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AnthonyPAlicea
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do-i-understand

Validate developer comprehension of AI-generated code changes through targeted questioning.

84|11|Updated Jun 8, 2026
Search Tags:#code review#pull request#ai#developer experience#software quality#accountability
One-click install
npx skills add https://github.com/AnthonyPAlicea/skills --skill do-i-understand
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: do-i-understand
Source: https://github.com/AnthonyPAlicea/skills/tree/main/skills/do-i-understand
Command: npx skills add https://github.com/AnthonyPAlicea/skills --skill do-i-understand

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill addresses the risk of developers merging AI-generated code they do not fully comprehend, ensuring they remain accountable for the software they ship.

Core Features & Use Cases

  • Reverse Code Review: Probes the developer's reasoning, assumptions, and understanding of consequences rather than just checking for syntax errors.
  • Risk-Based Triage: Focuses interrogation on high-stakes areas like authentication, security, migrations, and complex logic.
  • Accountability Attestation: Generates a structured report of the developer's understanding to be included in pull request descriptions or personal records.

Quick Start

Run the do-i-understand skill against the current pull request or branch to begin a guided interview about your changes.

Frequently Asked Questions about do-i-understand

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

FAQPage Schema
How do I ensure accountability for AI-generated code in pull requests?▼

Accountability for AI-generated code is ensured by validating developer comprehension of changes through targeted, non-adversarial questioning regarding logic, failure modes, and architectural assumptions.

What is reverse code review for software quality?▼

Reverse code review probes the developer's reasoning, assumptions, and understanding of consequences rather than just checking for syntax errors, focusing interrogation on high-stakes areas like authentication and migrations.

How do I validate my understanding of AI-generated commits and diffs?▼

Validate your understanding of AI-generated commits and diffs by running a guided interview against the changed lines, which anchors the interrogation to identify gaps in reasoning and produce an accountability report.

Can I use risk-based triage for AI-generated code changes?▼

Risk-based triage can be used for AI-generated code changes to focus interrogation on high-stakes areas like security, authentication, migrations, and complex logic, ensuring developers comprehend critical modifications.

Does accountability attestation work with pull request descriptions?▼

Accountability attestation generates a structured report of the developer's understanding that can be included directly in pull request descriptions or personal records to document comprehension of AI-generated code.

When should I not use automated code comprehension validation?▼

Automated code comprehension validation requires a concrete set of changed lines to anchor the interrogation, so it should not be used when no specific pull request, commit, or diff is available to review.

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