{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_paperguide","slug":"paperguide","name":"Paperguide","type":"product","url":"https://paperguide.ai","page_url":"https://unfragile.ai/paperguide","categories":["research-search"],"tags":[],"pricing":{"model":"freemium","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_paperguide__cap_0","uri":"capability://search.retrieval.semantic.paper.discovery.with.ai.ranking","name":"semantic-paper-discovery-with-ai-ranking","description":"Searches academic databases and preprint servers using semantic embeddings to surface relevant papers, then re-ranks results using LLM-based relevance scoring that understands research context and user intent. The system likely embeds paper metadata (title, abstract, keywords) into a vector space and performs similarity search, then applies a learned ranking model to prioritize papers matching the researcher's specific subdomain or methodology interests rather than simple keyword matching.","intents":["Find papers related to my research topic without manually sifting through hundreds of irrelevant results","Discover papers I wouldn't find with traditional keyword search because they use different terminology","Get ranked results that prioritize methodological fit and citation impact, not just keyword overlap"],"best_for":["Graduate students conducting broad literature reviews across interdisciplinary topics","Early-career researchers exploring new research directions without deep domain expertise"],"limitations":["Semantic search quality degrades for highly specialized subfields with limited training data","Re-ranking latency adds 2-5 seconds per query due to LLM inference","Free tier likely limits queries to 10-20 per day, creating friction during intensive literature review sessions","Cannot access paywalled papers behind institutional subscriptions without direct library integration"],"requires":["Internet connectivity to access external paper databases","API credentials for academic database access (likely PubMed, arXiv, or Semantic Scholar)","Active Paperguide account (free or paid)"],"input_types":["natural language query (e.g., 'transformer architectures for time series forecasting')","paper DOI or title for similarity-based discovery"],"output_types":["ranked list of papers with metadata (title, authors, abstract, publication date)","relevance scores or confidence metrics","direct links to paper PDFs or abstracts"],"categories":["search-retrieval","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_paperguide__cap_1","uri":"capability://text.generation.language.ai.powered.paper.summarization.with.key.extraction","name":"ai-powered-paper-summarization-with-key-extraction","description":"Processes uploaded or linked PDF papers through an LLM pipeline that generates abstractive summaries at multiple granularity levels (1-sentence, paragraph, full summary) and extracts structured key insights including methodology, findings, and limitations. The system likely uses prompt engineering or fine-tuned models to identify domain-relevant information patterns and present them in a standardized format that researchers can quickly scan without reading the full paper.","intents":["Quickly understand a paper's core contribution without reading 20+ pages","Extract methodology and key findings for comparison across multiple papers","Identify papers' limitations and gaps to inform my own research direction"],"best_for":["Researchers conducting rapid literature reviews with 50+ papers to evaluate","Students building research proposals who need to synthesize findings across multiple sources"],"limitations":["Summarization quality degrades for papers with non-standard structure (e.g., technical reports, theses) or dense mathematical notation","LLM hallucination risk: summaries may misrepresent findings or conflate results from different sections","Free tier likely limits summaries to 5-10 papers/month, forcing paid upgrade for serious researchers","No support for multi-language papers or papers with embedded figures/tables as primary content","Latency of 10-30 seconds per paper due to LLM processing"],"requires":["PDF upload capability or URL link to paper (arXiv, DOI resolver, or direct PDF)","Active Paperguide account with document upload quota","Papers in English with extractable text (not scanned images)"],"input_types":["PDF file (uploaded or linked via URL)","paper metadata (title, abstract) for context"],"output_types":["multi-level summaries (1-sentence, paragraph, full)","structured key insights (methodology, findings, limitations, future work)","highlighted quotes or key sentences from original paper"],"categories":["text-generation-language","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_paperguide__cap_2","uri":"capability://data.processing.analysis.unified.citation.management.with.auto.formatting","name":"unified-citation-management-with-auto-formatting","description":"Maintains a personal library of papers with automatic metadata extraction (authors, publication date, DOI, journal) and generates citations in multiple formats (APA, MLA, Chicago, IEEE) on demand. The system likely stores paper metadata in a structured database and uses citation formatting libraries or templates to produce correctly-formatted citations without manual entry, reducing the friction of citation management compared to manual BibTeX editing.","intents":["Automatically capture paper metadata without manual typing of author names and publication details","Generate citations in the format required by my target journal or institution","Maintain a searchable library of papers I've read with notes and highlights"],"best_for":["Students writing thesis chapters or journal submissions with strict citation requirements","Researchers managing 100+ papers across multiple projects with different citation styles"],"limitations":["Limited integration with institutional library systems (Mendeley, Zotero) means manual import/export workflows","Metadata extraction from PDFs is imperfect for papers with non-standard formatting, requiring manual correction","Free tier likely restricts library size to 50-100 papers, forcing paid upgrade for serious researchers","No support for custom citation styles or CSL (Citation Style Language) extensions","Lacks collaborative features for shared libraries or group projects"],"requires":["Paper metadata (extracted from PDF or manually entered)","Target citation format specification (APA, MLA, Chicago, IEEE, etc.)","Active Paperguide account