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synthesis-content-quality

Score AI-assisted content quality using a 36-point criteria framework.

15|2|Updated Mar 17, 2026
Search Tags:#anonymization#hallucination-detection#content-quality#writing-improvement#ai-content#editorial-review
One-click install
npx skills add https://github.com/rajivpant/synthesis-skills --skill synthesis-content-quality
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: synthesis-content-quality
Source: https://github.com/rajivpant/synthesis-skills/tree/main/synthesis-content-quality
Command: npx skills add https://github.com/rajivpant/synthesis-skills --skill synthesis-content-quality

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

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.

Frequently Asked Questions about synthesis-content-quality

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

FAQPage Schema
How do I detect AI hallucinations and chatbot artifacts in generated content?▼

AI hallucination detection identifies fabricated citations, chatbot artifacts, and placeholder text by applying a 36-point criteria framework to flag high, medium, and low confidence issues for editorial review.

What is the best way to audit AI content quality before publication?▼

Auditing AI content quality involves evaluating text against a 36-point framework to score language, formatting, sourcing, and tone, producing a prioritized checklist with actionable revision guidance for human editors.

How do I check AI-assisted writing for confidentiality exposures and tone problems?▼

Checking AI-assisted writing for confidentiality exposures applies scenario fingerprinting and criteria-based evaluation to identify sensitive data leaks and concierge tone, generating stepwise remediation guidance.

Can I use a 36-point framework to train editors on AI content refinement?▼

You can train editors on AI content refinement using a reference-backed 36-point framework that details each evaluation criterion and provides remediation examples to ensure consistent reviewer calibration.

Does editorial review of AI content require any specific dependencies?▼

Editorial review of AI content using this 36-point evaluation framework requires no external dependencies, allowing reviewers to directly analyze text and produce confidence-tiered revision checklists.

Why does AI-generated writing still need a human touch test?▼

AI-generated writing needs a human touch test because automated outputs often contain formulaic patterns and hallucinated citations that require stepwise human verification and expertise integration to ensure reliable publication.

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