
- Introduces a clear description of four cognitive modes: OOA (experience), OODA (reasoning), OOCA (creative), OOHA (discovery).
- Adds support for automatic mode switching and metacognitive monitoring with self-assessment and confidence scoring.
- Provides examples for both automatic and manual mode selection in code.
- Highlights usage tracking with complete logs and statistics.
- Confirms 100% test coverage with all tests passing.
- Expands documentation and quick start for improved usability.
元数据
常见问题
Cognitive Flexibility Release 是什么?
Cognitive Flexibility Skill - AI cognitive flexibility with 4 modes. Supports automatic mode switching and metacognitive monitoring. Use when: - Complex reas... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 111 次。
如何安装 Cognitive Flexibility Release?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install cognitive-flexibility」即可一键安装,无需额外配置。
Cognitive Flexibility Release 是免费的吗?
是的,Cognitive Flexibility Release 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Cognitive Flexibility Release 支持哪些平台?
Cognitive Flexibility Release 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 Cognitive Flexibility Release?
由 Alpha963852(@alpha963852)开发并维护,当前版本 v2.1.0。
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