資料月份 2026-09
Multiscal AI Audit
Multiscal AI Audit
Multiscal AI Audit
The Eye into AI Readiness. We help you see how AI perceives your digital presence. 100% local analysis.

據 AlphaMoat 統計,截至 2026-09,Chrome 外掛 Multiscal AI Audit 使用者數為 12,環比 +0%,在全部 9,324 款 AI 瀏覽器外掛中排名第 8,750 位,在「程式設計開發」分類(601 款)中排名第 562 位。

使用者數 · 2026-09
12+0%
評分
-
全站排名(9,324 個)
#8,750
「程式設計開發」排名
#562/ 601

Multiscal AI Audit 是什麼

Chrome 商店介紹

The Eye into AI Readiness. We help you see how AI perceives your digital presence. 100% local analysis. What it does Multiscal AI Audit checks whether your website is ready for AI search engines, answer engines, and LLM-based discovery. It runs 27 checks on any webpage, covering structured data, crawlability, content quality, semantic markup, and more.

You get a weighted score from 0-100, a breakdown by pillar, and specific fix instructions for each issue found.

27 metrics, organized by category Discovery & Access — Indexability, AI Crawler Permission, LLM Discovery, Hreflang Validation Technical Foundation — Performance, Accessibility, Security & Headers, Mobile Optimization Content Structure — Structured Data, Internal Linking, Boilerplate Detection Content Quality — Citation-Worthiness, Answerability, Content Depth, Fact Density, Source Authority, Cross-Reference Quality Semantic Understanding — Semantic Richness, Entity & Brand, E-E-A-T Freshness — Freshness, Temporal Signals AI Optimization — Snippet Optimization, AEO Optimization, Conversational Query, RAG-Friendly Media — Multimodal

Features Single-page audit from the popup or side panel Site-wide crawl (up to 50 pages) from the dashboard Weighted scoring with 4-tier grading: Excellent, Good, Fair, Needs Work Top 3 Fixes card showing which changes give the biggest score lift Score improvement simulator with real-time previews Copy any fix suggestion to clipboard with one click History tracking with comparison against previous audits Export results as JSON, CSV, or printable PDF report Accessibility labels and keyboard navigation throughout How scoring works Each of the 27 pillars has a different weight based on its impact on AI discoverability. Answerability and Citation-Worthiness carry the most weight. LLM Discovery and RAG-Friendly carry the least. The overall score is a weighted average.

The simulator lets you toggle improvements (add FAQ schema, convert headings to questions, add author byline, etc.) and see exactly how each change would affect your score before you make it.

Privacy Everything runs locally in your browser. No external API calls. No data collection. No accounts. The extension only needs activeTab and storage permissions.

展開其餘商店介紹▾

Who this is for SEO specialists checking AI readiness. Content teams optimizing for featured snippets and answer engines. Developers auditing structured data and crawler access. Anyone who wants to know how AI systems read their website.

外掛檔案

版本
v1.8.0
安裝包體積
204KiB
支援語言
English
更新於
2026-03-13

使用者增長趨勢

同一座標 · 懸停檢視月度數值
最新 12環比+0.0%
-4.38.61326-0426-0526-08
2026-04
12
—
2026-05
12
+0.0%
2026-06
11
-8.3%
2026-08
12
+9.1%
2026-09
12
+0.0%

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資料月份:2026-09 · 使用者數與評分來自 Chrome 應用商店公開資料,按月聚合更新。口徑說明見資料方法。