{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_ai-plagiarism-checker","slug":"ai-plagiarism-checker","name":"AI Plagiarism Checker","type":"product","url":"https://plagiarismcheck.org","page_url":"https://unfragile.ai/ai-plagiarism-checker","categories":["text-writing"],"tags":[],"pricing":{"model":"paid","free":false,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_ai-plagiarism-checker__cap_0","uri":"capability://safety.moderation.traditional.plagiarism.detection.via.text.fingerprinting.and.database.matching","name":"traditional plagiarism detection via text fingerprinting and database matching","description":"Scans submitted text against a proprietary database of academic papers, published content, and web sources using fingerprinting algorithms (likely rolling hash or shingle-based matching) to identify structurally similar passages. The system compares n-gram patterns and semantic tokens to flag potential plagiarism with similarity percentages, enabling educators to pinpoint exact source matches and citation gaps without manual review.","intents":["Verify whether student submissions contain unattributed copied text from existing sources","Identify specific plagiarized passages and their original sources for citation correction","Generate similarity reports showing percentage of matched content for academic integrity enforcement"],"best_for":["Academic institutions processing bulk student submissions","Educators needing quick plagiarism screening before grading","Content agencies verifying freelancer originality"],"limitations":["Database coverage limited to indexed sources—obscure or paywalled content may not be detected","Fingerprinting approach struggles with heavily paraphrased content that preserves meaning but changes structure","False positives on common phrases, citations, and legitimate quoted material require manual review","Latency scales with document length and database size—large batch submissions may queue"],"requires":["Plain text or document upload (PDF, DOCX, TXT support assumed)","Internet connectivity for real-time database queries","User account with submission quota or credits"],"input_types":["text","document (PDF, DOCX, TXT)"],"output_types":["similarity report (percentage match)","source citations with URLs","highlighted passages (matched text)"],"categories":["safety-moderation","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_ai-plagiarism-checker__cap_1","uri":"capability://safety.moderation.chatgpt.and.ai.generated.content.detection.via.statistical.language.model.analysis","name":"chatgpt and ai-generated content detection via statistical language model analysis","description":"Analyzes submitted text using machine learning classifiers trained to identify statistical signatures of AI-generated content (e.g., perplexity scores, burstiness metrics, entropy patterns, and token probability distributions characteristic of LLM outputs). The detector compares input text against baseline human writing patterns and known AI model outputs to flag likely AI-generated passages with confidence scores, addressing the emerging need to distinguish human-authored from machine-generated content.","intents":["Detect whether student essays or professional submissions were written by ChatGPT, GPT-4, or similar LLMs","Identify mixed submissions containing both human and AI-generated content with section-level granularity","Generate confidence scores for AI detection to support academic integrity policies and hiring decisions"],"best_for":["Educators enforcing AI use policies in academic settings","Content agencies verifying human authorship for client deliverables","Employers screening resumes and cover letters for authenticity"],"limitations":["AI detection accuracy remains unreliable—false positive rates (flagging human text as AI) and false negatives (missing sophisticated AI outputs) are industry-wide challenges","Adversarial robustness unclear—heavily edited or paraphrased AI text may evade detection","Model drift: as LLMs improve and evolve, detection classifiers require continuous retraining to remain effective","No transparency on which AI models the detector was trained against—may miss emerging models like Claude or Llama","Short text samples (<100 words) produce unreliable confidence scores due to insufficient statistical signal"],"requires":["Plain text input (minimum ~200 words recommended for reliable detection)","Internet connectivity for model inference","User acceptance of inherent uncertainty in AI detection results"],"input_types":["text"],"output_types":["AI detection confidence score (0-100%)","section-level flagging (which paragraphs appear AI-generated)","explanation of detected patterns"],"categories":["safety-moderation","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_ai-plagiarism-checker__cap_2","uri":"capability://automation.workflow.batch.document.submission.and.queuing.with.similarity.report.aggregation","name":"batch document submission and queuing with similarity report aggregation","description":"Accepts bulk uploads of multiple documents (student assignments, freelancer