modelslab-model-discovery

Name: modelslab-model-discovery
Availability: InStock
Author: ModelsLab

Search, filter, and compare ModelsLab models with bearer authentication.

10|1|Updated Feb 4, 2026

Search Tags:#api #models #search #filters #usage-analytics #modelslab

Ready to run

npx skills add https://github.com/ModelsLab/skills --skill modelslab-model-discovery

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: modelslab-model-discovery
Source: https://github.com/ModelsLab/skills/tree/main/model-discovery
Command: npx skills add https://github.com/ModelsLab/skills --skill modelslab-model-discovery

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Locate and evaluate AI models hosted on ModelsLab by enabling fast search, filtering, and comparison to inform decision-making.

Core Features & Use Cases

Search for models by name, feature, provider, or tags to identify best-fit options.
View model details, capabilities, pricing, and usage analytics to guide decisions.
Use filters and browse generation history to understand model evolution across tasks.

Quick Start

Authenticate with a bearer token and perform your first model search using a sample query.

Frequently Asked Questions about modelslab-model-discovery

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I search and filter AI models by capabilities and pricing?▼

To search and filter AI models, you can query the ModelsLab library by name, feature, provider, or tags. This allows you to compare capabilities and pricing across image, video, audio, and text domains to find the best fit.

What is the best way to compare AI models across different domains?▼

Comparing AI models across domains is done by retrieving model details and capabilities through structured search endpoints. You can evaluate options across image, video, audio, and text tasks to inform your selection decision.

Can I track API usage history for specific AI models?▼

Yes, you can track API usage history for specific AI models. The system exposes endpoints that return usage analytics, allowing you to browse generation history and understand model evolution across various tasks.

Do I need a bearer token to access model search endpoints?▼

Yes, you need a bearer token for authentication to access model search endpoints. The system enforces bearer authentication to securely retrieve structured model data, filters, and usage history.

How do I integrate structured AI model data into my application?▼

You integrate structured AI model data by calling the available search, details, and filter endpoints. The API returns structured data directly from the ModelsLab library, ensuring easy integration into your application workflow.