aiconfig-variations

Manage AI Config variations across models, prompts, and parameters via API.

Updated Feb 4, 2026
One-click install
npx skills add https://github.com/launchdarkly-labs/aiconfigs-skills --skill aiconfig-variations
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: aiconfig-variations
Source: https://github.com/launchdarkly-labs/aiconfigs-skills/tree/main/aiconfig-variations
Command: npx skills add https://github.com/launchdarkly-labs/aiconfigs-skills --skill aiconfig-variations

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill enables teams to manage AI Config variations across models, prompts, parameters, and tools within a single AI Config to enable comprehensive experimentation.

Core Features & Use Cases

  • Add, update, retrieve, and delete variations within an AI Config to test different setups.
  • Attach different tools and evaluation settings to each variation for targeted experimentation.
  • Run A/B-style comparisons of model responses, prompts, and parameters without changing the base config.

Quick Start

Use the variations skill to add an agent-mode and a completion-mode variation to an existing AI Config. The Quick Start provides sample Python snippets and API calls to illustrate how to create and manage variations.

Frequently Asked Questions about aiconfig-variations

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

FAQPage Schema
How do I test multiple AI models and prompts without changing my base configuration?

AI Config variations let you create and manage multiple model, prompt, and parameter combinations within a single config. Add variations to test different setups—such as agent-mode versus completion-mode—run A/B comparisons, and evaluate responses without modifying your original configuration.

Can I attach different tools and evaluation settings to each variation?

Yes. Each variation supports optional tool attachments and evaluation settings, enabling you to test targeted configurations. This allows comprehensive experimentation across models, prompts, parameters, and tools simultaneously within the same AI Config.

What's the best way to manage AI Config variations via API?

The variations API supports add, update, retrieve, and delete operations on variations within an AI Config. Use these endpoints to programmatically create test configurations, compare model responses, and manage parameter experiments without manual config edits.

Do I need to modify my existing AI Config to run model comparisons?

No. Variations enable A/B-style comparisons of models, prompts, and parameters as separate entries within your existing config. You preserve your base setup while testing different combinations for effective experimentation.

When should I use variations instead of creating separate AI Configs?

Use variations to test multiple setups within a single config for faster iteration and easier comparison. This approach keeps related experiments organized, supports batch evaluation, and simplifies rollback compared to managing separate configs for each test.