Model Recommendation
Suggests optimal open-source machine learning models from GitHub based on project requirements and data characteristics.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add model-recommendation npx -- -y @trustedskills/model-recommendation
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"model-recommendation": {
"command": "npx",
"args": [
"-y",
"@trustedskills/model-recommendation"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
The model-recommendation skill helps users discover and install AI agent skills from a registry, streamlining the process of finding relevant tools for specific tasks. It provides curated recommendations based on user needs or context.
When to use it
- You need to find an AI agent skill that fits a particular task or workflow.
- You're looking for new capabilities to enhance your AI agent's functionality.
- You want to explore available skills before installing them manually.
Key capabilities
- Search and filter skills by category, author, or use case.
- View detailed information about each skill, including install count and description.
- Install recommended skills directly through the registry interface.
Example prompts
- "Find a skill for code generation."
- "Show me AI agent skills related to data analysis."
- "Recommend tools for improving natural language understanding in my AI agent."
Tips & gotchas
- Ensure you review the description and install count before installing a recommended skill.
- Some skills may require additional setup or dependencies after installation.
Tags
TrustedSkills Verification
Unlike other registries that point to live repositories, TrustedSkills pins every skill to a verified commit hash. This protects you from malicious updates — what you install today is exactly what was reviewed and verified.
Security Audits
| Gen Agent Trust Hub | Pass |
| Socket | Pass |
| Snyk | Pass |
🏢 Official
Published by the company or team that built the technology.