апд

[AndreiDrang]

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[github-actions]

Z.ai Code Review

## 🔍 Review Summary
This Pull Request significantly enhances the site's SEO through expanded FAQ schemas, structured dataset/article markup, and explicitly configured robots.txt rules for AI crawlers. The changes are generally well-structured, but contain a missing step in the FAQ instructions and a potential runtime error in the Alpine.js component that should be addressed before merging.

## 🚨 Critical Issues & Bugs

• faq/index.html: The text for the step-by-step investment guide is missing a step, resulting in a broken and confusing sentence: "...и выберите удобный способ: В разделе «Инвестировать» или «Токены» выберите актив...". It abruptly jumps from selecting a payment method to selecting an asset without explaining the actual payment action.
• index.html: The Alpine.js expression x-text="stats.usdRate.toFixed(4)" is vulnerable to a TypeError. When the actual API endpoint is eventually connected, if the JSON response is missing the usdRate property, the spread operator (this.stats = { ...this.stats, ...d }) will overwrite the default, causing .toFixed(4) to throw an error and crash the component.
  • Fix: Use optional chaining or fallback values to ensure robustness.

    <div ... x-text="Number(stats.usdRate || 0).toFixed(4)">2.9060</div>

## 💡 Suggestions & Best Practices

• index.html: Hardcoded future dates (e.g., 2026-06-24) in both the JSON-LD schema and the UI markup will quickly become outdated and could negatively impact SEO rankings if search engines perceive the data as stale. If this is a statically generated site, consider automating the injection of these dates during your CI/CD build step.
• index.html: In the marketStats() Alpine component, the catch (e) block silently swallows API errors. It is a best practice to at least log these errors to the console to aid future debugging without affecting the user experience:

  } catch (e) {
    console.warn("Failed to load market stats:", e);
  }

• public/robots.txt: Explicitly declaring rules for specific AI search crawlers (ChatGPT, Claude, Perplexity) before a generic fallback is an excellent approach for modern LLM visibility. No changes needed here, but it is worth commending.

## 📊 Final Assessment

• Rating: Good
• Reason: The PR introduces high-value SEO and structural improvements with clear, well-organized code. The deducted points are only for a minor textual typo and a small missing null-check in the frontend JavaScript logic, which are both very quick to fix.