[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"extension-skill-PaddlePaddle-paddleocr-doc-parsing-en":3,"guides-for-PaddlePaddle-paddleocr-doc-parsing":372,"similar-k17f6kj5nsqfvjy2vj7tyj9kz186mpgh-en":373},{"_creationTime":4,"_id":5,"children":6,"community":7,"display":9,"evaluation":15,"identity":261,"isFallback":252,"parentExtension":267,"providers":268,"relations":273,"repo":275,"tags":368,"workflow":369},1778695189192.8508,"k17f6kj5nsqfvjy2vj7tyj9kz186mpgh",[],{"reviewCount":8},0,{"description":10,"installMethods":11,"name":13,"sourceUrl":14},"Use this skill to extract structured Markdown/JSON from PDFs and document images—tables with cell-level precision, formulas as LaTeX, figures, seals, charts, headers/footers, multi-column layout and correct reading order. Trigger terms: 文档解析, 版面分析, 版面还原, 表格提取, 公式识别, 多栏排版, 扫描件结构化, 发票, 财报, 复杂 PDF, PDF转Markdown, 图表, 阅读顺序; reading order, formula, LaTeX, layout parsing, structure extraction, PP-StructureV3, PaddleOCR-VL.",{"claudeCode":12},"PaddlePaddle/PaddleOCR","PaddleOCR Document Parsing","https://github.com/PaddlePaddle/PaddleOCR",{"_creationTime":16,"_id":17,"extensionId":5,"locale":18,"result":19,"trustSignals":242,"workflow":259},1778695207150.469,"kn7aahe5q8depngyf2er42chx186n86g","en",{"checks":20,"evaluatedAt":195,"extensionSummary":196,"features":197,"nonGoals":203,"practices":207,"prerequisites":208,"promptVersionExtension":214,"promptVersionScoring":215,"purpose":216,"rationale":217,"score":218,"summary":219,"tags":220,"targetMarket":229,"tier":230,"useCases":231,"workflow":236},[21,26,29,32,36,39,44,48,51,54,58,62,65,69,72,75,78,81,84,87,91,95,99,103,107,110,114,117,121,124,127,130,133,136,139,143,147,150,153,157,160,163,166,169,173,176,179,182,185,188,192],{"category":22,"check":23,"severity":24,"summary":25},"Practical Utility","Problem relevance","pass","The description clearly states the problem of extracting structured data from PDFs and document images, highlighting specific elements like tables, formulas, and layout.",{"category":22,"check":27,"severity":24,"summary":28},"Unique selling proposition","The skill leverages advanced models like PaddleOCR-VL and PP-StructureV3 for high-accuracy document parsing, offering capabilities beyond basic OCR and distinguishing it from simple wrappers.",{"category":22,"check":30,"severity":24,"summary":31},"Production readiness","The skill provides a complete workflow from input handling to structured output, including error handling and guidance for large files, making it ready for production use.",{"category":33,"check":34,"severity":24,"summary":35},"Scope","Single responsibility principle","The skill is focused on document parsing from PDFs and images, with a clear scope that does not extend into unrelated domains.",{"category":33,"check":37,"severity":24,"summary":38},"Description quality","The description accurately reflects the skill's capabilities for extracting structured data from PDFs and images, including specific elements and trigger terms.",{"category":40,"check":41,"severity":42,"summary":43},"Invocation","Scoped tools","not_applicable","This is a skill, not a tool-based extension, and therefore does not have scoped tools in the traditional sense.",{"category":45,"check":46,"severity":24,"summary":47},"Documentation","Configuration & parameter reference","The SKILL.md documentation clearly outlines environment variables for API configuration and optional parameters like file type, with their purposes explained.",{"category":33,"check":49,"severity":42,"summary":50},"Tool naming","This is a skill, not a tool-based extension, and therefore does not have traditional tool names.",{"category":33,"check":52,"severity":24,"summary":53},"Minimal I/O surface","The CLI interface and script parameters are well-defined, accepting specific inputs like file paths/URLs and optional parameters, and the output is structured JSON.",{"category":55,"check":56,"severity":24,"summary":57},"License","License usability","The license is Apache-2.0, clearly stated in the LICENSE file and SKILL.md, which is a permissive open-source license.",{"category":59,"check":60,"severity":24,"summary":61},"Maintenance","Commit recency","The repository shows recent commits as of 2026-05-13, indicating active maintenance.",{"category":59,"check":63,"severity":24,"summary":64},"Dependency