[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"extension-skill-lijigang-ljg-paper-flow-zh-CN":3,"guides-for-lijigang-ljg-paper-flow":265,"similar-k174smwg1tbsfe02zsg46cs889866z7e":266},{"_creationTime":4,"_id":5,"children":6,"community":7,"display":9,"evaluation":21,"identity":186,"isFallback":190,"parentExtension":191,"providers":242,"relations":245,"repo":246,"workflow":264},1778053348890.7822,"k174smwg1tbsfe02zsg46cs889866z7e",[],{"reviewCount":8},0,{"description":10,"installMethods":11,"name":12,"sourceUrl":13,"tags":14},"Paper workflow: read papers + cast cards in one go. Takes one or more arxiv links, paper URLs, PDFs, or paper names. For each paper, runs ljg-paper (generates org analysis) then ljg-card -v (generates visual sketchnote PNG). Use when user says '论文流', 'paper flow', '读论文并做卡片', '论文卡片', or provides multiple papers wanting both analysis and cards.",{},"ljg-paper-flow","https://github.com/lijigang/ljg-skills/tree/HEAD/skills/ljg-paper-flow",[15,16,17,18,19,20],"papers","arxiv","analysis","sketchnote","workflow","automation",{"_creationTime":22,"_id":23,"extensionId":5,"locale":24,"result":25,"trustSignals":175,"workflow":184},1778053415028.5596,"kn77w88x5j9n9ehnfyymex90z5866vfy","en",{"checks":26,"evaluatedAt":165,"extensionSummary":166,"promptVersionExtension":167,"promptVersionScoring":168,"rationale":169,"score":170,"summary":171,"tags":172,"targetMarket":173,"tier":174},[27,32,35,38,42,45,49,53,56,59,64,68,72,75,78,81,84,87,90,93,97,101,105,109,112,115,118,122,125,128,131,134,137,141,144,148,152,155,158,162],{"category":28,"check":29,"severity":30,"summary":31},"Practical Utility","Problem relevance","pass","The description clearly states the problem: automating the paper reading and card creation workflow, directly addressing the user's need to process multiple papers efficiently.",{"category":28,"check":33,"severity":30,"summary":34},"Unique selling proposition","This skill offers a significant value proposition by automating a multi-step, multi-paper workflow (reading, analysis, card generation) that goes beyond simple prompt engineering and orchestrates multiple underlying tools (`ljg-paper`, `ljg-card`).",{"category":28,"check":36,"severity":30,"summary":37},"Production readiness","The skill covers the complete lifecycle for processing papers, from input to output, and the documentation describes a clear execution flow, indicating readiness for practical use.",{"category":39,"check":40,"severity":30,"summary":41},"Scope","Single responsibility principle","The skill focuses on a single, coherent workflow: processing academic papers to generate analysis and visual cards, without extending into unrelated domains.",{"category":39,"check":43,"severity":30,"summary":44},"Description quality","The provided description is concise, readable, and accurately reflects the skill's behavior as described in the SKILL.md file.",{"category":46,"check":47,"severity":30,"summary":48},"Invocation","Scoped tools","The skill orchestrates specific tools (`ljg-paper`, `ljg-card`) with clear, verb-noun actions, rather than relying on a single generalist tool.",{"category":50,"check":51,"severity":30,"summary":52},"Documentation","Configuration & parameter reference","The SKILL.md file documents the available parameters (`-l`, `-i`, `-c`) and their effects, with clear defaults and no implicit configuration sources.",{"category":39,"check":54,"severity":30,"summary":55},"Tool naming","The underlying tools (`ljg-paper`, `ljg-card`) have descriptive verb-noun names.",{"category":39,"check":57,"severity":30,"summary":58},"Minimal I/O surface","The skill's inputs (paper sources) and outputs (org file paths, PNG file paths) are well-defined and appear minimal for the task. The underlying tools are assumed to adhere to this principle.",{"category":60,"check":61,"severity":62,"summary":63},"License","License usability","not_applicable","No license information is provided in the repository or manifests, making it impossible to determine usability. This check is marked not_applicable as there's no license signal to evaluate.",{"category":65,"check":66,"severity":62,"summary":67},"Maintenance","Commit recency","The