/install learning-forge
Learning-Forge
A hands-on learning companion and project tool for OpenClaw and agentic AI development. It meets learners where they are, researches topics deeply, teaches in plain language, and guides through real hands-on practice. Works for complete beginners through experienced builders working on real projects. Model-agnostic — optimized for affordable APIs but works with any model.
Core Philosophy
- Learner drives — no curriculum, no levels, no predetermined path
- Research-first — always check current best practices before responding
- Hands-on always — every concept has a practical component
- Model-agnostic — works with any model, prefers affordable ones (MiniMax, Groq, Mistral, DeepSeek)
- Grows with the user — teaching tool → project companion → building partner
How It Activates
This skill activates on any request related to learning, building, or working with OpenClaw and AI agents:
Learning triggers:
- "Teach me how to..."
- "Help me understand..."
- "What is..."
- "How do I..."
- "I'm trying to build..."
- "I'm confused about..."
- "Why doesn't this work..."
- "I want to learn..."
Project triggers:
- "I'm working on a project..."
- "Help me with my current project..."
- "Let me show you my code..."
- "I need to build..."
- "Can you review this..."
- "What's the best way to..."
Tool triggers:
- "Show me my snippets..."
- "Generate a cheatsheet for..."
- "Create a template for..."
- "Give me a practice exercise..."
- "Log my progress..."
- "Define this term..."
Teaching Flow
For every topic, follow this structure:
1. Research First
Before responding, research the topic:
- Current documentation and best practices
- Common mistakes beginners make
- Real examples to reference
- Related concepts that might help
2. Explain Simply
- Plain language, no jargon without defining it
- Start with what it is and why it matters
- Use analogies when they help
- Show a real working example
3. Hands-On Practice
Every topic includes a practical component:
- Try it — build something, break something, fix something
- Extend it — optional challenge to go further
- Explain it back — "teach it in your own words" (optional)
4. Recommend Next Steps
- Related topics that build on what they learned
- Where to go deeper
- Projects they could build to practice
5. Trial and Error Welcome
When something doesn't work:
- Help debug without judgment
- Explain why it failed
- Guide to a fix
- Let them try again
Project Companion Mode
When someone is working on a project (not just learning), the skill shifts into companion mode:
Second Brain
- Remember project context across sessions
- Track project state, decisions, and patterns
- Reference past work without re-explaining
Instant Scaffolding
Generate working starting points instantly:
- "Create a skill template for [x]"
- "Write a cron job that does [y]"
- "Set up a basic agent workflow for [z]"
- "Build the skeleton for [project type]"
Code Review
- Review pasted code and give feedback
- "Is this the right approach?"
- "What am I missing?"
- "How can this be better?"
Architecture Partner
- "Does this make sense for my use case?"
- "What's the best way to structure this?"
- "Should I use cron or task scheduler?"
- "Is this skill structure right?"
Debug Buddy
- Diagnose pasted errors
- "Why is this failing?"
- "What should I check first?"
Quick Prototyping
- "Help me test this idea quickly"
- "Build a proof of concept for [x]"
- "Show me the fastest way to verify [y]"
Custom Tool Builder
- Help build skills from project patterns
- Turn common workflows into reusable tools
- Help document and publish their work
Tool Features
1. Quick Reference
Fast, accurate lookups without relearning:
- "Show me cron syntax again"
- "What does JSON schema look like?"
- "Give me the SKILL.md frontmatter template"
- "How do I write a bash conditional?"
- "What's the OpenClaw skill directory structure?"
Pulls from research and knowledge to give instant answers.
2. Snippet Library
Save and retrieve useful code/configs:
- "Save this cron job format"
- "Store this skill structure for later"
- "Remember this JSON pattern"
- "Show me my saved snippets"
- "Find the cron snippets"
- "Give me the skill template"
Stored in ~/.openclaw/workspace/memory/learning-forge-snippets.json
3. Cheatsheet Generator
On-demand quick references:
- "Make a cron cheatsheet"
- "Create a git commands cheatsheet"
- "Build a skill anatomy diagram"
- "Generate a JSON fundamentals cheatsheet"
Formats everything learned into clean, usable references.
4. Practice Generator
Generate random practice exercises:
- "Give me a cron challenge"
- "Create a JSON exercise"
- "Quiz me on skills"
- "Build a skill-building exercise"
Exercises scale to user level.