Management","The project uses uv for dependency management, ensuring dependencies are resolved and managed effectively.",{"category":66,"check":67,"severity":24,"summary":68},"Security","Secret Management","Secrets are handled via environment variables (PADDLEOCR_ACCESS_TOKEN), not hardcoded, and the skill guides users on secure configuration.",{"category":66,"check":70,"severity":24,"summary":71},"Injection","The script processes file paths and URLs as data inputs, and there's no indication of executing instructions from loaded third-party data.",{"category":66,"check":73,"severity":24,"summary":74},"Transitive Supply-Chain Grenades","Dependencies are managed via uv, and the code does not appear to fetch external code or data at runtime for execution.",{"category":66,"check":76,"severity":24,"summary":77},"Sandbox Isolation","The script operates on provided file paths and URLs, and does not appear to modify files outside its designated output location or scope.",{"category":66,"check":79,"severity":24,"summary":80},"Sandbox escape primitives","The script does not appear to contain patterns like detached processes or retry loops around denied operations.",{"category":66,"check":82,"severity":24,"summary":83},"Data Exfiltration","The skill handles API calls with credentials via environment variables and does not exhibit patterns of reading or submitting confidential data to undocumented third parties.",{"category":66,"check":85,"severity":24,"summary":86},"Hidden Text Tricks","Bundled files appear to be free of hidden text tricks or malicious Unicode characters; descriptions are clean.",{"category":88,"check":89,"severity":24,"summary":90},"Hooks","Opaque code execution","The Python scripts are written in clear, readable code without obfuscation techniques like base64 encoding or eval.",{"category":92,"check":93,"severity":24,"summary":94},"Portability","Structural Assumption","The scripts handle file paths and URLs as inputs and do not make assumptions about user-specific project organization outside of the provided inputs.",{"category":96,"check":97,"severity":24,"summary":98},"Trust","Issues Attention","With 58 open and 60 closed issues in the last 90 days, the closure rate is high, indicating active maintainer engagement.",{"category":100,"check":101,"severity":24,"summary":102},"Versioning","Release Management","The project has a clear versioning strategy with frequent releases and updates, as indicated by recent commit dates and changelog entries.",{"category":104,"check":105,"severity":24,"summary":106},"Execution","Validation","Input parameters like file paths, URLs, and types are validated by the script's argument parsing and internal logic before being passed to the library.",{"category":66,"check":108,"severity":24,"summary":109},"Unguarded Destructive Operations","The skill is primarily read-only in its operation, focusing on parsing and extraction, and does not perform destructive operations.",{"category":111,"check":112,"severity":24,"summary":113},"Code Execution","Error Handling","The `lib.py` module consistently returns structured error dictionaries with codes and messages, and the CLI script handles these errors gracefully.",{"category":111,"check":115,"severity":24,"summary":116},"Logging","The script uses Python's logging module for internal operations, and user-facing output is managed via stdout/stderr as appropriate.",{"category":118,"check":119,"severity":24,"summary":120},"Compliance","GDPR","The skill processes document content provided by the user and does not inherently handle personal data without user submission or explicit processing of document contents.",{"category":118,"check":122,"severity":24,"summary":123},"Target market","The skill processes documents and does not appear to have any regional or jurisdictional limitations, making it globally applicable.",{"category":92,"check":125,"severity":24,"summary":126},"Runtime stability","The skill relies on standard Python libraries and `uv` for dependency management, ensuring cross-platform compatibility.",{"category":45,"check":128,"severity":24,"summary":129},"README","The README provides a comprehensive overview, features, installation, and usage examples, clearly stating the extension's purpose.",{"category":33,"check":131,"severity":42,"summary":132},"Tool surface size","This