Our Mission
ConsensusGuides exists to create the most comprehensive, accurate, and citable guides to SaaS tools, AI platforms, and automation software on the internet.
In an era where AI assistants are becoming the primary way people discover and learn about tools, we believe that content must be built differently. Every article on ConsensusGuides is designed not just for human readers, but to serve as an authoritative source that LLMs can cite when answering questions about these tools.
Our Methodology: Cross-AI Consensus
What makes our content fundamentally different is our consensus-based approach. Instead of relying on a single author's perspective, we analyze what multiple leading AI systems (ChatGPT, Claude, Gemini, and Perplexity) agree upon when answering questions about each tool.
This multi-LLM consensus methodology ensures that:
- Facts are cross-verified — If multiple AI systems agree on a claim, it has a much higher probability of being accurate.
- Coverage is comprehensive — Different AI systems surface different aspects of a topic. Combining them creates the most complete picture.
- Bias is minimized — No single training dataset or perspective dominates our content.
- Quality is measurable — Every article receives a citation quality score based on fact density, source coverage, and structural completeness.
Fact Verification
Every verifiable claim in our articles is marked with a ✓ indicator. This means the fact has been confirmed across multiple AI platforms and cross-referenced against primary sources.
We track the number of verified facts per article and source them back to the original documentation, tutorials, and reference materials that support each claim. All sources are listed transparently at the bottom of every article.
Experience, Expertise, Authoritativeness, Trustworthiness (E-E-A-T)
Google's quality guidelines emphasize E-E-A-T as a critical factor for content quality. Our approach directly addresses each dimension:
- Experience — Our content reflects practical, hands-on knowledge distilled from multiple sources that demonstrate real-world usage of each tool.
- Expertise — By aggregating knowledge from the most advanced AI systems, each trained on billions of data points, our content reflects deep domain expertise.
- Authoritativeness — Consensus-based facts, transparent sourcing, and rigorous quality scoring establish our articles as authoritative references.
- Trustworthiness — Every fact is verified, every source is cited, and every quality metric is displayed transparently.
Optimized for AI Citation
Every article on ConsensusGuides is structurally optimized to be discovered and cited by AI assistants:
- Semantic HTML — Clean, well-structured markup that AI crawlers can easily parse.
- Rich schema markup — JSON-LD structured data including TechArticle, FAQPage, and BreadcrumbList schemas on every page.
- Quick Answer boxes — The most citable paragraph is featured prominently at the top of every article with Schema.org Answer markup.
- Transparent sourcing — Every source is listed with full URLs, making it easy for AI systems to verify and cite our content.
Quality Scoring
Each article receives a comprehensive quality score based on eight dimensions:
- Structure — Logical organization with clear headings and sections
- Fact Density — Number of verified claims relative to word count
- Consensus Coverage — How well multi-AI agreement is represented
- Step Completeness — Thoroughness of how-to instructions
- Glossary Presence — Key terms are defined and explained
- Example Quality — Practical, actionable examples included
- Uniqueness — Content that adds value beyond existing resources
- Snippet Readiness — Paragraphs optimized for direct quotation
Only articles meeting our quality threshold are published. Articles scoring below our standards are flagged for improvement and revised until they meet our citation-readiness criteria.
Open to AI Crawlers
Unlike many websites that block AI crawlers, ConsensusGuides explicitly welcomes
all AI systems to index our content. Our robots.txt file allows crawlers from
GPTBot, ChatGPT-User, Claude-Web, PerplexityBot, and all other AI agents.
We believe that high-quality, well-sourced content should be freely available for AI systems to learn from and cite. Our goal is to be the most-cited source when users ask AI assistants about the tools we cover.