ai-content-quality-checker_skill

This skill evaluates AI generated content across readability, accuracy, relevance, originality, SEO, accessibility, engagement, and style to deliver actionable

HTML

1

GitHub Stars

1

Bundled Files

2 months ago

Catalog Refreshed

4 months ago

First Indexed

Readme & install

Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.

Installation

Preview and clipboard use veilstrat where the catalogue uses aiagentskills.

npx veilstrat add skill ntaksh42/agents --skill ai-content-quality-checker

SKILL.md14.3 KB

Overview

This skill evaluates AI-generated content across multiple quality dimensions and delivers a clear, prioritized improvement plan. It produces a 0–100 overall score and detailed sub-scores for readability, accuracy, relevance, originality, SEO, accessibility, engagement, grammar/style, and technical quality. The output is actionable and tailored to the target audience and content type.

How this skill works

The checker analyzes the submitted text or HTML and computes metrics like Flesch Reading Ease, sentence length distribution, passive voice usage, and syllable counts for readability. It verifies factual claims and citations, inspects SEO elements (titles, meta descriptions, keyword usage, schema), tests accessibility markers (semantic HTML, alt text, ARIA), scans for originality/duplication risk, and reviews code examples and links for technical correctness. Results include numeric scores, concise diagnostics, and prioritized recommendations with examples.

When to use it

Before publishing blog posts, documentation, or marketing copy generated by AI
When auditing multiple AI-generated drafts to choose the best version
To improve SEO and discoverability of AI-written articles
To ensure accessibility and compliance with basic WCAG guidelines
When validating technical examples, snippets, or linked resources

Best practices

Provide target audience, content type, and primary keywords with the submission
Include source links or data references to improve fact-check accuracy
Request specific focus areas (SEO, accessibility, originality) if needed
Prioritize high-impact fixes: accuracy, misleading claims, and accessibility
Iterate: re-run checks after applying recommended edits

Example use cases

Run a pre-publish audit of a technical tutorial to improve readability and fix inaccurate stats
Compare three AI-generated article drafts and get a ranked recommendation with reasons
Generate an SEO-focused report that suggests title, meta description, and keyword placement fixes
Audit an HTML article for WCAG 2.1 Level AA issues and receive concrete markup fixes
Check code examples for syntax, best practices, and security concerns before including them

FAQ

It flags unsupported claims and missing citations and highlights items that need manual verification; full automatic fact validation depends on provided sources and may require human review.

Does it check for plagiarism?

Yes — it reports similarity risk levels and suggests when to add citations or rewrite content to increase originality.