{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"awesome-sourcely","slug":"sourcely","name":"Sourcely","type":"product","url":"https://www.sourcely.net/","page_url":"https://unfragile.ai/sourcely","categories":["research-search"],"tags":[],"pricing":{"model":"unknown","free":false,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"awesome-sourcely__cap_0","uri":"capability://search.retrieval.ai.powered.academic.source.discovery.from.text.queries","name":"ai-powered academic source discovery from text queries","description":"Accepts natural language queries or paper excerpts and uses semantic understanding to identify relevant academic sources. The system likely employs embedding-based retrieval against a curated academic database, matching query intent to citation metadata (authors, abstracts, keywords) rather than simple keyword matching. This enables finding sources even when exact terminology differs between the query and published papers.","intents":["Find peer-reviewed sources for a specific research claim without manual database searching","Discover citations relevant to a paragraph or research question automatically","Identify foundational papers in a field when I only have a rough research direction","Validate claims in my writing by finding supporting academic evidence"],"best_for":["Graduate students and researchers writing literature reviews","Academic writers needing rapid source validation","Non-specialists entering new research domains who lack domain-specific search vocabulary"],"limitations":["Likely limited to indexed academic databases (PubMed, arXiv, CrossRef, etc.) — may miss very recent preprints or niche journals","Semantic matching quality depends on embedding model training data — may struggle with highly specialized or emerging terminology","No guarantee of finding ALL relevant sources — recall depends on database coverage and query formulation"],"requires":["Internet connection to access academic databases","Text input (query, paragraph, or paper excerpt)","User account (pricing model unknown)"],"input_types":["natural language text query","paper excerpt or paragraph","research topic description"],"output_types":["structured citation list (likely BibTeX, APA, or similar formats)","ranked source results with metadata (title, authors, abstract, DOI)"],"categories":["search-retrieval","academic-research"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-sourcely__cap_1","uri":"capability://data.processing.analysis.batch.citation.extraction.and.formatting.from.document.text","name":"batch citation extraction and formatting from document text","description":"Processes uploaded documents or pasted text to automatically identify citation contexts, extract referenced sources, and format them into standard citation styles (APA, MLA, Chicago, Harvard, etc.). The system likely uses NLP-based entity recognition to detect author names, publication years, and citation patterns, then maps these to full bibliographic records from academic databases.","intents":["Convert informal citations in my draft to properly formatted bibliography entries","Extract all sources mentioned in a paper and generate a complete reference list","Automatically reformat citations when switching between citation styles mid-project","Identify missing or incomplete citation information in my manuscript"],"best_for":["Academic writers managing large documents with many citations","Students preparing final manuscripts with strict citation requirements","Researchers collaborating across institutions with different citation style requirements"],"limitations":["Citation extraction accuracy depends on text quality — OCR'd documents or poorly formatted text may produce errors","May fail to disambiguate author names or resolve incomplete citations without manual intervention","Formatting conversion is lossy for complex citation types (e.g., unpublished manuscripts, personal communications) that don't fit standard schemas"],"requires":["Document upload capability (PDF, DOCX, or plain text)","Access to citation formatting templates and academic metadata databases","User account with document storage"],"input_types":["PDF document","DOCX/Word document","plain text with embedded citations"],"output_types":["formatted bibliography in multiple styles (APA, MLA, Chicago, Harvard, IEEE, etc.)","structured citation data (JSON or CSV with metadata)","downloadable reference list"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-sourcely__cap_2","uri":"capability://search.retrieval.context.aware.source.recommendation.based.on.document.content","name":"context-aware source recommendation based on document content","description":"Analyzes the full text of a user's draft or research document and recommends relevant academic sources that should be cited. The system builds a semantic representation of the document's key concepts, research questions, and claims, then queries academic databases to surface papers that address similar topics or provide supporting evidence. This goes beyond simple keyword matching by understanding the document's research narrative.","intents":["Discover sources I should cite but haven't found yet based on my paper's content","Identify gaps in my literature review by finding related work I may have missed","Get suggestions for foundational papers in areas I'm discussing","Validate my research claims by finding supporting or contradicting evidence"],"best_for":["Researchers in early-to-mid stages of writing who want to strengthen their literature review","Interdisciplinary researchers who may lack comprehensive knowledge of all relevant subfields","Teams collaborating on large research projects needing comprehensive source coverage"],"limitations":["Recommendations are only as good as the underlying academic database — may miss sources from non-indexed journals or recent preprints","Cannot distinguish between sources that support vs. contradict your claims — requires human judgment to evaluate relevance","May recommend overly broad or tangentially related papers if document topic is interdisciplinary or novel"],"requires":["Full document text (minimum length likely required for meaningful analysis)","Access to academic database indexes","Semantic analysis model trained on academic literature"],"input_types":["full research document (PDF or text)","document excerpt or section","research abstract or outline"],"output_types":["ranked list of recommended sources with relevance scores","grouped recommendations by topic or research area","citation-ready metadata for recommended