feat: GEO/SEO structured data + search ranking tracker

scripts/compliance_optimizer.py

@@ -169,25 +169,28 @@ def polish_with_llm(html: str, platform: str, remaining_issues: Optional[List[Di
     """
     if not HAVE_LLM:
         return html, None
+    prompt_key = "compliance_fix" if remaining_issues else "compliance_polish"
     for attempt in range(2):
         try:
             temperature = 0.5
-            max_tokens = 4000
+            params = get_prompt_params(prompt_key)
+            max_tokens = params.get("max_tokens", 8000)
             system_prompt = "你是一个专业的内容合规与优化助手，擅长在保持文章质量和可读性的前提下修复合规问题。"
             if remaining_issues:
                 issues_desc = "\n".join(
                     f"- [{i['type']}] {i.get('category','')}: {i.get('detail','')}"
                     for i in remaining_issues
                 )
-                prompt = get_prompt("compliance_fix", issues_desc=issues_desc, html=html)
+                prompt = get_prompt(prompt_key, issues_desc=issues_desc, html=html)
             else:
-                prompt = get_prompt("compliance_polish", html=html)
+                prompt = get_prompt(prompt_key, html=html)
             polished = call_llm(prompt, temperature=temperature, max_tokens=max_tokens, system_prompt=system_prompt)
             polished = clean_html_content(polished)
             polished = strip_ai_preface(polished)
             polished = strip_thinking_html(polished)
             if '<h2' in polished or '<p>' in polished:
-                if len(polished) > len(html) * 0.3 and len(polished) > 100:
+                min_acceptable = min(len(html) * 0.3, 12000)
+                if len(polished) > min_acceptable and len(polished) > 100:
                     tag = "针对性修复" if remaining_issues else "常规润色"
                     return polished, f"LLM {tag}"
                 logger.warning(f"LLM 优化输出过短，保留原文 (len={len(polished)})")