submissions, content batches) and processes them through a job queue system, returning aggregated similarity reports for each document with side-by-side comparison of plagiarism and AI detection results. The system likely uses asynchronous processing to handle large batches without blocking, storing results in a user dashboard for historical review and export.","intents":["Submit 50+ student essays at once and receive plagiarism + AI detection reports for all without manual per-file submission","Compare plagiarism and AI detection results across a cohort to identify patterns or outliers","Export batch results as CSV or PDF for institutional records and compliance documentation"],"best_for":["Educators grading large classes (100+ students)","Academic institutions processing semester-wide submissions","Content agencies auditing multiple freelancer deliverables"],"limitations":["Batch processing latency depends on queue depth and system load—peak times may introduce delays","No real-time streaming results—users must wait for batch completion before viewing any reports","Storage limits on batch size and total document volume unclear—may require tiered pricing for large institutions","Export formats limited to common options (CSV, PDF)—no API for programmatic result retrieval"],"requires":["User account with batch submission permissions","Supported document formats (PDF, DOCX, TXT)","Sufficient account credits or subscription tier for batch volume"],"input_types":["document (PDF, DOCX, TXT)","text"],"output_types":["batch report (aggregated similarity scores)","per-document reports (plagiarism + AI detection)","export (CSV, PDF)"],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_ai-plagiarism-checker__cap_3","uri":"capability://data.processing.analysis.similarity.percentage.scoring.with.source.attribution.and.citation.mapping","name":"similarity percentage scoring with source attribution and citation mapping","description":"Calculates a composite similarity score (0-100%) representing the proportion of submitted text matching known sources, with granular breakdowns by source type (academic papers, web pages, published books, student submissions). The system maps matched passages to their original sources with URLs and citation metadata, enabling educators to quickly assess whether plagiarism is accidental (missing citations) or intentional (unattributed copying), and to generate corrected citations.","intents":["Determine overall plagiarism risk with a single percentage score for quick pass/fail decisions","Identify which sources a student copied from and generate proper citations for missing attributions","Distinguish between accidental plagiarism (paraphrasing without citation) and intentional copying (verbatim text)"],"best_for":["Educators making rapid plagiarism judgments during grading","Students self-checking submissions before final submission","Academic integrity officers documenting plagiarism cases"],"limitations":["Similarity score is a blunt metric—high scores may reflect legitimate citations, common knowledge, or paraphrasing rather than plagiarism","Source attribution depends on database coverage—obscure or paywalled sources may not be identified","Citation mapping assumes standard citation formats—non-standard or multilingual citations may not be recognized","No distinction between intentional plagiarism and accidental paraphrasing—requires human judgment"],"requires":["Submitted text in supported format","Access to source database (requires active subscription)"],"input_types":["text","document"],"output_types":["similarity percentage (0-100%)","source list with URLs and match percentages","citation suggestions (APA, MLA, Chicago formats assumed)"],"categories":["data-processing-analysis","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_ai-plagiarism-checker__cap_4","uri":"capability://automation.workflow.user.dashboard.with.submission.history.report.storage.and.access.controls","name":"user dashboard with submission history, report storage, and access controls","description":"Provides a web-based dashboard where users can view all past submissions, access stored plagiarism and AI detection reports, manage account settings, and control permissions for institutional users (e.g., allowing instructors to view student submissions but not vice versa). The system likely uses role-based access control (RBAC) to enforce institutional policies and stores reports in a queryable database for historical audit trails.","intents":["Review plagiarism and AI detection reports for past submissions without re-uploading documents","Compare results across multiple submissions to track student progress or identify repeat offenders","Grant institutional access to multiple instructors while restricting student visibility to their own reports"],"best_for":["Educators managing multiple classes and semesters of submissions","Academic institutions with multi-user accounts and role hierarchies","Content agencies tracking freelancer submission history"],"limitations":["Report retention period unclear—may have automatic deletion policies for old