Truesight Evaluation Creator FAQs

Question 1

What does this skill do for AI testing?

Accepted Answer

It provides a step-by-step workflow to define what 'quality' means for your specific AI task, turns that into a technical evaluation, and deploys a live API endpoint to score your AI's outputs automatically.

Question 2

How does the 'Seed Labeling' process work?

Accepted Answer

You label a small sample of 2-10 examples to teach the system your specific preferences. The skill then uses those examples to auto-label the rest of your dataset, ensuring the judge reflects your standards.

Question 3

Can I use this for non-binary scores?

Accepted Answer

Yes. While it defaults to binary pass/fail for clarity, it supports categorical labels (e.g., 'Professional' vs 'Casual') and continuous numeric scoring (e.g., 1-10).

Question 4

Do I need existing data to create an evaluation?

Accepted Answer

While real production traces are preferred, the skill can automatically generate synthetic data to bootstrap your evaluation if you have fewer than 20 examples.

Question 5

What is the companion skill generated at the end?

Accepted Answer

It is a custom-coded skill file for Claude that explains exactly how to call your new evaluations, making it easy to integrate the quality checks directly into your development loop.

Truesight Evaluation Creator

主要功能

使用场景

Truesight Evaluation Creator

主要功能

使用场景