{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_basmo-chatbook","slug":"basmo-chatbook","name":"Basmo Chatbook","type":"product","url":"https://basmo.app","page_url":"https://unfragile.ai/basmo-chatbook","categories":["chatbots-assistants"],"tags":[],"pricing":{"model":"paid","free":false,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_basmo-chatbook__cap_0","uri":"capability://memory.knowledge.book.content.to.conversational.ai.indexing","name":"book-content-to-conversational-ai-indexing","description":"Ingests book text (via manual upload, OCR, or ISBN lookup) and creates a searchable, semantically-indexed knowledge base that enables the AI to retrieve relevant passages during conversation. The system likely uses vector embeddings (sentence or paragraph-level) to map book content into a high-dimensional space, allowing retrieval-augmented generation (RAG) to ground responses in actual book text rather than relying solely on the model's training data. This prevents hallucination by anchoring answers to source material.","intents":["I want to upload a PDF or image of a book and immediately start asking questions about its content","I need the chatbot to cite specific passages when answering my questions about a book","I want to ensure the AI is answering based on the actual book, not its general knowledge"],"best_for":["students studying dense academic texts who need passage-level citations","book clubs wanting to explore themes with AI-assisted discussion","researchers cross-referencing multiple books without manual note-taking"],"limitations":["OCR accuracy degrades on scanned books with poor image quality, leading to indexing errors","Chunking strategy (sentence vs. paragraph vs. page-level) affects retrieval precision; too-small chunks lose context, too-large chunks reduce relevance ranking","No built-in deduplication of repeated passages across editions, potentially creating noise in retrieval","Indexing latency scales with book length; 500+ page books may take minutes to process"],"requires":["Book source in digital format (PDF, EPUB, image scan, or ISBN for lookup)","Active internet connection for embedding generation and vector storage","Storage quota on Basmo servers (likely tiered by subscription)"],"input_types":["PDF files","image scans (JPG, PNG)","ISBN numbers","plain text"],"output_types":["vector embeddings (internal)","indexed knowledge base (internal)","passage citations in chat responses"],"categories":["memory-knowledge","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_basmo-chatbook__cap_1","uri":"capability://text.generation.language.context.aware.conversational.qa.with.passage.grounding","name":"context-aware-conversational-qa-with-passage-grounding","description":"Maintains a multi-turn conversation context while dynamically retrieving relevant book passages to answer user questions. The system uses a context window (likely 4K-8K tokens) to track conversation history, combines it with real-time semantic search over the indexed book, and generates responses that cite specific passages. This prevents the chatbot from drifting into general knowledge and ensures answers remain grounded in the book's actual content, reducing hallucination risk compared to vanilla LLM chat.","intents":["I want to ask follow-up questions and have the AI remember what we discussed earlier in the conversation","I want the AI to explain a concept from the book in the context of something I asked 5 messages ago","I want to challenge the AI's answer and have it re-examine the book passage it cited"],"best_for":["students engaged in deep, multi-turn analysis of complex texts","researchers exploring interconnected themes across a book","book club participants building on previous discussion points"],"limitations":["Context window limits conversation depth; very long discussions (50+ turns) may lose early context or require summarization","Retrieval may fail for nuanced questions requiring synthesis across multiple non-adjacent passages","AI may still hallucinate details not in the book if the question is ambiguous or the retrieval returns low-confidence matches","No explicit fact-checking against the book; if the AI misinterprets a passage, it will confidently propagate the error"],"requires":["Book already indexed in the system","Active chat session with conversation history","Sufficient API quota for multi-turn LLM calls"],"input_types":["natural language questions","follow-up prompts","clarification requests"],"output_types":["natural language responses","passage citations with page/chapter references","structured summaries of book concepts"],"categories":["text-generation-language","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_basmo-chatbook__cap_2","uri":"capability://data.processing.analysis.multi.format.book.input.with.ocr.fallback","name":"multi-format-book-input-with-ocr-fallback","description":"Accepts books in multiple formats (PDF, EPUB, image scans, ISBN lookup) and automatically converts them into machine-readable text using OCR (optical character recognition) for scanned books or native text extraction for digital formats. The system likely uses a cloud-based OCR service (e.g., Tesseract, AWS Textract, or proprietary) to handle low-quality scans, with fallback logic to retry failed pages or prompt users to re-upload clearer images. This enables users to add physical books to their library without manual transcription.","intents":["I have a physical book and want to photograph it and add it to Basmo without typing it out","I have a PDF of a book and want to upload it directly","I want to search