self-learning
Autonomously research new technologies from the web and generate reusable agent skills.
Works with
What it does
Discovers authoritative documentation via web search, prioritizing official docs, GitHub repositories, and blogs
Extracts installation, core concepts, API references, and code examples from 3–5 high-quality sources
Generates a self-contained skill with YAML frontmatter, markdown instructions, and optional bundled resources (scripts, references, assets)
Saves skills to workspace-specific or glob
Installation Guide
How to use self-learning on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your machine
- ›Node.js 16+ with npm — verify with
node --version - ›Active project directory where you want to add
self-learning
Run the install command
Execute the skills CLI command in your project's root directory to begin installation:
Fetches self-learning from philschmid/self-learning-skill and configures it for Cursor.
Select Cursor when prompted
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate self-learning. Access via /self-learning in your agent's command palette.
Security Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Documentation
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale