Google 2026 Checker - SagaSu
Description
Based on Google's latest 2026 standards (E-E-A-T, March 2026 Core Update), it performs comprehensive quality checks on SEO articles, generates structured scoring reports, and provides step-by-step optimization guidance and direct rewriting. Suitable for pre-publishing checks and post-publishing audits, usable by beginners and experts alike.
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SEO+GEO Visibility Engine
Optimize the search performance and AI citation readiness of your articles, product pages, and landing pages. Quickly identify the issues most worth fixing, or get ready-to-use titles, rewrites, content briefs, technical fix lists, or performance retest plans. Four modes route tasks appropriately: send only a link or body copy for a quick diagnosis by default; request writing to get usable text first; use a full audit to break findings down by target engine and page; or use a performance retest with clearly defined data sources, numerators, denominators, and comparison conditions. Simple tasks do not require a full-length report. Supports platform-specific checks for Google AI Overviews / AI Mode, Bing / Copilot, ChatGPT Search, Perplexity, and Claude. Search, training, and user-triggered visits are assessed separately. For Chinese platforms, checks are adapted to actually available sources and direct observations rather than applying rules from other engines. v8 standardizes scoring and evidence criteria, limits the scope of local blocks, distinguishes answer trigger rate, conditional citation rate, and overall citation rate, and updates Google site-level AI control checks. Use it for your own websites, articles on third-party platforms, and unpublished drafts. Recommendations distinguish what you can change from items that require platform-side validation. Each key finding includes evidence or clearly stated limitations. Scores are provided when needed; data, authors, or citations are never fabricated, and rankings, indexing, or AI citations are not guaranteed. Actual run example (2026-09-07; test material, not business results) Title mode: Given test copy for “How to write a team weekly report” with a request to return only 3 titles, the actual output was: 1. How to Write a Team Weekly Report: Blank Template Included 2. Team Weekly Report Writing Guide: Progress, Issues, and Next Week’s Plan (Template Included) 3. Team Weekly Report Template: This Week’s Progress, Issues, and Next Week’s Plan Calculation mode: Simulated 12 attempts, with 10 successes and 2 timeouts; 2 successful runs generated AI answers, and 1 cited the target website. Actual output: AI answer trigger rate 2/10 = 20%, conditional citation rate 1/2 = 50%, and overall observed citation rate 1/10 = 10%. Normal no-answer cases remain in the overall denominator, while timeouts are listed separately. These figures validate the calculation criteria only and do not represent actual citation performance.
WriteUltimate General SEO Writer
This is perhaps the best SEO article writing skill. With this skill, you can ensure your articles comply with the E-E-A-T framework and avoid fabrication. You need to provide product information and competitor articles. (Below is an AI-written detailed introduction.) This general SEO batch writing skill can help you transform a competitor's article library into 10 original, high-quality SEO posts for any product or service: It automatically scans and scores all articles in your current section, filters top references, avoids repeating already published topics, builds a clear 10-article strategy matrix (including keywords, intent, unique perspectives, and natural product mentions), and then generates HTML articles ready for WordPress, which follow Google's E-E-A-T principles and on-page SEO best practices—each article comes with a built-in quality assessment report at the end.