for a book by ISBN and have Basmo automatically fetch it"],"best_for":["users with physical book collections who want to digitize without manual effort","students with scanned lecture notes or textbook excerpts","international users with books in non-English languages (if OCR supports them)"],"limitations":["OCR accuracy is highly dependent on image quality; blurry photos, poor lighting, or unusual fonts can result in 5-20% character error rates","Handwritten annotations or marginalia are not reliably captured by OCR","Complex layouts (multi-column text, sidebars, footnotes) may be extracted out of order or with missing context","ISBN lookup may fail for obscure, self-published, or very old books","Processing time scales with book length and image quality; 300+ page scans may take 10-30 minutes"],"requires":["High-quality camera or scanner for physical books (minimum 300 DPI for OCR)","Internet connection for cloud OCR processing","Storage quota for uploaded files"],"input_types":["PDF files","EPUB files","JPG/PNG image scans","ISBN numbers","plain text files"],"output_types":["extracted text (internal)","indexed knowledge base","error reports for failed OCR pages"],"categories":["data-processing-analysis","image-visual"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_basmo-chatbook__cap_3","uri":"capability://memory.knowledge.book.library.management.with.metadata.preservation","name":"book-library-management-with-metadata-preservation","description":"Maintains a user's personal library of indexed books with metadata (title, author, ISBN, cover image, reading progress, tags, notes) and enables browsing, searching, and organizing books by category, rating, or custom collections. The system likely stores metadata in a relational database (user → books → chapters/sections) and provides a UI for library management. This allows users to manage multiple books and switch between them in conversations without re-uploading.","intents":["I want to keep a library of all the books I've added to Basmo and easily switch between them","I want to tag books by subject (philosophy, history, fiction) and filter my library","I want to track my reading progress and see which books I've finished"],"best_for":["avid readers managing 10+ books simultaneously","students organizing books by course or subject","book clubs coordinating reading across multiple titles"],"limitations":["No built-in integration with Goodreads or other book tracking platforms; metadata must be manually entered or auto-populated from ISBN lookup","Library size limits may apply (e.g., max 100 books on free tier)","No collaborative library sharing; each user has a separate library","Metadata editing is manual; no bulk import from reading lists or CSV files"],"requires":["Basmo account with persistent storage","Books already indexed in the system"],"input_types":["book metadata (title, author, ISBN)","custom tags and notes","reading progress indicators"],"output_types":["organized library view","filtered/sorted book lists","metadata summaries"],"categories":["memory-knowledge","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_basmo-chatbook__cap_4","uri":"capability://search.retrieval.semantic.search.across.indexed.books","name":"semantic-search-across-indexed-books","description":"Enables users to search for concepts, themes, or passages across an indexed book using natural language queries rather than keyword matching. The system converts the user's query into a vector embedding and performs similarity search against the book's indexed passages, returning the most relevant sections ranked by semantic relevance. This allows users to find discussions of a topic even if they don't know the exact wording used in the book.","intents":["I want to find all passages in the book that discuss a specific theme or concept","I want to search for 'the author's view on technology' without knowing the exact chapter","I want to see how a character or idea evolves throughout the book"],"best_for":["researchers analyzing thematic patterns across a book","students preparing essays and needing to locate supporting passages","readers exploring interconnected concepts without manual indexing"],"limitations":["Semantic search may return false positives if the query is ambiguous or the book discusses multiple unrelated topics with similar language","Search quality depends on embedding model quality; older or domain-specific books may have lower relevance ranking","No support for complex boolean queries (AND, OR, NOT); search is purely semantic","Latency for large books (500+ pages) may be 1-3 seconds per search"],"requires":["Book indexed with vector embeddings","Query in natural language"],"input_types":["natural language search queries","concept names","thematic descriptions"],"output_types":["ranked list of relevant passages","passage excerpts with page/chapter references","relevance scores"],"categories":["search-retrieval","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_basmo-chatbook__cap_5","uri":"capability://text.generation.language.ai.powered.book.summarization.and.key.insights.extraction","name":"ai-powered-book-summarization-and-key-insights-extraction","description":"Automatically generates summaries of books or chapters and extracts key insights, themes, and arguments using the LLM. The system likely uses the indexed book content as context, prompts the LLM to identify main ideas and supporting evidence, and presents summaries at multiple granularities (full book, chapter, section). This allows users to quickly grasp a book's core ideas without reading the entire text.","intents":["I