{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_openread","slug":"openread","name":"OpenRead","type":"webapp","url":"https://www.openread.academy","page_url":"https://unfragile.ai/openread","categories":["research-search"],"tags":[],"pricing":{"model":"free","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_openread__cap_0","uri":"capability://text.generation.language.ai.powered.academic.paper.summarization.with.key.findings.extraction","name":"ai-powered academic paper summarization with key findings extraction","description":"Automatically generates concise summaries of academic papers by processing PDF content through a language model pipeline that identifies and extracts key findings, methodology, and conclusions. The system parses PDF structure to isolate abstract, body sections, and results, then applies abstractive summarization to produce human-readable summaries that capture essential research contributions without requiring manual reading of full papers.","intents":["I need to quickly understand what a 20-page paper is about without reading the entire document","I want to extract the main findings and methodology from a research paper in under 2 minutes","I need summaries of papers in multiple languages to understand international research"],"best_for":["Graduate students conducting literature reviews across dozens of papers","Researchers with limited time seeking rapid paper triage before deep reading","Non-English speaking academics needing translation alongside summarization"],"limitations":["Summarization quality degrades on papers with non-standard formatting or scanned PDFs without OCR","Cannot capture nuanced theoretical arguments that require full contextual reading","Multi-language support may introduce translation artifacts that obscure technical terminology"],"requires":["PDF file upload capability (typical max 50MB)","Internet connection for cloud-based LLM inference","Browser with JavaScript enabled for UI interaction"],"input_types":["PDF documents","Academic papers in standard formats"],"output_types":["Text summaries","Structured key findings","Methodology descriptions"],"categories":["text-generation-language","academic-research"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_openread__cap_1","uri":"capability://search.retrieval.semantic.search.across.academic.literature.with.relevance.ranking","name":"semantic search across academic literature with relevance ranking","description":"Enables researchers to search academic papers using natural language queries that are converted to semantic embeddings and matched against a database of paper embeddings, returning results ranked by semantic relevance rather than keyword matching. The system likely uses dense vector representations (embeddings) of paper abstracts and metadata to perform similarity search, allowing queries like 'machine learning approaches to protein folding' to surface relevant papers even without exact keyword matches.","intents":["I want to find papers related to my research topic using natural language instead of boolean operators","I need to discover papers that are semantically similar to a paper I already found relevant","I want to search across papers in my field without knowing the exact terminology researchers use"],"best_for":["Researchers exploring new domains where they lack domain-specific terminology","Students building literature reviews who need broad topic discovery","Interdisciplinary researchers seeking papers across multiple fields"],"limitations":["Search quality depends on the size and diversity of the indexed paper corpus","Semantic search may return papers with high embedding similarity but low practical relevance","No apparent filtering by publication date, venue, or citation count to refine results","Unknown whether the search indexes full paper text or only abstracts/metadata"],"requires":["Access to OpenRead's indexed academic paper database","Internet connection for query processing","Natural language query formulation ability"],"input_types":["Natural language search queries","Paper identifiers for similarity search"],"output_types":["Ranked list of papers","Relevance scores","Paper metadata (title, authors, abstract)"],"categories":["search-retrieval","academic-research"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_openread__cap_2","uri":"capability://text.generation.language.multi.language.paper.analysis.and.cross.lingual.research.discovery","name":"multi-language paper analysis and cross-lingual research discovery","description":"Processes academic papers and research queries in multiple languages, automatically detecting source language and providing analysis, summaries, and search results in the user's preferred language. Implementation likely uses multilingual language models (e.g., mBERT, XLM-RoBERTa) or translation pipelines to normalize papers across languages before analysis, enabling non-English researchers to access and understand papers regardless of publication language.","intents":["I need to understand a paper published in Chinese/Spanish/German without translating it manually","I want to search for research papers across multiple languages to ensure comprehensive literature coverage","I need to read and compare papers from different language research communities in my field"],"best_for":["Non-English speaking researchers in regions with strong local research communities","International research teams collaborating across language barriers","Researchers studying topics where significant work is published in non-English languages"],"limitations":["Translation quality varies significantly across language pairs; rare languages may have poor support","Technical terminology may be mistranslated, especially in specialized domains","No indication of which languages are supported or how many language pairs are covered","Multilingual models often have lower performance on non-English text compared to English"],"requires":["Papers or queries in supported languages","Internet connection for language detection and translation processing","No explicit language selection required (auto-detection)"],"input_types":["PDF documents in multiple languages","Search queries in multiple languages"],"output_types":["Translated