WriteAIGC Reduction & Rewrite v7.0
📚 Academic Paper AIGC Reduction and Quality-Preserving Rewriting Expert v7.0 Designed for graduate students, researchers, and paper authors, this academic text optimization skill operates on a core closed loop of 'source control → process correction → result verification → reverse self-check → iterative re-check'. It systematically diagnoses and optimizes issues such as templated expressions, mechanical logic, vague content, inaccurate terminology, and style inconsistencies while preserving original meaning, technical terms, data, and core conclusions. 🔍📝 🌟 Core Capabilities 🔬 Multi-layer Risk Diagnosis Covers 10 types of universal text fingerprints and assists in identifying common expression patterns of models such as ChatGPT, Claude, DeepSeek, and Wenxin Yiyan. 🧠 Deep Semantic Restructuring Goes beyond synonym replacement to rebuild more natural and in-depth academic reasoning by adjusting proposition expression, information order, argument approach, and evidence organization. ✍️ Quality-Preserving Rewriting Comprehensively applies 13 sentence transformation strategies and 20 methods for cleaning high-frequency templated expressions, improving mechanical sentence structures, repetitive connectors, and overly rigid formatting. 📊 Full-text Structure Diagnosis Through macro-cycle and five key triangles, checks whether research problems, theory, literature review, methods, results, conclusions, and innovation form a complete closed loop. 🧩 Fine-grained Section Adaptation Develops differentiated diagnostic and rewriting strategies for abstract, introduction, literature review, research methods, results, discussion, and conclusion respectively. 🌐 Cross-language Risk Scanning Assists in identifying translationese, passive voice stacking, long sentence nesting, and mixed Chinese-English formatting abnormalities to make Chinese academic expression more natural and accurate. 🔄 Reverse Self-check Loop After rewriting, re-verifies from three aspects: technique distribution, new text fingerprints, and information integrity, to avoid 'becoming more templated' or losing key content. 🛡️ Academic Integrity Protection Does not fabricate literature, data, cases, or policy evidence; separately marks information requiring author verification and reminds users to honestly disclose AI usage. 🎯 Use Cases ✅ Single paragraph or partial section optimization ✅ Targeted modification of marked paragraphs from inspection reports ✅ Polishing of abstract, introduction, literature review, discussion, and conclusion ✅ Full-text AIGC risk feature diagnosis ✅ Language and structure adaptation for target journals ✅ Pre-submission quality review and consistency check 📦 Final Deliverables 📄 Quality-preserving rewritten text 🔎 Risk and issue diagnosis report 🛠️ Rewriting strategy and technique description ✅ Reverse self-check and information integrity report 💡 Items requiring author verification and subsequent revision suggestions 🎓 Original meaning preserved · Logic intact · No fabricated data · Academic quality maintained ⚠️ This skill aims to improve academic expression quality and reduce text risk features. It does not guarantee passage through any specific detection platform or achieving a particular detection score.
Google 2026 Checker - SagaSu
Description
Based on Google's latest 2026 standards (E-E-A-T, March 2026 Core Update), it performs comprehensive quality checks on SEO articles, generates structured scoring reports, and provides step-by-step optimization guidance and direct rewriting. Suitable for pre-publishing checks and post-publishing audits, usable by beginners and experts alike.
Related Skills
View allSEO+GEO Visibility Engine
Optimize the search performance and AI citation readiness of your articles, product pages, and landing pages. Quickly identify the issues most worth fixing, or get ready-to-use titles, rewrites, content briefs, technical fix lists, or performance retest plans. Four modes route tasks appropriately: send only a link or body copy for a quick diagnosis by default; request writing to get usable text first; use a full audit to break findings down by target engine and page; or use a performance retest with clearly defined data sources, numerators, denominators, and comparison conditions. Simple tasks do not require a full-length report. Supports platform-specific checks for Google AI Overviews / AI Mode, Bing / Copilot, ChatGPT Search, Perplexity, and Claude. Search, training, and user-triggered visits are assessed separately. For Chinese platforms, checks are adapted to actually available sources and direct observations rather than applying rules from other engines. v8 standardizes scoring and evidence criteria, limits the scope of local blocks, distinguishes answer trigger rate, conditional citation rate, and overall citation rate, and updates Google site-level AI control checks. Use it for your own websites, articles on third-party platforms, and unpublished drafts. Recommendations distinguish what you can change from items that require platform-side validation. Each key finding includes evidence or clearly stated limitations. Scores are provided when needed; data, authors, or citations are never fabricated, and rankings, indexing, or AI citations are not guaranteed. Actual run example (2026-09-07; test material, not business results) Title mode: Given test copy for “How to write a team weekly report” with a request to return only 3 titles, the actual output was: 1. How to Write a Team Weekly Report: Blank Template Included 2. Team Weekly Report Writing Guide: Progress, Issues, and Next Week’s Plan (Template Included) 3. Team Weekly Report Template: This Week’s Progress, Issues, and Next Week’s Plan Calculation mode: Simulated 12 attempts, with 10 successes and 2 timeouts; 2 successful runs generated AI answers, and 1 cited the target website. Actual output: AI answer trigger rate 2/10 = 20%, conditional citation rate 1/2 = 50%, and overall observed citation rate 1/10 = 10%. Normal no-answer cases remain in the overall denominator, while timeouts are listed separately. These figures validate the calculation criteria only and do not represent actual citation performance.
