synthesis-content-quality

What problem does it solve?

Provides a repeatable, confidence-tiered methodology to detect, score, and remediate quality problems in AI-assisted writing so editors and creators can publish reliable, human-reviewed content.

Core Features & Use Cases

• 36-point evaluation: Comprehensive criteria across language, style, formatting, sourcing, confidentiality, and tone with high/medium/low confidence tags.
• Detection & Triage: Highlights hallucinated citations, chatbot artifacts, placeholders, scenario fingerprinting, and concierge tone to prioritize editorial fixes.
• Revision workflow: Stepwise guidance for eliminating formulaic patterns, verifying sources, adding expertise, and applying a Human Touch test; suitable for pre-publication review, training editors, and calibrating AI content generators.
• Reference-backed guidance: Includes a detailed reference document explaining each criterion and remediation examples for consistent reviewer training.

Quick Start

Review this draft and produce a prioritized checklist of high, medium, and low confidence indicators from the 36-point framework with concrete revision actions.