want a quick summary of the book to decide if I want to read it fully","I want a summary of a specific chapter I'm about to read","I want the AI to identify the 5 most important ideas in the book"],"best_for":["busy professionals wanting to extract value from books without full reading","students preparing for exams and needing condensed overviews","readers deciding whether a book is worth their time"],"limitations":["Summaries may oversimplify nuanced arguments or miss subtle themes important to the author's intent","AI may prioritize dramatic or surprising content over core arguments, skewing the summary","No customization of summary length or focus; summaries are generated with fixed parameters","Summaries are static; they don't update if the book is re-indexed or if new passages are added","Risk of hallucination: AI may invent insights not actually present in the book"],"requires":["Book indexed in the system","Sufficient API quota for LLM summarization calls"],"input_types":["indexed book content","chapter or section identifiers"],"output_types":["text summaries","bullet-point key insights","thematic overviews"],"categories":["text-generation-language","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_basmo-chatbook__cap_6","uri":"capability://text.generation.language.multi.turn.dialogue.with.follow.up.clarification","name":"multi-turn-dialogue-with-follow-up-clarification","description":"Supports extended conversations where users ask follow-up questions, request clarifications, and explore ideas in depth. The system maintains conversation history, tracks which passages were cited in previous responses, and allows users to ask the AI to re-examine or reinterpret passages based on new context. This enables Socratic-style learning where users progressively deepen their understanding through dialogue.","intents":["I want to ask the AI to explain a concept in simpler terms after its first explanation","I want to challenge the AI's interpretation and ask it to reconsider a passage","I want to explore how a concept from one chapter relates to ideas in another chapter"],"best_for":["students engaged in active learning and critical thinking","researchers exploring complex ideas through dialogue","book club participants debating interpretations"],"limitations":["Context window limits conversation length; very long dialogues (100+ turns) may lose early context","AI may contradict itself if earlier context is dropped from the context window","No explicit memory of previous conversations; each new chat session starts fresh","AI may become increasingly confident in incorrect interpretations if not corrected early"],"requires":["Active chat session","Book indexed in the system"],"input_types":["natural language questions and follow-ups","clarification requests","challenge statements"],"output_types":["natural language responses","passage citations","revised explanations"],"categories":["text-generation-language","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_basmo-chatbook__cap_7","uri":"capability://safety.moderation.hallucination.mitigation.through.passage.grounding","name":"hallucination-mitigation-through-passage-grounding","description":"Reduces AI hallucination by requiring the LLM to cite specific passages from the indexed book when answering questions. The system uses a retrieval-augmented generation (RAG) approach where the LLM is prompted to only answer based on retrieved passages and to explicitly state when information is not found in the book. This creates accountability and allows users to verify answers against source material.","intents":["I want to verify that the AI's answer is actually in the book, not just general knowledge","I want the AI to tell me when it doesn't know something rather than making it up","I want to cite the AI's answers in an essay and need to know the exact source"],"best_for":["academic users who need verifiable sources","researchers building arguments on cited evidence","students learning to distinguish between book content and general knowledge"],"limitations":["Passage retrieval may fail for nuanced questions requiring synthesis across multiple passages; the AI may then refuse to answer rather than hallucinate","AI may still misinterpret or misquote passages, especially if they are ambiguous or context-dependent","Grounding reduces the AI's ability to provide general knowledge context; users may need to ask follow-up questions to understand unfamiliar concepts","No explicit fact-checking; if the book itself contains errors, the AI will propagate them"],"requires":["Book indexed with vector embeddings","Retrieval system returning relevant passages","LLM prompt engineering to enforce grounding"],"input_types":["user questions","retrieved passages from the book"],"output_types":["grounded responses with citations","explicit statements of uncertainty","passage references"],"categories":["safety-moderation","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_basmo-chatbook__cap_8","uri":"capability://memory.knowledge.reading.progress.tracking.and.personalized.recommendations","name":"reading-progress-tracking-and-personalized-recommendations","description":"Tracks which books a user has read, is currently reading, or wants to read, and optionally provides personalized recommendations based on reading history and preferences. The system stores reading progress (percentage complete, last read date, bookmarks) and may use collaborative filtering or content-based recommendation algorithms to suggest similar books. This helps users discover new books and maintain reading