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angeldevagent-coder

Learning-Forge

by angeldev · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install learning-forge
Description
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...
README (SKILL.md)

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:

  1. Acknowledge the topic
  2. Research it thoroughly
  3. Teach what you've learned
  4. Be honest about limitations — "I know this much, let's explore together"
  5. 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:

  1. Edit ~/.openclaw/workspace/skills/learning-forge/SKILL.md
  2. Add your custom content to the appropriate section
  3. Test it — "Does this work the way I expected?"
  4. 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.

Usage Guidance
Install only if you want a learning assistant that may keep local project and learning notes across sessions. Avoid saving secrets, API keys, private credentials, or sensitive proprietary code in snippets, journals, or glossary entries, and use the documented reset or tracking-off commands if you do not want ongoing progress memory.
Capability Assessment
Purpose & Capability
The described capabilities, including teaching, research, scaffolding, debugging help, snippets, journaling, and glossary building, fit the stated purpose of an OpenClaw and agentic AI learning companion.
Instruction Scope
Activation language is broad and includes generic learning and project prompts, but it is framed around OpenClaw, AI agents, scripting, tools, and AI development rather than unrelated takeover behavior.
Install Mechanism
The package contains only a SKILL.md file, declares python3 as a requirement, has no executable scripts or dependencies, and static scan metadata reports no suspicious patterns.
Credentials
The skill asks the agent to research current practices and may help write or review code, which is proportionate for an educational development assistant and does not include hidden credential access, destructive commands, or external data exfiltration.
Persistence & Privilege
The skill discloses local storage paths for snippets, journal, glossary, and progress tracking under ~/.openclaw/workspace/memory, but progress is enabled by default and some memory features could retain sensitive project details if the user saves or logs them.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install learning-forge
  3. After installation, invoke the skill by name or use /learning-forge
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release: hands-on learning companion and project tool for OpenClaw and agentic AI development
Metadata
Slug learning-forge
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Learning-Forge?

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... It is an AI Agent Skill for Claude Code / OpenClaw, with 30 downloads so far.

How do I install Learning-Forge?

Run "/install learning-forge" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Learning-Forge free?

Yes, Learning-Forge is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Learning-Forge support?

Learning-Forge is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Learning-Forge?

It is built and maintained by angeldev (@angeldevagent-coder); the current version is v1.0.0.

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