with library storage quota"],"input_types":["PDF file with extractable metadata","manual metadata entry (authors, title, journal, year)","DOI or ISBN for automatic metadata lookup"],"output_types":["formatted citations in multiple styles (APA, MLA, Chicago, IEEE)","BibTeX or RIS export for use in LaTeX or other tools","searchable library with metadata and notes"],"categories":["data-processing-analysis","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_paperguide__cap_3","uri":"capability://text.generation.language.ai.assisted.research.writing.with.context.awareness","name":"ai-assisted-research-writing-with-context-awareness","description":"Provides writing assistance for research papers by suggesting text completions, rephrasing, and structural improvements based on the papers in the user's library and the current draft context. The system likely uses retrieval-augmented generation (RAG) to fetch relevant papers from the user's library, then conditions the LLM on both the draft text and retrieved paper content to generate contextually appropriate suggestions that align with the research narrative.","intents":["Get writing suggestions that are grounded in my research papers, not generic advice","Rephrase sentences to improve clarity while maintaining technical accuracy","Receive structural suggestions for organizing findings and related work sections"],"best_for":["Non-native English speakers writing research papers who need grammar and clarity assistance","Researchers struggling with paper organization and narrative flow"],"limitations":["Writing suggestions lack domain-specific intelligence for technical fields (e.g., statistical methods, experimental design)","RAG retrieval may surface irrelevant papers if library is poorly organized or papers lack good metadata","LLM-generated suggestions may introduce subtle errors or misrepresent findings from source papers","Free tier likely limits suggestions to 20-50 per day, creating friction during intensive writing sessions","No support for collaborative writing or real-time feedback from co-authors","Latency of 3-5 seconds per suggestion due to RAG + LLM inference"],"requires":["Active Paperguide account with populated paper library","Draft text in the editor (plain text or markdown)","Papers in library with extractable text for RAG retrieval"],"input_types":["draft text or sentence to be improved","context about paper topic or research question"],"output_types":["suggested text completions or rephrasing","structural suggestions for paper organization","citations to relevant papers in the user's library"],"categories":["text-generation-language","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_paperguide__cap_4","uri":"capability://text.generation.language.cross.paper.insight.synthesis.with.comparison","name":"cross-paper-insight-synthesis-with-comparison","description":"Analyzes multiple papers in the user's library to identify common themes, contradictions, and methodological patterns, then generates a synthesis document that compares findings across papers. The system likely uses clustering or topic modeling to group papers by theme, then applies LLM-based analysis to identify relationships and generate comparative insights that would normally require manual reading and note-taking.","intents":["Understand how different papers approach the same research problem and what methodologies they use","Identify contradictions or gaps in the literature that my research could address","Generate a literature review section that synthesizes findings across 20+ papers"],"best_for":["Researchers writing literature review sections or research proposals","Students conducting comprehensive surveys of a research topic"],"limitations":["Synthesis quality depends heavily on library size and metadata quality; small or poorly-organized libraries produce shallow insights","LLM may miss nuanced contradictions or overstate consensus where papers actually disagree","Latency of 30-60 seconds for analyzing 20+ papers due to batch LLM processing","Free tier likely limits synthesis to 1-2 per month, forcing paid upgrade for iterative refinement","No support for domain-specific comparison frameworks (e.g., experimental design, statistical methods)"],"requires":["Active Paperguide account with 10+ papers in library","Papers with extractable text and good metadata for clustering","Specification of comparison criteria or research question"],"input_types":["subset of papers from user's library","research question or comparison criteria"],"output_types":["synthesis document comparing findings across papers","thematic clusters or topic groupings","identified contradictions or gaps in literature","structured comparison table (methodology, findings, limitations)"],"categories":["text-generation-language","data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_paperguide__cap_5","uri":"capability://memory.knowledge.research.project.organization.with.tagging","name":"research-project-organization-with-tagging","description":"Provides a project-based organizational structure where users can group papers, notes, and drafts by research project, with automatic tagging based on paper content and manual tag creation. The system likely uses document clustering or LLM-based tagging to automatically assign papers to projects and generate tags based on abstract/title content, reducing manual organization overhead while allowing users to customize tags for their specific research taxonomy.","intents":["Organize papers and notes by research project without manually creating folders and moving files","Automatically tag papers with relevant topics so I can find them later without remembering exact titles","Switch between multiple research projects without losing context or mixing up papers"],"best_for":["Researchers managing 3+ concurrent research projects with overlapping topics","Students juggling multiple courses or thesis chapters with shared literature"],"limitations":["Automatic tagging may be inaccurate for papers with ambiguous abstracts or interdisciplinary content","Free tier likely limits projects to 2-3, forcing paid upgrade for researchers with many concurrent projects","No support for hierarchical tags or custom taxonomies beyond simple flat tag lists","Limited search across projects; users must switch project context to find papers","No collaborative project features for shared research with advisors or lab members"],"requires":["Active Paperguide account","Papers with extractable metadata (title, abstract) for