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model-alternatives

Analyze codebases for paid AI API calls and recommend open-source model replacements.

Updated Feb 17, 2026
Search Tags:#code analysis#open source#ai#llm#cost optimization#model evaluation
One-click install
npx skills add https://github.com/janewilkin/bismuth-digital-llc-web --skill model-alternatives-janewilkin
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: model-alternatives
Source: https://github.com/janewilkin/bismuth-digital-llc-web/tree/main/.claude/skills/model-alternatives
Command: npx skills add https://github.com/janewilkin/bismuth-digital-llc-web --skill model-alternatives-janewilkin

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires anthropic, openai, ollama, groq, httpx, tabulate, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill helps you reduce your reliance on expensive paid AI APIs by identifying them in your codebase and recommending free, open-source alternatives. It also generates an evaluation suite to ensure the quality of the replacements.

Core Features & Use Cases

  • API Call Discovery: Scans your codebase to find all instances of paid AI API usage (e.g., OpenAI, Anthropic).
  • OSS Model Recommendation: Suggests suitable free, open-source models based on the task type (e.g., code generation, summarization, classification).
  • Eval Suite Generation: Creates a runnable Python script to benchmark free models against your paid API calls using your actual prompts.
  • Risk/Reward Analysis: Provides a clear assessment of the potential savings, quality impact, and migration effort for each replacement.
  • Use Case: A startup is spending $500/month on OpenAI API calls for text summarization. This Skill identifies these calls, recommends a self-hosted Llama 3.3 model, generates an evaluation script to confirm quality, and provides a migration plan, potentially saving the company thousands per year.

Quick Start

Run the model-alternatives skill to analyze the current project for paid AI API calls and suggest free replacements.

Frequently Asked Questions about model-alternatives

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

FAQPage Schema
How do I find and replace paid AI API calls in my Python codebase?▼

To find and replace paid AI API calls in a Python codebase, this Skill scans your project to identify paid API usage and recommends free, open-source model replacements. It generates a runnable Python evaluation script to benchmark the free models against your actual prompts.

Can I benchmark open source models against OpenAI and Anthropic prompts?▼

Yes, you can benchmark open source models against OpenAI and Anthropic prompts. The Skill generates an evaluation suite that compares the performance of free models against your paid API calls using your actual project prompts.

What is the best way to evaluate LLM cost optimization for code analysis tasks?▼

The best way to evaluate LLM cost optimization for code analysis is using the Skill's generated evaluation suite to benchmark free open-source models against paid ones. It provides an aggressive risk and reward assessment for cost savings, quality impact, and migration effort.

Does this model evaluation tool support Groq and Ollama for self-hosting?▼

Yes, this model evaluation tool supports Groq and Ollama for self-hosting replacements. It analyzes your codebase dependencies on OpenAI and Anthropic to suggest suitable free open-source models hosted through these supported platforms.

How do I generate a migration strategy for switching to free open source models?▼

To generate a migration strategy for switching to free open source models, run the Skill to analyze your codebase. It provides a clear assessment of potential savings, quality impact, and the required migration effort for each replacement.

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