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Documentation Index

Fetch the complete documentation index at: https://docs.zued.ai/llms.txt

Use this file to discover all available pages before exploring further.

After each audit — initial or weekly snapshot — zued generates recommendations automatically. They are specific to each URL, chunk, and prompt: not generic advice, but concrete changes tied to the exact analysis that produced them.

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Four types of output

Alignment Gaps

Per prompt and per content chunk: what AI engines say versus what your page actually contains. Includes missing topics, format mismatches, and accuracy issues.

Technical Issues

Per URL: bot blocking, JavaScript rendering failures, Core Web Vitals problems, missing structured data.

Cross-URL Insights

For prompts spanning multiple pages: how your URLs work as an ensemble, internal linking gaps, and unified recommendations. See Cross-URL Analysis.

Quick Wins

A ranked list of the highest-impact, lowest-effort changes across your entire project — sorted by priority score.

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Priority score

Every recommendation has a priority score from 0 to 100. The score is calculated from impact, effort, and how many AI engines are affected. See Prioritization for the full formula. Recommendations are grouped into four categories:
CategoryScoreWhen to act
Quick Win80–100This week
Strategic Investment50–79Next sprint
Medium Priority30–49After quick wins
Low Priority0–29Deprioritize
Technical issues that block AI crawlers are always scored at Priority 100 — fix these before any content changes.

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How recommendations are grounded

Every page’s recommendations are built on top of a set of observations about that page — what concepts it already covers, how consistently it names its primary entity, which explanatory questions it answers, and which AI engines mention topics it does not. Recommendations are required to cite these observations as evidence, which keeps them specific to the page and hard to confuse with generic advice. Content gaps are prioritized by the strength of the signal behind them. Topics that many AI engines discuss receive the highest priority. Topics another page of your site already covers are surfaced as linking or consolidation opportunities, not as rewrites. Topics a single engine mentions are flagged but ranked lower. Each new-section recommendation also includes example phrasing grounded in your own entity list, so you have concrete starting sentences rather than an abstract topic brief.

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Tracking progress

When you implement a recommendation and the next snapshot runs, zued compares the new scores against the previous snapshot. Resolved quick wins are tracked automatically — you can see which changes produced measurable improvements.