qa

Assess artifact quality against a predefined standard and return a structured verdict.

5.4k|535|Updated Jan 14, 2026
One-click install
npx skills add https://github.com/Q00/ouroboros --skill qa-q00
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: qa
Source: https://github.com/Q00/ouroboros/tree/main/skills/qa
Command: npx skills add https://github.com/Q00/ouroboros --skill qa-q00

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Quickly assesses artifacts against a predefined quality bar and returns a structured verdict with actionable next steps.

Core Features & Use Cases

  • Determine artifact quality across code, docs, tests, and API responses with a single pass.
  • Provide PASS/REVISE/FAIL verdicts and recommended loop actions to guide iterative improvement.
  • Use MCP mode when available or fall back to a deterministic internal judge for environments without MCP.

Quick Start

Run ooo qa [file_path | artifact_text] to evaluate your latest output and receive a structured verdict.

Frequently Asked Questions about qa

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

FAQPage Schema
How do I evaluate code quality against a predefined standard?▼

You can evaluate document quality by running the assessment tool with your file path or artifact text. It checks the artifact against a predefined quality bar and returns a structured verdict with actionable next steps to guide iterative improvement.

Can I automate API response evaluation without an MCP environment?▼

You can automate API response evaluation in environments without MCP by using the fallback deterministic internal judge. It requires a defined quality bar, clear artifact specification, and optional seed or reference data to drive deterministic results.

What is the best way to get actionable verdicts for test outputs?▼

The best way to get actionable verdicts for test outputs is to run a single-pass quality assessment against a predefined standard. This process returns a structured verdict and recommended loop actions to guide iterative improvement.

Does the quality evaluation tool support iterative improvement workflows?▼

The quality evaluation tool supports iterative improvement workflows by providing recommended loop actions alongside its structured verdicts. It determines artifact quality across code, docs, tests, and API responses in a single pass to guide your next steps.

Do I need reference data to evaluate artifact quality deterministically?▼

You do not always need reference data to evaluate artifact quality, but providing optional seed or reference data helps drive deterministic results. A defined quality bar and clear artifact specification are required to perform the assessment.