is a skill with a single entry point, not a collection of tools.",{"category":40,"check":134,"severity":42,"summary":135},"Overlapping near-synonym tools","This is a skill with a single entry point, not a collection of tools with overlapping synonyms.",{"category":45,"check":137,"severity":24,"summary":138},"Phantom features","All advertised features, such as document parsing and output formats, are directly supported by the provided scripts and documentation.",{"category":140,"check":141,"severity":24,"summary":142},"Install","Installation instruction","The SKILL.md provides clear installation instructions using `uv` and copy-pasteable usage examples for various scenarios.",{"category":144,"check":145,"severity":24,"summary":146},"Errors","Actionable error messages","Errors are reported with codes and human-readable messages, guiding the user on configuration, input, or API issues.",{"category":104,"check":148,"severity":24,"summary":149},"Pinned dependencies","Dependencies are managed via `uv` and declared with specific versions, ensuring reproducible builds.",{"category":33,"check":151,"severity":42,"summary":152},"Dry-run preview","The skill is primarily for data extraction and does not perform state-changing operations that would typically require a dry-run mode.",{"category":154,"check":155,"severity":24,"summary":156},"Protocol","Idempotent retry & timeouts","The API client has a configurable timeout, and operations are not state-changing in a way that would cause issues with retries.",{"category":118,"check":158,"severity":24,"summary":159},"Telemetry opt-in","The skill does not appear to emit any telemetry by default, and no opt-out mechanisms are mentioned, aligning with opt-in principles.",{"category":40,"check":161,"severity":24,"summary":162},"Precise Purpose","The description clearly defines the artifact (PDFs, document images) and the task (extract structured Markdown/JSON), with specific trigger terms.",{"category":40,"check":164,"severity":24,"summary":165},"Concise Frontmatter","The frontmatter is concise and effectively summarizes the core capability and lists relevant trigger terms.",{"category":45,"check":167,"severity":24,"summary":168},"Concise Body","The SKILL.md is well-structured, with main instructions and references to separate documentation files like `output_schema.md`.",{"category":170,"check":171,"severity":24,"summary":172},"Context","Progressive Disclosure","Detailed schema information is provided in a separate file (`references/output_schema.md`), demonstrating progressive disclosure.",{"category":170,"check":174,"severity":42,"summary":175},"Forked exploration","The skill is a direct processing tool and does not involve deep exploration that would require forked context.",{"category":22,"check":177,"severity":24,"summary":178},"Usage examples","Multiple clear, end-to-end usage examples are provided in the SKILL.md, demonstrating various input methods and output options.",{"category":22,"check":180,"severity":24,"summary":181},"Edge cases","The documentation addresses potential issues like unsupported formats, API errors, and large file handling with recovery steps.",{"category":111,"check":183,"severity":42,"summary":184},"Tool Fallback","This skill does not rely on external tools like MCP servers and uses its own library, so fallbacks are not applicable.",{"category":92,"check":186,"severity":24,"summary":187},"Stack assumptions","The SKILL.md specifies Python 3.9+ as a requirement and uses standard libraries managed by `uv`, ensuring portability.",{"category":189,"check":190,"severity":24,"summary":191},"Safety","Halt on unexpected state","The script includes checks for valid inputs and handles API errors gracefully by reporting them, effectively halting on unexpected states.",{"category":92,"check":193,"severity":24,"summary":194},"Cross-skill coupling","The skill operates standalone and does not implicitly rely on other skills; its functionality is self-contained.",1778695206661,"This skill leverages PaddleOCR's advanced models (PaddleOCR-VL, PP-StructureV3) to extract structured Markdown/JSON from PDFs and document images, including tables, formulas, figures, and layout information. It supports various input methods (URL, local path), optional file type specification, and configurable output handling (save to