sources"],"categories":["search-retrieval","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-sourcely__cap_3","uri":"capability://data.processing.analysis.multi.format.document.upload.and.parsing.with.ocr.support","name":"multi-format document upload and parsing with ocr support","description":"Accepts documents in multiple formats (PDF, DOCX, images, scanned papers) and converts them to machine-readable text using OCR for scanned documents and native parsing for digital formats. The system likely uses a pipeline combining format-specific parsers (PDF extraction libraries, DOCX DOM parsing) with optical character recognition (Tesseract or cloud-based OCR) for image-based inputs, preserving document structure where possible.","intents":["Upload a scanned paper or PDF and automatically extract its text for citation analysis","Process multiple document formats without manual conversion","Extract citations from images or screenshots of papers","Preserve document structure (headings, sections) when processing for citation analysis"],"best_for":["Researchers working with legacy printed papers or scanned documents","Users managing mixed document collections in different formats","Teams needing to process bulk document uploads without preprocessing"],"limitations":["OCR accuracy degrades with poor image quality, non-English text, or complex layouts — may require manual correction","Scanned documents with handwritten annotations cannot be processed","Very large PDFs (1000+ pages) may timeout or require chunking","Document structure preservation is imperfect — complex layouts may lose formatting information"],"requires":["File upload interface with size limits (likely 10-100MB per file)","OCR engine (cloud-based or local)","PDF and DOCX parsing libraries","Sufficient server storage for temporary document processing"],"input_types":["PDF files","DOCX/Word documents","image files (PNG, JPG, TIFF)","scanned documents"],"output_types":["extracted plain text","structured document representation with sections/headings","confidence scores for OCR'd text","metadata (page count, language detected)"],"categories":["data-processing-analysis","image-visual"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-sourcely__cap_4","uri":"capability://data.processing.analysis.citation.style.conversion.and.template.based.formatting","name":"citation style conversion and template-based formatting","description":"Converts bibliographic data between multiple citation formats (APA, MLA, Chicago, Harvard, IEEE, Vancouver, etc.) using format-specific templates and rules. The system maintains a structured representation of citation metadata (authors, title, publication date, DOI, etc.) and applies format-specific rules for ordering, punctuation, and abbreviation. This enables users to switch citation styles without re-entering source information.","intents":["Change my entire bibliography from APA to Chicago style for journal submission","Generate citations in multiple formats from a single source record","Ensure consistent formatting across all citations in my document","Export citations in a specific format for use in other tools or documents"],"best_for":["Students and researchers switching between institutions or journals with different citation requirements","Interdisciplinary teams using different citation conventions","Authors preparing manuscripts for multiple journal submissions with varying style guides"],"limitations":["Some citation types (e.g., unpublished manuscripts, personal communications, software) don't map cleanly between all formats","Custom or non-standard citation formats cannot be generated without manual editing","Conversion may lose information for formats with fewer required fields (e.g., converting detailed Chicago to minimal IEEE)"],"requires":["Structured citation metadata (author, title, date, source, etc.)","Citation style templates for each supported format","Citation formatting rule engine"],"input_types":["structured citation data (JSON, BibTeX, RIS)","existing formatted citations (parsed and re-formatted)"],"output_types":["formatted citation strings in target style","complete bibliography in target format","BibTeX, RIS, or other structured export formats"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-sourcely__cap_5","uri":"capability://tool.use.integration.integration.with.academic.databases.and.metadata.apis","name":"integration with academic databases and metadata apis","description":"Connects to external academic databases (CrossRef, PubMed, arXiv, Google Scholar, etc.) and metadata APIs to enrich citation records with complete bibliographic information. When a user provides partial citation data (e.g., author and title), the system queries these APIs to fetch missing fields (DOI, publication date, abstract, journal name) and validate the source. This enables automatic completion of incomplete citations.","intents":["Automatically fill in missing citation details (DOI, publication date) from database lookups","Verify that a source I cited actually exists and get the correct bibliographic information","Enrich citations with abstracts or metadata for annotation purposes","Resolve ambiguous citations when multiple papers match the provided information"],"best_for":["Researchers working with incomplete or informal citations","Teams needing to validate citation accuracy before publication","Users wanting to enrich citations with additional metadata (abstracts, keywords)"],"limitations":["API rate limits may throttle bulk citation lookups — processing large batches may be slow","Not all sources are indexed in all databases — some citations may not resolve","API availability and uptime depend on external services — failures cascade to the application","Some databases (e.g., Google Scholar) have terms-of-service restrictions on automated access"],"requires":["API keys or authentication for academic databases (CrossRef, PubMed, etc.)","Network connectivity to external services","Caching layer to minimize API calls and improve performance","Fallback mechanisms for API failures"],"input_types":["partial citation data (author, title, year)","DOI or other persistent identifier","full citation string (parsed for metadata extraction)"],"output_types":["complete bibliographic record with all standard fields","enriched metadata (abstract, keywords, citation count)","validation status (found, ambiguous, not found)"],"categories":["tool-use-integration","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-sourcely__cap_6","uri":"capability://automation.workflow.collaborative.citation.management.with.shared.libraries","name":"collaborative