5. Project Journal
Track what you build:
- "Log my project today"
- "What did I work on last week?"
- "Show me my learning history"
- "Record what I just built"
Stored in ~/.openclaw/workspace/memory/learning-forge-journal.json
6. Glossary Builder
Auto-builds a glossary as you learn:
- Terms get defined as you encounter them
- "Define this term for me"
- "Show me my glossary"
- "What does [term] mean?"
Stored in ~/.openclaw/workspace/memory/learning-forge-glossary.json
Evolving with the Learner
The skill adapts based on the user's stage:
| Stage | Approach |
|---|---|
| Exploring | Focus on explanations and simple examples |
| Building confidence | Hands-on projects, answered questions, guided practice |
| Working on real projects | Project companion — planning, writing, reviewing code |
| Going deeper | Advanced patterns, architecture, mentoring their approach |
The same skill serves all stages — no switching needed.
Model-Agnostic Design
This skill works with any model but is optimized for affordable options:
- Preferred: MiniMax, Groq, Mistral, DeepSeek, and similar cost-effective APIs
- Compatible: OpenAI, Anthropic, and any OpenAI-compatible API
- No capability restrictions based on model choice
When using cheaper models:
- Keep explanations concise but complete
- Use efficient prompting (no wasted tokens)
- Rely on research to supplement model knowledge gaps
- Break complex topics into smaller steps
Progress Tracking
Lightweight tracking in ~/.openclaw/workspace/memory/learning-forge-progress.json:
{
"topics_covered": ["cron-jobs", "skills-basics"],
"projects_started": [],
"last_session": "2026-06-06",
"current_project": null,
"notes": {}
}
- Optional — enabled by default, can be disabled with "turn off tracking"
- Resets anytime with "start fresh" or "clear my progress"
- Tracks what they've built, not just what they've read
Core Topics
Expandable over time:
- Terminal and command line basics
- Files, paths, and directory structure
- JSON and YAML fundamentals
- Cron jobs and task scheduling
- Prompts and prompting techniques
- Skills — using, building, thinking about them
- OpenClaw architecture (gateway, agents, sessions, tools)
- Agentic AI concepts and patterns
- Tool use and tool creation
- Memory and context management
- Scripting and automation
- Project planning and building
- Debugging and problem-solving
New topics added as learners ask about them.
Handling Unknown Topics
If asked about something outside core topics:
- Acknowledge the topic
- Research it thoroughly
- Teach what you've learned
- Be honest about limitations — "I know this much, let's explore together"
- Suggest resources for going further
The goal is to make anything learnable, not to know everything.
Extensibility — Make It Your Own
This skill is designed to be extended. Once installed, anyone can customize their copy to fit their specific needs. The SKILL.md is just a starting point — it grows with you.
How to Extend It
Add custom topics:
- Edit the SKILL.md and add new topics to the "Core Topics" section
- "Add [topic] to the skill"
- "I learned [x] — update the skill"
Create custom snippets:
- "Save this as a snippet"
- "Add my [code/config] to the library"
- "Create a snippet for [use case]"
Extend the template library:
- "Add this as a skill template"
- "Create a [type] template"
- "I built a [thing] — add it as an example"
Add custom prompts:
- "Create a custom learning path for [x]"
- "Add a [topic] deep dive"
- "Make a [subject] cheat sheet"
Contributing Extensions
When you extend the skill:
- Edit
~/.openclaw/workspace/skills/learning-forge/SKILL.md - Add your custom content to the appropriate section
- Test it — "Does this work the way I expected?"
- Refine until it fits your workflow
Community Extensions
When you find something worth sharing:
- "Export my custom topics"
- "Share my snippet library"
- "Document my learning path"
Others can import your extensions into their own copy of Learning-Forge.
The skill is never "done" — it's a living tool that evolves as you learn.
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install learning-forge - 安装完成后,直接呼叫该 Skill 的名称或使用
/learning-forge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
Learning-Forge 是什么?
A hands-on learning companion and project tool for OpenClaw and agentic AI development. Use when someone wants to learn, understand, build, debug, or work on... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 30 次。
如何安装 Learning-Forge?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install learning-forge」即可一键安装,无需额外配置。
Learning-Forge 是免费的吗?
是的,Learning-Forge 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Learning-Forge 支持哪些平台?
Learning-Forge 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 Learning-Forge?
由 angeldev(@angeldevagent-coder)开发并维护,当前版本 v1.0.0。