file, stdout). Error handling and API configuration guidance are provided.",[198,199,200,201,202],"Extract tables with cell-level precision","Recognize formulas as LaTeX","Parse multi-column layouts and reading order","Output structured Markdown or JSON","Support for PDFs and document images",[204,205,206],"Simple text-only OCR tasks","Speed-critical OCR on basic images","Processing screenshots or basic images with clear text",[],[209,210,211,212,213],"Python 3.9+","uv package manager","Internet access for API calls","PADDLEOCR_DOC_PARSING_API_URL environment variable","PADDLEOCR_ACCESS_TOKEN environment variable","3.0.0","4.4.0","To accurately extract structured information from complex documents and images, making the content easily usable for LLMs and downstream processing.","The extension is exceptionally well-documented and implemented, with comprehensive usage examples, clear error handling, and robust dependency management. It addresses a specific user need effectively and adheres to best practices across security, portability, and maintenance.",99,"A highly robust and well-documented skill for extracting structured data from PDFs and document images.",[221,222,223,224,225,226,227,228],"ocr","document-parsing","pdf","image-processing","layout-analysis","structure-extraction","markdown","json","global","verified",[232,233,234,235],"Processing invoices and financial reports","Extracting content from academic papers","Structuring data from scanned documents","Analyzing complex document layouts",[237,238,239,240,241],"Identify input source (URL or local file)","Execute document parsing script with appropriate parameters","Parse the JSON response (checking `ok` status and `error` fields)","Extract relevant data (text, tables, formulas) from the structured output","Present results to the user or use for further processing",{"codeQuality":243,"collectedAt":245,"documentation":246,"maintenance":249,"security":256,"testCoverage":258},{"hasLockfile":244},true,1778695190156,{"descriptionLength":247,"readmeSize":248},419,23379,{"closedIssues90d":250,"forks":251,"hasChangelog":252,"openIssues90d":253,"pushedAt":254,"stars":255},60,10426,false,58,1778674559000,77756,{"hasNpmPackage":252,"license":257,"smitheryVerified":252},"Apache-2.0",{"hasCi":244,"hasTests":244},{"updatedAt":260},1778695207150,{"basePath":262,"githubOwner":263,"githubRepo":264,"locale":18,"slug":265,"type":266},"skills/paddleocr-doc-parsing","PaddlePaddle","PaddleOCR","paddleocr-doc-parsing","skill",null,{"evaluate":269,"extract":271},{"promptVersionExtension":214,"promptVersionScoring":215,"score":218,"tags":270,"targetMarket":229,"tier":230},[221,222,223,224,225,226,227,228],{"commitSha":272,"license":257},"HEAD",{"repoId":274},"kd77seqrqsfst3qefpyp2ape5h86mhqy",{"_creationTime":276,"_id":274,"identity":277,"providers":278,"workflow":364},1778695167335.008,{"githubOwner":263,"githubRepo":264,"sourceUrl":14},{"classify":279,"discover":346,"github":349},{"commitSha":272,"extensions":280},[281,303,316,334],{"basePath":262,"description":10,"displayName":265,"installMethods":282,"rationale":283,"selectedPaths":284,"source":302,"sourceLanguage":18,"type":266},{"claudeCode":12},"SKILL.md frontmatter at skills/paddleocr-doc-parsing/SKILL.md",[285,288,291,294,296,298,300],{"path":286,"priority":287},"SKILL.md","mandatory",{"path":289,"priority":290},"references/output_schema.md","medium",{"path":292,"priority":293},"scripts/layout_caller.py","low",{"path":295,"priority":293},"scripts/lib.py",{"path":297,"priority":293},"scripts/optimize_file.py",{"path":299,"priority":293},"scripts/smoke_test.py",{"path":301,"priority":293},"scripts/split_pdf.py","rule",{"basePath":304,"description":305,"displayName":306,"installMethods":307,"rationale":308,"selectedPaths":309,"source":302,"sourceLanguage":18,"type":266},"skills/paddleocr-text-recognition","Use this skill whenever the user wants text extracted from images, photos, scans, screenshots, or scanned PDFs. Returns exact machine-readable strings with line-level text and optional bbox coordinates. Strong accuracy for CJK, small print, and handwritten text. Trigger terms: OCR, 文字识别, 图片转文字, 截图识字, 提取图中文字, 扫描识字, 识字, 纯文字, plain text extraction, 坐标, 检测框, bbox, bounding box, image to text, screenshot, photo scan, recognize text.","paddleocr-text-recognition",{"claudeCode":12},"SKILL.md