momentum.","intents":["I want to track my reading progress across multiple books","I want Basmo to recommend books similar to ones I've enjoyed","I want to see statistics about my reading habits (books per month, genres read, etc.)"],"best_for":["avid readers managing multiple books simultaneously","users seeking personalized book recommendations","book clubs coordinating reading schedules"],"limitations":["Recommendations require sufficient reading history (5+ books) to be meaningful","No integration with external book discovery platforms (Goodreads, Amazon); recommendations are limited to books already in Basmo's system","Recommendation algorithm quality is unknown; may be simplistic (e.g., genre-based) rather than sophisticated","No social recommendations (e.g., 'books your friends read'); recommendations are purely personalized"],"requires":["Basmo account with reading history","Books indexed in the system"],"input_types":["reading progress indicators","book ratings or preferences","reading history"],"output_types":["reading progress summaries","personalized recommendations","reading statistics"],"categories":["memory-knowledge","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_basmo-chatbook__cap_9","uri":"capability://text.generation.language.export.and.citation.generation.for.academic.use","name":"export-and-citation-generation-for-academic-use","description":"Allows users to export passages, summaries, or conversation transcripts in standard citation formats (APA, MLA, Chicago) for use in essays, research papers, or presentations. The system likely integrates with citation management tools (Zotero, Mendeley) or generates citations programmatically based on book metadata. This enables seamless integration with academic workflows.","intents":["I want to export a passage from the book with proper citation for my essay","I want to generate a bibliography of all books I've cited in my Basmo conversations","I want to export my conversation with the AI as a study guide with citations"],"best_for":["students writing academic papers and needing proper citations","researchers documenting sources for literature reviews","educators creating study materials with cited passages"],"limitations":["Citation accuracy depends on book metadata quality; incomplete or incorrect ISBN/author info will result in malformed citations","No support for citing specific page numbers if the book was uploaded as images or unstructured text","Export formats are limited to common academic styles; specialized formats (IEEE, ACS) may not be supported","No integration with citation management tools; exports are manual"],"requires":["Book indexed with complete metadata (title, author, ISBN, publication date)","Passages or conversations to export"],"input_types":["selected passages","conversation transcripts","book metadata"],"output_types":["formatted citations (APA, MLA, Chicago)","exported passages with citations","bibliographies"],"categories":["text-generation-language","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":40,"verified":false,"data_access_risk":"high","permissions":["Book source in digital format (PDF, EPUB, image scan, or ISBN for lookup)","Active internet connection for embedding generation and vector storage","Storage quota on Basmo servers (likely tiered by subscription)","Book already indexed in the system","Active chat session with conversation history","Sufficient API quota for multi-turn LLM calls","High-quality camera or scanner for physical books (minimum 300 DPI for OCR)","Internet connection for cloud OCR processing","Storage quota for uploaded files","Basmo account with persistent storage"],"failure_modes":["OCR accuracy degrades on scanned books with poor image quality, leading to indexing errors","Chunking strategy (sentence vs. paragraph vs. page-level) affects retrieval precision; too-small chunks lose context, too-large chunks reduce relevance ranking","No built-in deduplication of repeated passages across editions, potentially creating noise in retrieval","Indexing latency scales with book length; 500+ page books may take minutes to process","Context window limits conversation depth; very long discussions (50+ turns) may lose early context or require summarization","Retrieval may fail for nuanced questions requiring synthesis across multiple non-adjacent passages","AI may still hallucinate details not in the book if the question is ambiguous or the retrieval returns low-confidence matches","No explicit fact-checking against the book; if the AI misinterprets a passage, it will confidently propagate the error","OCR accuracy is highly dependent on image quality; blurry photos, poor lighting, or unusual fonts can result in 5-20% character error rates","Handwritten annotations or marginalia are not reliably captured by OCR","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.31666666666666665,"quality":0.72,"ecosystem":0.15000000000000002,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.1,"match_graph":0.35,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:29.134Z","last_scraped_at":"2026-04-05T13:23:42.561Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=basmo-chatbook","compare_url":"https://unfragile.ai/compare?artifact=basmo-chatbook"}},"signature":"bSXUXJoECkev1o0Pm1AkT/IdelqPjejE5gWeM5UlAux6CI6+mUa17DJDeaDyoQjur+3V3+dQtbrJAwJjbxIvCg==","signedAt":"2026-06-22T05:12:35.137Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/basmo-chatbook","artifact":"https://unfragile.ai/basmo-chatbook","verify":"https://unfragile.ai/api/v1/verify?slug=basmo-chatbook","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}