ai-factory.verify

Name: ai-factory.verify
Availability: InStock
Author: yaroslavkomarov

Compare planned tasks against implemented code and generate a verification report.

Updated Apr 6, 2026

Search Tags:#quality #diff #plan #verify #compile #tests

Ready to run

npx skills add https://github.com/YaroslavKomarov/ShedulerBot --skill ai-factory-verify-yaroslavkomarov

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: ai-factory.verify
Source: https://github.com/YaroslavKomarov/ShedulerBot/tree/main/.claude/skills/verify
Command: npx skills add https://github.com/YaroslavKomarov/ShedulerBot --skill ai-factory-verify-yaroslavkomarov

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill ensures that implemented work aligns with the plan, checks that all tasks are completed, code compiles, and tests pass, delivering a reliable release.

Core Features & Use Cases

Load and interpret the plan, enumerate tasks, and compare with the actual code changes.
Check that the code compiles and test suites pass.
Generate a structured verification report detailing completeness gaps and remediation recommendations.

Quick Start

Run /ai-factory.verify after implementing all tasks to confirm completeness and quality.

Frequently Asked Questions about ai-factory.verify

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

FAQPage Schema

How do I verify code changes match the original implementation plan?▼

To verify code changes against a plan, compare implemented features with the planned tasks to identify completeness gaps. This process checks task adherence, confirms code compiles, and ensures test suites pass to guarantee release readiness.

What is post-implementation quality verification in software engineering?▼

Post-implementation quality verification is the process of validating that completed code changes align with the planned tasks. It confirms task completeness, successful compilation, and passing tests to ensure the build is ready for release.

Can I check task completeness and test success across multiple builds?▼

Yes, you can apply post-implementation reviews across software features, builds, and tests. The verification process enumerates planned tasks, validates completion, checks compilation, and runs test suites to confirm overall quality gates.

What is the best way to identify gaps between planned tasks and implemented code?▼

The best way to identify plan adherence gaps is to generate a structured verification report. This report details incomplete tasks, flags compilation or test failures, and provides remediation recommendations to achieve full release readiness.

Why does my post-implementation review fail to catch release readiness issues?▼

A post-implementation review might fail if it does not explicitly validate task completeness, compile success, and test execution against the original plan. Without checking these specific quality gates, unresolved gaps and failing tests can slip through.