Fact-Checking & Self-Assessment FAQs

Question 1

How does it determine if code is 'production-ready'?

Accepted Answer

The skill validates code against requirement specifications, tests for file accessibility, checks for proper error handling, and evaluates the overall architecture. It generates a confidence score where 90% or higher indicates the code is ready for production use.

Question 2

What does the Fact-Checking & Self-Assessment skill do?

Accepted Answer

This skill provides automated validation for AI outputs. It extracts factual claims for multi-source verification, generates quantitative quality scores for code, and assesses whether a solution meets production-grade standards before delivery.

Question 3

How does this skill improve AI-assisted coding?

Accepted Answer

It adds a critical layer of automated oversight, reducing hallucinations and logic errors. By providing objective metrics for accuracy and functionality, it helps developers catch gaps in implementations that might otherwise be overlooked during manual review.

Question 4

What specific capabilities does the self-assessment framework provide?

Accepted Answer

The framework offers quantitative scoring (0-100) across four key pillars: accuracy, completeness, functionality, and reliability. It also identifies unverified information and provides actionable recommendations to improve the output's quality score.

Question 5

When should I use this skill in my development workflow?

Accepted Answer

Use this skill when implementing new features, performing technical research, or conducting final quality assurance. It is particularly useful for verifying technical claims, checking requirements coverage, and ensuring code syntax and structure are production-ready.

Fact-Checking & Self-Assessment

Fact-Checking & Self-Assessment

概要

主な機能

ユースケース

概要

主な機能

ユースケース