submissions","No API access to reports—all retrieval must be manual via web interface","Role-based access control granularity unknown—may not support fine-grained permissions (e.g., per-assignment access)","Dashboard performance may degrade with large submission histories (1000+ reports)"],"requires":["User account with login credentials","Web browser with JavaScript enabled","Institutional account setup for multi-user access"],"input_types":[],"output_types":["report list (metadata: date, similarity score, AI detection score)","detailed reports (plagiarism + AI detection results)","export (PDF, CSV)"],"categories":["automation-workflow","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_ai-plagiarism-checker__cap_5","uri":"capability://safety.moderation.ai.generated.content.confidence.scoring.with.pattern.explanation","name":"ai-generated content confidence scoring with pattern explanation","description":"Beyond binary AI/human classification, the detector produces a confidence score (0-100%) indicating the likelihood that text was generated by an LLM, along with explanatory patterns (e.g., 'unusually consistent sentence length', 'low perplexity', 'high token probability') that justify the score. This enables users to understand WHY text is flagged as AI-generated and to make informed decisions rather than relying on opaque scores.","intents":["Understand which linguistic patterns triggered AI detection flags for a submission","Distinguish between high-confidence AI detection (e.g., 95% likely ChatGPT) and borderline cases (e.g., 55% likely AI)","Educate students on how LLM outputs differ from human writing by showing specific detected patterns"],"best_for":["Educators using AI detection as a teaching tool to explain LLM characteristics","Academic integrity officers documenting plagiarism cases with explainable evidence","Researchers studying AI detection methodology and false positive rates"],"limitations":["Pattern explanations may be misleading—some 'AI patterns' (e.g., consistent sentence length) can occur in human writing","Confidence scores lack calibration—a 75% score may not correspond to 75% actual probability of AI generation","No explanation for why certain patterns are weighted more heavily in the final score","Explainability adds computational overhead—may increase latency per submission"],"requires":["Text input (minimum ~200 words for reliable pattern detection)","User understanding that confidence scores are probabilistic, not definitive"],"input_types":["text"],"output_types":["confidence score (0-100%)","detected patterns (list with descriptions)","pattern weights or importance scores (if provided)"],"categories":["safety-moderation","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":39,"verified":false,"data_access_risk":"high","permissions":["Plain text or document upload (PDF, DOCX, TXT support assumed)","Internet connectivity for real-time database queries","User account with submission quota or credits","Plain text input (minimum ~200 words recommended for reliable detection)","Internet connectivity for model inference","User acceptance of inherent uncertainty in AI detection results","User account with batch submission permissions","Supported document formats (PDF, DOCX, TXT)","Sufficient account credits or subscription tier for batch volume","Submitted text in supported format"],"failure_modes":["Database coverage limited to indexed sources—obscure or paywalled content may not be detected","Fingerprinting approach struggles with heavily paraphrased content that preserves meaning but changes structure","False positives on common phrases, citations, and legitimate quoted material require manual review","Latency scales with document length and database size—large batch submissions may queue","AI detection accuracy remains unreliable—false positive rates (flagging human text as AI) and false negatives (missing sophisticated AI outputs) are industry-wide challenges","Adversarial robustness unclear—heavily edited or paraphrased AI text may evade detection","Model drift: as LLMs improve and evolve, detection classifiers require continuous retraining to remain effective","No transparency on which AI models the detector was trained against—may miss emerging models like Claude or Llama","Short text samples (<100 words) produce unreliable confidence scores due to insufficient statistical signal","Batch processing latency depends on queue depth and system load—peak times may introduce delays","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":"2026-05-24T12:16:29.132Z","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=ai-plagiarism-checker","compare_url":"https://unfragile.ai/compare?artifact=ai-plagiarism-checker"}},"signature":"/IKGna7SdfZJ3DfY5AdszggN1IZFct5Ki6hyP2WvVbVmPwjh/zveQT4cvk8nCV0qzrApbGmq/szmAlXuh501Cg==","signedAt":"2026-06-21T18:32:18.345Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/ai-plagiarism-checker","artifact":"https://unfragile.ai/ai-plagiarism-checker","verify":"https://unfragile.ai/api/v1/verify?slug=ai-plagiarism-checker","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"}}