Confidence Check FAQs

Question 1

When should I use this skill?

Accepted Answer

You should use this skill at the very beginning of every implementation task. By running a Confidence Check first, you ensure that the proposed solution is necessary, follows your existing tech stack, and has a clear path to success.

Question 2

Does this skill provide a return on investment (ROI)?

Accepted Answer

Yes. While a check costs roughly 100-200 tokens, it can save between 5,000 and 50,000 tokens by preventing the AI from performing large-scale, incorrect work. It boasts a 100% precision and recall rate in production testing.

Question 3

What are the five criteria used for the confidence score?

Accepted Answer

The skill evaluates five areas: 1) Searching for existing duplicate implementations (25%), 2) Verifying tech stack and architecture compliance (25%), 3) Reviewing official documentation (20%), 4) Referencing proven Open Source implementations (15%), and 5) Confirming the root cause of the issue is identified (15%).

Question 4

How does this skill improve my AI coding workflow?

Accepted Answer

It acts as a quality gate that prevents 'wrong-direction' execution. By requiring a 90% confidence score to proceed, it minimizes architectural drift and significantly reduces wasted tokens spent on incorrect or redundant implementations.

Question 5

What does the Confidence Check skill do?

Accepted Answer

Confidence Check is a pre-implementation diagnostic tool that assesses the readiness of a coding task. It uses a 5-point scoring system to evaluate duplicate code risks, architectural alignment, documentation status, and root cause identification before any code is actually written.

Confidence Check

Confidence Check

Key Features

Use Cases

Key Features

Use Cases