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Agent Skill · 研究检索

learn-cog(学习齿轮)

learn-cog 用于记录任务执行中的错误、用户纠正、经验和能力缺口,适合在 OpenClaw 中希望让 Agent 持续沉淀问题、修正和最佳实践时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

learn-cog 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为调用外部服务;许可证为 MIT-0,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 1,125。

总安装 118,460周安装 4,746GitHub Stars 7下载 38,348核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.12

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:learn-cog(学习齿轮)
来源仓库:https://github.com/nitishgargiitd/learn-cog
安装命令:
openclaw skills install learn-cog
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install learn-cog

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

持续记录任务执行中的错误、纠正和经验缺口,助力Agent自我优化。适用于希望Agent沉淀问题、修正行为并积累最佳实践的协作环境。自动捕获交互反馈,支持跨会话的知识累积与能力迭代。安装前需评估权限边界、数据读写风险及长期维护状态。建议配合原始README核验实际集成方式与安全策略。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install learn-cog;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要调用外部服务,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

learn-cog 怎么安装?

在终端执行 openclaw skills install learn-cog。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

learn-cog 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

learn-cog 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

learn-cog 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

learn-cog 用的人多吗?

公开数据是累计安装 118,460 次,近一周安装 4,746 次,下载 38,348 次,GitHub 7 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

learn-cog 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
learn-cog

学习齿轮 · 本页

118,4607调用外部服务MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
learn-cog
description
AI tutoring and education powered by CellCog. Study guides, exam prep, coding tutorials, language learning, math help, science explanations, practice problems — every subject, every level. Explains concepts via diagrams, analogies, worked examples, and interactive lessons.
metadata
openclaw
emoji
📚
os
[darwin, linux, windows]
requires
bins
[python3]
env
[CELLCOG_API_KEY]
author
CellCog
homepage
https://cellcog.ai
dependencies
[cellcog]

Learn Cog - The Tutor That Explains Five Different Ways

The best tutors explain the same concept five different ways. CellCog does too.

#1 on DeepResearch Bench (Apr 2026) for reasoning depth — deep enough to break concepts into first principles — combined with multi-modal output for every learning style: diagrams, analogies, worked examples, practice problems, interactive explanations, and full study guides. Any subject, any level.

How to Use

For your first CellCog task in a session, read the cellcog skill for the full SDK reference — file handling, chat modes, timeouts, and more.

OpenClaw (fire-and-forget):

result = client.create_chat(
    prompt="[your task prompt]",
    notify_session_key="agent:main:main",
    task_label="my-task",
    chat_mode="agent",
)

All agents except OpenClaw (blocks until done):

from cellcog import CellCogClient
client = CellCogClient(agent_provider="openclaw|cursor|claude-code|codex|...")
result = client.create_chat(
    prompt="[your task prompt]",
    task_label="my-task",
    chat_mode="agent",
)
print(result["message"])

How Learn-Cog Helps

Concept Explanations

Understand anything:

  • Break It Down: "Explain quantum entanglement like I'm 10 years old"
  • Multiple Angles: "Explain recursion using 3 different analogies"
  • Deep Dives: "Give me a comprehensive explanation of how neural networks learn"
  • Visual Learning: "Create a diagram explaining the water cycle"

Example prompt:

"Explain blockchain technology: Level: Complete beginner, no tech background Include: - Simple analogy to start - How transactions work - Why it's secure - Real-world examples - Common misconceptions Use simple language, avoid jargon. Include a visual diagram."

Homework & Problem Solving

Work through problems:

  • Math Problems: "Solve this calculus problem and explain each step"
  • Science Questions: "Help me understand this physics concept and solve these problems"
  • Essay Help: "Help me structure an essay on the causes of World War I"
  • Code Debugging: "Explain why my code isn't working and help me fix it"

Example prompt:

"Help me understand this math problem: Problem: Find the derivative of f(x) = x³sin(x) I know basic derivatives but I'm confused about the product rule. Please: 1. Remind me of the product rule 2. Apply it step by step 3. Give me 2 similar problems to practice 4. Show me how to check my answer"

Study Materials

Prepare for success:

  • Study Guides: "Create a study guide for AP Chemistry exam"
  • Flashcards: "Generate 50 flashcards for Spanish vocabulary"
  • Practice Tests: "Create a practice quiz on US History 1900-1950"
  • Summary Notes: "Summarize Chapter 5 of my biology textbook"
  • Cheat Sheets: "Create a one-page reference for Python syntax"