summaries","Localized search results","Multi-language metadata"],"categories":["text-generation-language","academic-research"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_openread__cap_3","uri":"capability://data.processing.analysis.citation.context.extraction.and.paper.relationship.mapping","name":"citation context extraction and paper relationship mapping","description":"Identifies citations within papers and extracts the context in which citations appear, enabling researchers to understand how papers relate to and build upon each other. The system parses paper text to locate citation markers, retrieves surrounding sentences/paragraphs, and maps citation networks to show which papers cite which others and in what context, creating a graph of research relationships without requiring manual citation manager integration.","intents":["I want to see how a specific paper is cited and used in other research","I need to understand the citation context to see if a cited paper is actually relevant to my research","I want to trace the evolution of an idea through citations across multiple papers"],"best_for":["Researchers conducting systematic literature reviews requiring citation analysis","Students learning how to properly contextualize citations in their own work","Researchers mapping research trends and influence networks in their field"],"limitations":["Limited integration with major citation managers (Zotero, Mendeley, EndNote) means citation data cannot be exported to existing workflows","Citation extraction accuracy depends on paper formatting consistency; non-standard formats may fail","No indication of support for forward citations (papers that cite a given paper) vs. backward citations","Unknown whether the system handles citation ambiguity (multiple papers with similar titles/authors)"],"requires":["Papers with standard citation formatting (IEEE, APA, Chicago, etc.)","Internet connection for citation resolution","No explicit citation manager integration available"],"input_types":["PDF documents with citations","Paper identifiers for citation lookup"],"output_types":["Citation lists with context","Citation network graphs","Citation relationship metadata"],"categories":["data-processing-analysis","academic-research"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_openread__cap_4","uri":"capability://data.processing.analysis.paper.metadata.extraction.and.structured.research.data.organization","name":"paper metadata extraction and structured research data organization","description":"Automatically extracts and structures metadata from academic papers including authors, publication date, venue, keywords, abstract, and research methodology, organizing this information in a queryable format. The system uses NLP and document structure parsing to identify metadata fields from paper headers and abstracts, creating structured records that enable filtering, sorting, and organization of research collections without manual data entry.","intents":["I want to organize papers I've found into a structured database with consistent metadata","I need to filter papers by publication year, venue, or author to narrow my literature review","I want to extract keywords and topics from papers to identify research trends"],"best_for":["Researchers building personal research databases or literature review collections","Teams managing shared research repositories requiring consistent metadata","Researchers analyzing publication patterns and trends in their field"],"limitations":["Metadata extraction accuracy varies with paper formatting; conference papers and preprints may have incomplete metadata","No built-in persistence or database backend — extracted metadata cannot be saved to personal research libraries","Limited integration with citation managers means metadata cannot be synced to Zotero, Mendeley, or similar tools","Unknown whether extracted keywords are from paper content or only from author-provided keywords"],"requires":["PDF documents with standard academic formatting","Internet connection for metadata processing","No local storage or database backend included"],"input_types":["PDF documents","Paper identifiers"],"output_types":["Structured metadata objects","Keyword lists","Author and venue information","Publication dates and citations counts"],"categories":["data-processing-analysis","academic-research"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_openread__cap_5","uri":"capability://data.processing.analysis.comparative.paper.analysis.and.research.methodology.comparison","name":"comparative paper analysis and research methodology comparison","description":"Analyzes multiple papers side-by-side to identify similarities and differences in research methodology, findings, and conclusions, enabling researchers to compare approaches across studies. The system likely uses NLP to extract methodology sections, results, and conclusions from multiple papers, then applies comparison algorithms to highlight methodological variations, conflicting findings, and complementary research approaches.","intents":["I want to compare how different researchers approached the same research question","I need to identify methodological variations across papers to understand best practices","I want to see if different papers reach conflicting conclusions and why"],"best_for":["Researchers conducting meta-analyses or systematic reviews comparing multiple studies","Students learning research methodology by comparing approaches across papers","Teams evaluating different technical approaches to solve similar problems"],"limitations":["Comparison quality depends on papers having clearly structured methodology sections","No indication of support for comparing more than 2-3 papers simultaneously","Unknown whether the system can identify subtle methodological differences vs. only obvious variations","Comparative analysis may miss domain-specific nuances that require expert interpretation"],"requires":["Multiple PDF documents for comparison","Papers with explicit methodology sections","Internet connection for analysis processing"],"input_types":["Multiple PDF documents","Paper identifiers for batch comparison"],"output_types":["Comparative analysis reports","Methodology comparison