frontmatter at skills/paddleocr-text-recognition/SKILL.md",[310,311,312,313,315],{"path":286,"priority":287},{"path":289,"priority":290},{"path":295,"priority":293},{"path":314,"priority":293},"scripts/ocr_caller.py",{"path":299,"priority":293},{"basePath":317,"installMethods":318,"rationale":320,"selectedPaths":321,"source":302,"sourceLanguage":18,"type":333},"",{"pypi":319},"paddleocr","cli ecosystem detected at /",[322,324,326,328,331],{"path":323,"priority":287},"pyproject.toml",{"path":325,"priority":287},"setup.py",{"path":327,"priority":287},"README.md",{"path":329,"priority":330},"LICENSE","high",{"path":332,"priority":290},"paddleocr/__main__.py","cli",{"basePath":335,"displayName":336,"installMethods":337,"rationale":338,"selectedPaths":339,"source":302,"sourceLanguage":344,"type":345},"mcp_server","paddleocr_mcp",{"pypi":336},"pyproject.toml with mcp/fastmcp dependency + scripts at mcp_server/pyproject.toml",[340,341,342],{"path":323,"priority":287},{"path":327,"priority":287},{"path":343,"priority":290},"paddleocr_mcp/__main__.py","fr","mcp",{"sources":347},[348],"manual",{"closedIssues90d":250,"description":350,"forks":251,"homepage":351,"license":257,"openIssues90d":253,"pushedAt":254,"readmeSize":248,"stars":255,"topics":352},"Turn any PDF or image document into structured data for your AI. A powerful, lightweight OCR toolkit that bridges the gap between images/PDFs and LLMs. Supports 100+ languages.","https://www.paddleocr.com",[221,353,354,355,356,222,357,358,359,360,361,362,363],"chineseocr","pdf2markdown","pp-ocr","pp-structure","document-translation","kie","ai4science","pdf-extractor-rag","pdf-parser","rag","paddleocr-vl",{"classifiedAt":365,"discoverAt":366,"extractAt":367,"githubAt":367,"updatedAt":365},1778695188896,1778695167335,1778695186352,[222,224,228,225,227,221,223,226],{"evaluatedAt":260,"extractAt":370,"updatedAt":371},1778695189192,1778695313334,[],[374,393,425,451,473,495],{"_creationTime":375,"_id":376,"community":377,"display":378,"identity":380,"providers":381,"relations":388,"tags":389,"workflow":390},1778695189192.851,"k17a43s5382jae1sgtne8ngfg586m9f0",{"reviewCount":8},{"description":305,"installMethods":379,"name":306,"sourceUrl":14},{"claudeCode":12},{"basePath":304,"githubOwner":263,"githubRepo":264,"locale":18,"slug":306,"type":266},{"evaluate":382,"extract":387},{"promptVersionExtension":214,"promptVersionScoring":215,"score":218,"tags":383,"targetMarket":229,"tier":230},[221,384,385,222,223,386],"text-extraction","image-to-text","python",{"commitSha":272},{"repoId":274},[222,385,221,223,386,384],{"evaluatedAt":391,"extractAt":370,"updatedAt":392},1778695224039,1778695313155,{"_creationTime":394,"_id":395,"community":396,"display":397,"identity":403,"providers":408,"relations":418,"tags":421,"workflow":422},1778691104675.98,"k17a012kzjtmn6vm9xf7k1q3d986n6me",{"reviewCount":8},{"description":398,"installMethods":399,"name":401,"sourceUrl":402},"Convert a resume PDF to clean markdown for LLM parsing or candidate pipelines.",{"claudeCode":400},"iterationlayer/skills","Convert Resume to Markdown","https://github.com/iterationlayer/skills",{"basePath":404,"githubOwner":405,"githubRepo":406,"locale":18,"slug":407,"type":266},"skills/convert-resume-to-markdown","iterationlayer","skills","convert-resume-to-markdown",{"evaluate":409,"extract":416},{"promptVersionExtension":214,"promptVersionScoring":215,"score":410,"tags":411,"targetMarket":229,"tier":230},100,[412,223,227,413,414,415],"document-processing","resume","hiring","nlp",{"commitSha":272,"license":417},"MIT",{"parentExtensionId":419,"repoId":420},"k1721s0xmp59902ybtpakrrffn86n10s","kd76p4g2qmtrkgx99cnab3683d86n4g8",[412,414,227,415,223,413],{"evaluatedAt":423,"extractAt":424,"updatedAt":423},1778691474825,1778691104676,{"_creationTime":426,"_id":427,"community":428,"display":429,"identity":435,"providers":438,"relations":444,"tags":447,"workflow":448},1778686940775.5723,"k17d40zvn2sfy64zvq7rzpzksh86mndd",{"reviewCount":8},{"description":430,"installMethods":431,"name":433,"sourceUrl":434},"Efficiently extract and convert the contents of any local file—such as PDF, DOCX, DOC, ODT, RTF, XLSX, XLS, or HTML—into clean, well-formatted markdown saved to disk. Use this skill whenever the user requests to parse, read, or extract information from a file on their computer, including phrases like “parse this PDF”, “convert this document”, “read this file”, “extract text from”, or when a local file path (not a URL) is provided. This skill offers advanced options like generating AI-powered summaries and answering questions based on the file's content. Prefer this tool over `scrape` when handling local files to deliver precise, structured outputs for downstream tasks.