WriteUltimate General SEO Writer
This is perhaps the best SEO article writing skill. With this skill, you can ensure your articles comply with the E-E-A-T framework and avoid fabrication. You need to provide product information and competitor articles. (Below is an AI-written detailed introduction.) This general SEO batch writing skill can help you transform a competitor's article library into 10 original, high-quality SEO posts for any product or service: It automatically scans and scores all articles in your current section, filters top references, avoids repeating already published topics, builds a clear 10-article strategy matrix (including keywords, intent, unique perspectives, and natural product mentions), and then generates HTML articles ready for WordPress, which follow Google's E-E-A-T principles and on-page SEO best practices—each article comes with a built-in quality assessment report at the end.
WriteAIGC Reduction & Rewrite v7.0
📚 Academic Paper AIGC Reduction and Quality-Preserving Rewriting Expert v7.0 Designed for graduate students, researchers, and paper authors, this academic text optimization skill operates on a core closed loop of 'source control → process correction → result verification → reverse self-check → iterative re-check'. It systematically diagnoses and optimizes issues such as templated expressions, mechanical logic, vague content, inaccurate terminology, and style inconsistencies while preserving original meaning, technical terms, data, and core conclusions. 🔍📝 🌟 Core Capabilities 🔬 Multi-layer Risk Diagnosis Covers 10 types of universal text fingerprints and assists in identifying common expression patterns of models such as ChatGPT, Claude, DeepSeek, and Wenxin Yiyan. 🧠 Deep Semantic Restructuring Goes beyond synonym replacement to rebuild more natural and in-depth academic reasoning by adjusting proposition expression, information order, argument approach, and evidence organization. ✍️ Quality-Preserving Rewriting Comprehensively applies 13 sentence transformation strategies and 20 methods for cleaning high-frequency templated expressions, improving mechanical sentence structures, repetitive connectors, and overly rigid formatting. 📊 Full-text Structure Diagnosis Through macro-cycle and five key triangles, checks whether research problems, theory, literature review, methods, results, conclusions, and innovation form a complete closed loop. 🧩 Fine-grained Section Adaptation Develops differentiated diagnostic and rewriting strategies for abstract, introduction, literature review, research methods, results, discussion, and conclusion respectively. 🌐 Cross-language Risk Scanning Assists in identifying translationese, passive voice stacking, long sentence nesting, and mixed Chinese-English formatting abnormalities to make Chinese academic expression more natural and accurate. 🔄 Reverse Self-check Loop After rewriting, re-verifies from three aspects: technique distribution, new text fingerprints, and information integrity, to avoid 'becoming more templated' or losing key content. 🛡️ Academic Integrity Protection Does not fabricate literature, data, cases, or policy evidence; separately marks information requiring author verification and reminds users to honestly disclose AI usage. 🎯 Use Cases ✅ Single paragraph or partial section optimization ✅ Targeted modification of marked paragraphs from inspection reports ✅ Polishing of abstract, introduction, literature review, discussion, and conclusion ✅ Full-text AIGC risk feature diagnosis ✅ Language and structure adaptation for target journals ✅ Pre-submission quality review and consistency check 📦 Final Deliverables 📄 Quality-preserving rewritten text 🔎 Risk and issue diagnosis report 🛠️ Rewriting strategy and technique description ✅ Reverse self-check and information integrity report 💡 Items requiring author verification and subsequent revision suggestions 🎓 Original meaning preserved · Logic intact · No fabricated data · Academic quality maintained ⚠️ This skill aims to improve academic expression quality and reduce text risk features. It does not guarantee passage through any specific detection platform or achieving a particular detection score.
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