tables","Finding discrepancy summaries"],"categories":["data-processing-analysis","academic-research"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_openread__cap_6","uri":"capability://data.processing.analysis.research.trend.identification.and.topic.evolution.tracking","name":"research trend identification and topic evolution tracking","description":"Analyzes patterns across multiple papers to identify emerging research trends, track how research topics evolve over time, and highlight shifts in methodology or focus within a field. The system aggregates paper metadata, keywords, and publication dates to identify temporal patterns, topic clustering, and citation trends that reveal how research communities are moving and what areas are gaining or losing attention.","intents":["I want to identify emerging research trends in my field to stay ahead of the curve","I need to understand how a research topic has evolved over the past 5-10 years","I want to find research areas that are gaining momentum and attracting new researchers"],"best_for":["Researchers planning new research directions and seeking emerging topics","Graduate students identifying novel research gaps and opportunities","Research teams analyzing competitive landscape and research momentum"],"limitations":["Trend identification depends on the size and recency of indexed paper corpus","Unknown whether the system analyzes full paper text or only metadata and abstracts","No indication of temporal granularity (yearly, quarterly, monthly trends)","Trend analysis may be biased toward well-indexed venues and languages, missing emerging research communities"],"requires":["Access to OpenRead's indexed academic paper database","Papers spanning multiple years for temporal analysis","Internet connection for trend analysis processing"],"input_types":["Paper collections or search results","Topic or keyword queries"],"output_types":["Trend reports","Topic evolution timelines","Emerging research area summaries","Publication volume trends"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_openread__cap_7","uri":"capability://search.retrieval.personalized.research.recommendation.based.on.reading.history.and.interests","name":"personalized research recommendation based on reading history and interests","description":"Recommends relevant papers to researchers based on their reading history, saved papers, and explicitly stated research interests, using collaborative filtering or content-based recommendation algorithms. The system tracks which papers a user has read, summarized, or saved, then identifies similar papers in the database and surfaces recommendations that match the user's demonstrated research interests without requiring explicit topic specification.","intents":["I want to discover papers similar to ones I've already found relevant","I want OpenRead to suggest papers based on my research interests without manually searching","I want to get notified when new papers matching my interests are added to the database"],"best_for":["Researchers conducting ongoing literature reviews who want continuous discovery","Students exploring research areas and wanting guided paper discovery","Researchers with limited time who want passive recommendations"],"limitations":["Recommendation quality depends on sufficient reading history (cold-start problem for new users)","No indication of whether recommendations are personalized per user or generic","Unknown whether the system supports explicit interest specification or only implicit signals","No apparent notification system for new recommendations; users must manually check"],"requires":["User account with reading history","Multiple papers read or saved to establish preferences","Internet connection for recommendation processing"],"input_types":["User reading history","Saved papers","Explicit interest tags or topics"],"output_types":["Recommended paper lists","Relevance scores","Recommendation explanations"],"categories":["search-retrieval","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":39,"verified":false,"data_access_risk":"high","permissions":["PDF file upload capability (typical max 50MB)","Internet connection for cloud-based LLM inference","Browser with JavaScript enabled for UI interaction","Access to OpenRead's indexed academic paper database","Internet connection for query processing","Natural language query formulation ability","Papers or queries in supported languages","Internet connection for language detection and translation processing","No explicit language selection required (auto-detection)","Papers with standard citation formatting (IEEE, APA, Chicago, etc.)"],"failure_modes":["Summarization quality degrades on papers with non-standard formatting or scanned PDFs without OCR","Cannot capture nuanced theoretical arguments that require full contextual reading","Multi-language support may introduce translation artifacts that obscure technical terminology","Search quality depends on the size and diversity of the indexed paper corpus","Semantic search may return papers with high embedding similarity but low practical relevance","No apparent filtering by publication date, venue, or citation count to refine results","Unknown whether the search indexes full paper text or only abstracts/metadata","Translation quality varies significantly across language pairs; rare languages may have poor support","Technical terminology may be mistranslated, especially in specialized domains","No indication of which languages are supported or how many language pairs are covered","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.31666666666666665,"quality":0.67,"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":"2026-05-24T12:16:31.859Z","last_scraped_at":"2026-04-05T13:23:42.560Z","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=openread","compare_url":"https://unfragile.ai/compare?artifact=openread"}},"signature":"fOpgK0ShA/FWKBhbea6r7tnVIrSOE2rMH7gcR5ldsEO3ZjOjohiT4C7BgEW7UrzLrzaCjmnCpS9p4WRKFcxfDQ==","signedAt":"2026-06-23T00:54:29.485Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/openread","artifact":"https://unfragile.ai/openread","verify":"https://unfragile.ai/api/v1/verify?slug=openread","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"}}