automatic tagging"],"input_types":["paper metadata (title, abstract, keywords)","manual project creation and tag assignment"],"output_types":["organized project structure with papers and notes","auto-generated tags based on paper content","project-scoped search results"],"categories":["memory-knowledge","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_paperguide__cap_6","uri":"capability://text.generation.language.pdf.annotation.and.highlighting.with.ai.notes","name":"pdf-annotation-and-highlighting-with-ai-notes","description":"Allows users to highlight text in PDFs and attach notes, with AI-powered suggestions for note content based on the highlighted text and surrounding context. The system likely uses NLP to identify key concepts in highlighted passages and suggests note templates or summary points that users can accept, edit, or discard, reducing the friction of manual note-taking while maintaining user control.","intents":["Quickly capture key insights from papers without manually typing detailed notes","Get AI-suggested summaries of highlighted passages that I can refine or reject","Search across all my highlights and notes to find relevant passages for my draft"],"best_for":["Students reading 20+ papers per week who need fast note-taking","Researchers building literature review notes with consistent structure"],"limitations":["AI note suggestions may misinterpret technical content or miss nuanced insights","Free tier likely limits highlights/notes to 100-200 per month, creating friction during intensive reading","No support for collaborative annotations or shared highlights with lab members","Highlighting only works on PDFs uploaded to Paperguide; cannot sync with external PDF readers (Adobe, Zotero)","Search across highlights is limited to simple keyword matching, not semantic search"],"requires":["PDF uploaded to Paperguide with extractable text","Active Paperguide account with annotation quota"],"input_types":["highlighted text passages from PDF","surrounding context (paragraph or page)"],"output_types":["AI-suggested notes or summaries","searchable highlight and note library","export of highlights and notes in markdown or text format"],"categories":["text-generation-language","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_paperguide__cap_7","uri":"capability://planning.reasoning.research.question.refinement.with.gap.analysis","name":"research-question-refinement-with-gap-analysis","description":"Analyzes papers in the user's library to identify research gaps and suggests refinements to the user's research question based on what's already been studied. The system likely uses topic modeling and LLM analysis to identify underexplored areas within the user's research domain, then generates suggestions for narrowing or broadening the research question to address identified gaps.","intents":["Identify gaps in the literature that my research could address","Refine my research question to be more specific and novel based on existing work","Understand what methodologies have been used and what approaches are missing"],"best_for":["PhD students formulating dissertation research questions","Researchers planning new projects who want to ensure novelty"],"limitations":["Gap analysis quality depends on library comprehensiveness; incomplete libraries may miss important work","LLM suggestions may overstate novelty or miss subtle differences from existing work","Free tier likely limits gap analysis to 1-2 per month, forcing paid upgrade for iterative refinement","No support for domain-specific gap analysis frameworks (e.g., methodological gaps vs. empirical gaps)","Latency of 30-60 seconds for analyzing library and generating suggestions"],"requires":["Active Paperguide account with 20+ papers in library","Initial research question or topic description","Papers with extractable text and good metadata"],"input_types":["research question or topic description","subset of papers from user's library"],"output_types":["identified research gaps and underexplored areas","suggested refinements to research question","papers addressing similar questions with different approaches"],"categories":["planning-reasoning","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":39,"verified":false,"data_access_risk":"high","permissions":["Internet connectivity to access external paper databases","API credentials for academic database access (likely PubMed, arXiv, or Semantic Scholar)","Active Paperguide account (free or paid)","PDF upload capability or URL link to paper (arXiv, DOI resolver, or direct PDF)","Active Paperguide account with document upload quota","Papers in English with extractable text (not scanned images)","Paper metadata (extracted from PDF or manually entered)","Target citation format specification (APA, MLA, Chicago, IEEE, etc.)","Active Paperguide account with library storage quota","Active Paperguide account with populated paper library"],"failure_modes":["Semantic search quality degrades for highly specialized subfields with limited training data","Re-ranking latency adds 2-5 seconds per query due to LLM inference","Free tier likely limits queries to 10-20 per day, creating friction during intensive literature review sessions","Cannot access paywalled papers behind institutional subscriptions without direct library integration","Summarization quality degrades for papers with non-standard structure (e.g., technical reports, theses) or dense mathematical notation","LLM hallucination risk: summaries may misrepresent findings or conflate results from different sections","Free tier likely limits summaries to 5-10 papers/month, forcing paid upgrade for serious researchers","No support for multi-language papers or papers with embedded figures/tables as primary content","Latency of 10-30 seconds per paper due to LLM processing","Limited integration with institutional library systems (Mendeley, Zotero) means manual import/export workflows","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":"2026-05-24T12:16:32.437Z","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=paperguide","compare_url":"https://unfragile.ai/compare?artifact=paperguide"}},"signature":"5jSww/tHOh1pV1uwSPBibOX9nRt4XsJMrV8DTfRAItNQcmCXCQQUeX3sQh9KM0hGEBKM9w4mt34zTylvHEXVBg==","signedAt":"2026-06-22T00:30:32.612Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/paperguide","artifact":"https://unfragile.ai/paperguide","verify":"https://unfragile.ai/api/v1/verify?slug=paperguide","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"}}