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specsafe-qa

Validate AI-generated code against specifications and generate GO/NO-GO reports.

3|Updated Jan 27, 2026
Search Tags:#code quality#testing#tdd#validation#qa#specsafe
One-click install
npx skills add https://github.com/Agentic-Engineering-Agency/specsafe --skill specsafe-qa
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: specsafe-qa
Source: https://github.com/Agentic-Engineering-Agency/specsafe/tree/main/.opencode/skills/specsafe-qa
Command: npx skills add https://github.com/Agentic-Engineering-Agency/specsafe --skill specsafe-qa

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill automates the quality assurance process for AI-generated code, ensuring that implementations meet defined specifications and pass rigorous validation checks before deployment.

Core Features & Use Cases

  • Automated QA Execution: Runs predefined quality assurance tests against the implemented code.
  • Validation Reporting: Provides detailed reports on test results, coverage metrics, and a GO/NO-GO recommendation.
  • Use Case: After an AI has generated code to implement a new user authentication feature, this Skill can be used to automatically run all associated QA tests and confirm the code's readiness for the next stage.

Quick Start

Run the quality assurance checks for the spec with ID 'SPEC-20231027-001'.

Frequently Asked Questions about specsafe-qa

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

FAQPage Schema
How do I validate AI-generated code before deployment?▼

You can validate AI-generated code by running automated quality assurance checks against your defined specifications. This process executes validation tests, generates coverage reports, and provides a GO/NO-GO recommendation to prevent premature completion.

When do I need to run QA validation on my code implementation?▼

You need to run QA validation when all unit tests are passing and the implementation is ready for a final quality gate. This ensures the AI-generated code meets rigorous validation checks before moving to deployment.

What is included in a code quality validation report?▼

A code quality validation report includes detailed test results and coverage metrics for the implemented code. It also provides a final GO/NO-GO recommendation to confirm the implementation's readiness for the next stage.

How do I execute quality assurance checks using a spec ID?▼

To execute quality assurance checks, you provide the spec ID as input to the validation skill. It then runs the predefined QA tests against the implemented code and outputs the validation reports.

Can I get a deployment recommendation from automated code testing?▼

Yes, automated code testing provides a GO/NO-GO recommendation as part of its validation reporting. This enforces guardrails against premature completion and confirms whether the generated code is ready for deployment.

Does QA validation work if some unit tests are failing?▼

No, QA validation is applied only when all unit tests are passing. It acts as a final quality gate after successful test execution to ensure the implementation meets defined specifications before deployment.

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