What is 'spec drift' and why does it matter?

Spec drift happens when the code and the documentation diverge. This skill catches instances where the spec was updated but the code wasn't (or vice-versa), ensuring your project remains maintainable.

Does this work with my existing testing framework?

Yes, it is framework-agnostic and can be configured to run npm test, pytest, go test, or any other command-line testing utility.

Can I skip the verification gate if I'm in a hurry?

The skill is designed to enforce discipline. While you can manually override, its primary purpose is to prevent the common pitfall of claiming a task is 'done' when it is only partially implemented.

How does this differ from standard test running?

While standard verification only checks if tests pass, this skill explicitly compares your code against your feature specifications to ensure every requirement was actually implemented as designed.

Spec-Aware Verification Gate

Name: Spec-Aware Verification Gate
Author: rhuss

byrhuss

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Seguridad y Pruebas

Enforces rigorous quality standards by validating implementation against both test suites and functional specifications before project completion.

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The Verification Before Completion skill is a critical component of Specification-Driven Development (SDD) that transforms Claude into a disciplined quality gatekeeper. It goes beyond simple test execution by explicitly mapping code output back to original project specifications, identifying 'spec drift,' and ensuring every functional requirement and success criterion has been met. By blocking completion on failures and generating structured verification reports, it prevents incomplete features or untested edge cases from reaching production.

Características Principales

Detection of 'spec drift' between current code and design documents
Detailed Go/No-Go reporting with prioritized blocking issues
Automated execution and analysis of multi-language test suites
Strict quality gates that prevent task completion until 100% compliance is met
1 GitHub stars
Line-by-line requirement validation against markdown specifications

Casos de Uso

Auditing code changes for compliance before committing to high-stakes repositories
Maintaining synchronization between project documentation and actual implementation
Ensuring AI-generated features perfectly match complex business logic requirements

Acerca de

Características Principales

Detection of 'spec drift' between current code and design documents
Detailed Go/No-Go reporting with prioritized blocking issues
Automated execution and analysis of multi-language test suites
Strict quality gates that prevent task completion until 100% compliance is met
1 GitHub stars
Line-by-line requirement validation against markdown specifications

Casos de Uso

Auditing code changes for compliance before committing to high-stakes repositories
Maintaining synchronization between project documentation and actual implementation
Ensuring AI-generated features perfectly match complex business logic requirements