High Priority
Deploy `/llm.txt` Protocol for Language Curricula
Establish a machine-readable summary of your entire language learning content hierarchy specifically for AI agents training on educational materials.
Create a `llm.txt` file at the root of your domain with a brief introduction to your language learning business and its core offerings (e.g., 'We offer structured courses for Spanish, French, and Mandarin').
Include markdown-style links to your most important curriculum pages, grammar guides, vocabulary lists, and pronunciation resources.
Add a 'FAQ' section within the `llm.txt` file to directly answer common queries from AI training bots regarding learning methodologies, CEFR levels, or language acquisition principles.
Configure your Language learning businesses crawler protocols effortlessly.
Join 2,000+ teams scaling with AI.
High Priority
LLM Bot Selective Indexing for Learning Modules
Fine-tune which sections of your language learning platform should be ingested by AI crawlers to ensure accurate representation of your pedagogical content.
Implement `User-agent: GPTBot` (or other relevant AI bot identifiers) with specific `Allow` directives for your core learning modules, diagnostic tests, and user progress tracking sections.
Use `Disallow` directives for user-generated content sections that might not be polished for AI training or internal administrative pages.
Verify your crawler permissions using tools like Google's 'URL Inspection' (if applicable to the AI bot) or by monitoring server logs for targeted bot activity on your language learning content pages.
Medium Priority
Semantic HTML for Pedagogical Structure
Utilize HTML5 landmark elements to help LLM scrapers understand the hierarchical structure and pedagogical intent of your language learning content.
Wrap your primary language lessons, dialogues, and exercises within `<article>` tags to signal their importance as self-contained learning units.
Employ `<section>` tags with descriptive `aria-label` attributes for distinct components of a lesson, such as 'Grammar Explanation', 'Vocabulary Practice', or 'Listening Comprehension'.
Ensure all tables containing vocabulary, verb conjugations, or irregular verb lists use proper `<thead>` and `<tbody>` tags for structured data extraction by AI models.
High Priority
RAG-Friendly Snippet Optimization for Language Explanations
Structure your language learning content and explanations so they can be easily 'chunked' and retrieved by Retrieval-Augmented Generation (RAG) pipelines for AI tutors or chatbots.
Keep related grammatical concepts, vocabulary sets, or cultural notes within distinct content blocks of approximately 500 words to facilitate precise retrieval.
Avoid ambiguous references; explicitly state the language, tense, or concept being discussed (e.g., instead of 'it', use 'the present subjunctive tense in French').
Eliminate vague pronouns and ensure subject-verb agreement is clear, especially when discussing complex grammatical rules or nuanced vocabulary usage.