Example prompt:

"Create a comprehensive study guide for the AWS Solutions Architect exam: Cover: - Key services and when to use them - Networking concepts - Security best practices - Cost optimization strategies Format: Clear sections, bullet points, diagrams where helpful Include: Practice questions after each section"

Coding & Tech Learning

Level up your skills:

  • Language Learning: "Teach me Python from zero to building a web app"
  • Code Review: "Review my code and explain how to improve it"
  • Project Tutorials: "Walk me through building a REST API step by step"
  • Concept Deep Dives: "Explain how Docker containers actually work"

Example prompt:

"Teach me React hooks: My level: I know basic JavaScript and HTML/CSS, never used React Structure: 1. What problem do hooks solve? 2. useState with simple examples 3. useEffect with practical use cases 4. When to use which hook 5. A mini-project putting it together Include code examples I can run."

Language Learning

Master new languages:

  • Grammar Explanations: "Explain Japanese particles with examples"
  • Conversation Practice: "Practice ordering food in French"
  • Writing Feedback: "Check my Spanish essay and explain my mistakes"
  • Vocabulary Building: "Teach me 20 essential business Chinese phrases"

Learning Styles

Tell CellCog how you learn best:

StyleAsk For
VisualDiagrams, charts, infographics
ExamplesMultiple worked examples, real-world applications
AnalogiesComparisons to familiar concepts
Step-by-StepDetailed breakdowns, numbered procedures
Big PictureOverview first, then details
Hands-OnPractice problems, projects

Subjects

CellCog can help with virtually any subject:

STEM:

  • Mathematics (all levels through advanced calculus and beyond)
  • Physics, Chemistry, Biology
  • Computer Science and Programming
  • Statistics and Data Science
  • Engineering concepts

Humanities:

  • History and Social Studies
  • Literature and Writing
  • Philosophy
  • Languages
  • Psychology

Professional:

  • Business and Finance
  • Marketing
  • Project Management
  • Design
  • Legal concepts

Tech Skills:

  • Programming languages
  • Cloud platforms (AWS, GCP, Azure)
  • DevOps and infrastructure
  • Data engineering
  • AI/ML concepts

Chat Mode for Learning

ScenarioRecommended Mode
Homework help, concept explanations, practice problems"agent"
Comprehensive study guides, full curriculum design, deep research"agent team"

Use "agent" for most learning. Quick explanations, homework help, and study materials execute well in agent mode.

Use "agent team" for comprehensive learning - full course outlines, research papers, or when you need multi-source synthesis.


Example Prompts

Concept explanation:

"Explain the concept of recursion in programming: My level: Beginner programmer, comfortable with loops I need: - Clear definition - Visual representation - 3 progressively harder examples (factorial, fibonacci, tree traversal) - Common mistakes to avoid - When to use recursion vs iteration Language: Python"

Exam prep:

"Create a study plan for the GRE: Timeline: 2 months Goal: 320+ score Weak areas: Vocabulary and geometry Include: - Weekly schedule - Resources to use - Practice test strategy - Day-before checklist Make it realistic for someone working full-time."

Language practice:

"Help me practice Japanese: Level: JLPT N4 Focus: Conversational situations Create a dialogue practice: - Scenario: Asking for directions in Tokyo - Include vocabulary list - Grammar points used - Cultural notes - Variations to practice Use romaji and kanji with hiragana readings."

Tips for Better Learning

  1. State your level: "Complete beginner" vs "I understand the basics" changes everything.
  1. Ask why: Don't just ask for answers. Ask for explanations of the reasoning.
  1. Request practice: Learning happens through doing. Ask for practice problems.
  1. Admit confusion: "I don't understand the part where..." helps CellCog target explanations.
  1. Build on previous: Reference what you already understand to get appropriate explanations.
  1. Active recall: Ask CellCog to quiz you, not just explain. Testing improves retention.

If CellCog is not installed

Run /cellcog-setup (or /cellcog:cellcog-setup depending on your tool) to install and authenticate. OpenClaw users: Run clawhub install cellcog instead. Manual setup: pip install -U cellcog and set CELLCOG_API_KEY. See the cellcog skill for SDK reference.

平台分布

OpenClaw

72.14%
按下载量换算27,664

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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