citation management with shared libraries","description":"Enables multiple users to maintain shared citation libraries or projects, with real-time synchronization of added sources, annotations, and formatting changes. The system likely uses a centralized database with access control (read/write permissions per user or team) and change tracking to support collaborative workflows. Users can tag, annotate, and organize shared sources without conflicts.","intents":["Build a shared citation library with my research team without duplicating effort","Collaborate on a literature review where multiple people add and annotate sources","Maintain consistent citation formatting across a team project","Track who added each source and when for accountability"],"best_for":["Research teams and labs working on shared projects","Interdisciplinary collaborations requiring coordinated literature reviews","Large projects with multiple authors needing centralized source management"],"limitations":["Real-time sync may have latency — concurrent edits could cause conflicts if not handled carefully","Shared libraries require user account management and permission administration overhead","No built-in conflict resolution for simultaneous edits to the same citation","Audit trail and version history may not be available for all changes"],"requires":["User authentication and authorization system","Centralized database with concurrent access support","Real-time synchronization mechanism (WebSocket, polling, or similar)","Team/project management interface"],"input_types":["citations added by multiple users","annotations and tags","formatting preferences"],"output_types":["synchronized shared library view","change notifications and activity log","exported bibliography with contributor attribution"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-sourcely__cap_7","uri":"capability://planning.reasoning.ai.powered.citation.quality.assessment.and.gap.detection","name":"ai-powered citation quality assessment and gap detection","description":"Analyzes a user's citations against their document content to identify quality issues: missing citations for claims, outdated sources, over-reliance on single authors, lack of diversity in source types, and potential citation errors. The system uses NLP to match claims in the text to cited sources, detects when citations are missing or weak, and recommends improvements. This goes beyond simple formatting validation to assess citation adequacy.","intents":["Identify claims in my paper that lack proper citation support","Detect if I'm over-relying on a small set of sources or authors","Find outdated citations that should be supplemented with recent research","Ensure my citations represent diverse perspectives and source types"],"best_for":["Academic writers preparing manuscripts for peer review","Students learning proper citation practices and academic integrity","Researchers wanting to strengthen the evidence base for their claims"],"limitations":["Cannot distinguish between intentional and unintentional citation gaps — requires human judgment","May flag legitimate claims that don't require citations (e.g., common knowledge, methodology descriptions)","Assessment quality depends on NLP accuracy — may miss implicit claims or misinterpret context","No understanding of field-specific citation norms — may over-flag or under-flag issues depending on discipline"],"requires":["Full document text with embedded citations","NLP model trained on academic writing patterns","Citation-to-claim mapping algorithm","Citation metadata (publication date, source type, author diversity)"],"input_types":["full research document with citations","document section or chapter"],"output_types":["quality assessment report with issues flagged","specific recommendations for additional citations","citation diversity metrics (author count, publication date range, source types)"],"categories":["planning-reasoning","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":23,"verified":false,"data_access_risk":"high","permissions":["Internet connection to access academic databases","Text input (query, paragraph, or paper excerpt)","User account (pricing model unknown)","Document upload capability (PDF, DOCX, or plain text)","Access to citation formatting templates and academic metadata databases","User account with document storage","Full document text (minimum length likely required for meaningful analysis)","Access to academic database indexes","Semantic analysis model trained on academic literature","File upload interface with size limits (likely 10-100MB per file)"],"failure_modes":["Likely limited to indexed academic databases (PubMed, arXiv, CrossRef, etc.) — may miss very recent preprints or niche journals","Semantic matching quality depends on embedding model training data — may struggle with highly specialized or emerging terminology","No guarantee of finding ALL relevant sources — recall depends on database coverage and query formulation","Citation extraction accuracy depends on text quality — OCR'd documents or poorly formatted text may produce errors","May fail to disambiguate author names or resolve incomplete citations without manual intervention","Formatting conversion is lossy for complex citation types (e.g., unpublished manuscripts, personal communications) that don't fit standard schemas","Recommendations are only as good as the underlying academic database — may miss sources from non-indexed journals or recent preprints","Cannot distinguish between sources that support vs. contradict your claims — requires human judgment to evaluate relevance","May recommend overly broad or tangentially related papers if document topic is interdisciplinary or novel","OCR accuracy degrades with poor image quality, non-English text, or complex layouts — may require manual correction","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.26,"ecosystem":0.25,"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":"2026-06-17T09:51:04.049Z","last_scraped_at":"2026-05-03T14:00:23.056Z","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=sourcely","compare_url":"https://unfragile.ai/compare?artifact=sourcely"}},"signature":"sKQe+ekL2b+Um1XFIVrdLDGo3zHOnMo1V88oXjojgXAcxn+7HZAlRL9/kaBULfS0zpHGfhxGuSJh6KRbXqXgCQ==","signedAt":"2026-06-20T01:03:21.377Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/sourcely","artifact":"https://unfragile.ai/sourcely","verify":"https://unfragile.ai/api/v1/verify?slug=sourcely","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"}}