LLM Infrastructure & Evals FAQs

Question 1

What kind of observability does it provide?

Accepted Answer

The skill provides patterns for wrapping LLM calls with tracing tools like Langfuse or Phoenix, enabling you to capture token usage, costs, and errors in production.

Question 2

Can it help with LLM security?

Accepted Answer

Yes, it includes specialized audits for security, specifically scanning for prompt injection vulnerabilities and implementing red team test cases in the eval suite.

Question 3

How does it improve prompt engineering?

Accepted Answer

It identifies anti-patterns like over-prescriptive 'step-by-step' instructions and helps rewrite them into the 'Role + Objective + Latitude' pattern, which allows modern LLMs to use their reasoning capabilities more effectively.

Question 4

Does this skill support automated testing?

Accepted Answer

Yes, it integrates with Promptfoo to create evaluation suites, including happy path tests, edge cases, and security red teaming, which can be gated in your CI/CD pipeline.

Question 5

Why does this skill require a web search for models?

Accepted Answer

LLM model benchmarks and availability change rapidly. This skill enforces real-time research to ensure you aren't using deprecated models or outdated documentation that could lead to poor performance.

LLM Infrastructure & Evals

主要功能

使用场景

LLM Infrastructure & Evals

主要功能

使用场景