\n",{"claudeCode":432},"firecrawl/cli","firecrawl-parse","https://github.com/firecrawl/cli",{"basePath":436,"githubOwner":437,"githubRepo":333,"locale":18,"slug":433,"type":266},"skills/firecrawl-parse","firecrawl",{"evaluate":439,"extract":443},{"promptVersionExtension":214,"promptVersionScoring":215,"score":218,"tags":440,"targetMarket":229,"tier":230},[441,222,227,223,442,333],"file-conversion","docx",{"commitSha":272},{"parentExtensionId":445,"repoId":446},"k17axfavjpz72cd3qqzn86shb186ncqt","kd7csd1wb06dg9c1jfy5063f2586ne60",[333,222,442,441,227,223],{"evaluatedAt":449,"extractAt":450,"updatedAt":449},1778687175227,1778686940775,{"_creationTime":452,"_id":453,"community":454,"display":455,"identity":459,"providers":462,"relations":469,"tags":470,"workflow":471},1778691104676.005,"k17b3rrsy570h6ysqbn0p324f186mzxv",{"reviewCount":8},{"description":456,"installMethods":457,"name":458,"sourceUrl":402},"Generate a professionally styled PDF document from Markdown content with custom fonts, headers, and page numbers.",{"claudeCode":400},"Markdown to Styled PDF",{"basePath":460,"githubOwner":405,"githubRepo":406,"locale":18,"slug":461,"type":266},"skills/markdown-to-styled-pdf","markdown-to-styled-pdf",{"evaluate":463,"extract":468},{"promptVersionExtension":214,"promptVersionScoring":215,"score":218,"tags":464,"targetMarket":229,"tier":230},[223,227,465,466,467],"document-generation","content-creation","styling",{"commitSha":272,"license":417},{"parentExtensionId":419,"repoId":420},[466,465,227,223,467],{"evaluatedAt":472,"extractAt":424,"updatedAt":472},1778693710276,{"_creationTime":474,"_id":475,"community":476,"display":477,"identity":481,"providers":484,"relations":491,"tags":492,"workflow":493},1778691104675.9805,"k173dwe2djyydbkrp6qr8dbrfs86nk8d",{"reviewCount":8},{"description":478,"installMethods":479,"name":480,"sourceUrl":402},"Extract structured data from documents using AI-powered field extraction.",{"claudeCode":400},"Document Extraction API",{"basePath":482,"githubOwner":405,"githubRepo":406,"locale":18,"slug":483,"type":266},"skills/document-extraction-api","document-extraction-api",{"evaluate":485,"extract":490},{"promptVersionExtension":214,"promptVersionScoring":215,"score":218,"tags":486,"targetMarket":229,"tier":230},[412,487,488,489,223,221],"data-extraction","ai","api",{"commitSha":272,"license":417},{"parentExtensionId":419,"repoId":420},[488,489,487,412,221,223],{"evaluatedAt":494,"extractAt":424,"updatedAt":494},1778691504579,{"_creationTime":496,"_id":497,"community":498,"display":499,"identity":505,"providers":508,"relations":518,"tags":520,"workflow":521},1778695810823.162,"k1704fp8n8znrmyrxm482pgpr586nfzx",{"reviewCount":8},{"description":500,"installMethods":501,"name":503,"sourceUrl":504},"Process documents with Nutrient DWS. Use when the user wants to generate PDFs from HTML or URLs, convert Office/images/PDFs, assemble or split packets, OCR scans, extract text/tables/key-value pairs, redact PII, watermark, sign, fill forms, optimize PDFs, or produce compliance outputs like PDF/A or PDF/UA. Triggers include convert to PDF, merge these PDFs, OCR this scan, extract tables, redact PII, sign this PDF, make this PDF/A, or linearize for web delivery.",{"claudeCode":502},"PSPDFKit-labs/nutrient-agent-skill","nutrient-document-processing","https://github.com/PSPDFKit-labs/nutrient-agent-skill",{"basePath":503,"githubOwner":506,"githubRepo":507,"locale":18,"slug":503,"type":266},"PSPDFKit-labs","nutrient-agent-skill",{"evaluate":509,"extract":517},{"promptVersionExtension":214,"promptVersionScoring":215,"score":510,"tags":511,"targetMarket":229,"tier":230},98,[412,223,221,512,513,514,515,516],"conversion","redaction","signing","compliance","extraction",{"commitSha":272},{"repoId":519},"kd71fjmn43awb0bgafy6r3vers86ngqg",[515,512,412,516,221,223,513,514],{"evaluatedAt":522,"extractAt":523,"updatedAt":524},1778695838272,1778695810823,1778695861458]