last commit date is not available, so recency cannot be determined.",{"category":69,"check":70,"severity":62,"summary":71},"Security","Secret Management","The skill does not appear to handle or use any secrets, making this check not applicable.",{"category":69,"check":73,"severity":30,"summary":74},"Injection","The skill appears to bundle all necessary data and scripts, and the workflow relies on internal tools rather than external data fetching, mitigating injection risks.",{"category":69,"check":76,"severity":30,"summary":77},"Transitive Supply-Chain Grenades","The skill does not appear to fetch remote content or execute arbitrary commands at runtime, keeping all operations within the bundle.",{"category":69,"check":79,"severity":30,"summary":80},"Sandbox Isolation","The skill operates on provided paper sources and generates files, but the workflow description and available files do not suggest any operations outside the skill's designated scope or filesystem.",{"category":69,"check":82,"severity":30,"summary":83},"Sandbox escape primitives","No detached-process spawns or retry loops around denied tool calls were identified in the provided scripts or documentation.",{"category":69,"check":85,"severity":30,"summary":86},"Data Exfiltration","The skill processes local files and generates output files; there are no documented outbound calls or references to sensitive data exfiltration.",{"category":69,"check":88,"severity":30,"summary":89},"Hidden Text Tricks","The bundled markdown and script files do not contain any hidden-steering tricks, invisible characters, or obfuscation attempts.",{"category":69,"check":91,"severity":30,"summary":92},"Opaque code execution","The skill's scripts and documentation do not indicate any obfuscated code execution, base64 payloads, or runtime script fetching.",{"category":94,"check":95,"severity":30,"summary":96},"Portability","Structural Assumption","The skill operates on provided paper sources and generates output files, and the process description does not indicate assumptions about user-specific project organization outside of these inputs/outputs.",{"category":98,"check":99,"severity":62,"summary":100},"Trust","Issues Attention","No issue data is available to evaluate maintainer engagement.",{"category":102,"check":103,"severity":30,"summary":104},"Versioning","Release Management","A version ('1.0.2') is clearly declared in the SKILL.md frontmatter.",{"category":106,"check":107,"severity":30,"summary":108},"Code Execution","Validation","The skill relies on underlying tools (`ljg-paper`, `ljg-card`) which are assumed to handle their own input validation. The skill itself orchestrates these tools based on defined parameters and collected paper sources.",{"category":69,"check":110,"severity":30,"summary":111},"Unguarded Destructive Operations","The skill's primary actions involve reading input papers and generating output files (analysis, cards), which are not considered destructive operations requiring special guards.",{"category":106,"check":113,"severity":30,"summary":114},"Error Handling","The skill's execution flow is clearly defined, and it's expected that the underlying tools (`ljg-paper`, `ljg-card`) would provide meaningful error reporting. The overall structure implies failure would halt the workflow.",{"category":106,"check":116,"severity":62,"summary":117},"Logging","The skill is primarily read-only concerning user data (papers) and generates new files. There are no destructive actions or sensitive outbound calls that would necessitate local audit logging for review.",{"category":119,"check":120,"severity":62,"summary":121},"Compliance","GDPR","The skill processes academic paper content and generates output files. It does not appear to operate on personal data that would require GDPR-specific sanitization.",{"category":119,"check":123,"severity":30,"summary":124},"Target market","The skill processes academic papers and generates analysis/cards, with no discernible regional or jurisdictional logic, making it globally applicable. `targetMarket` is set to 'global'.",{"category":94,"check":126,"severity":30,"summary":127},"Runtime stability","The skill's workflow description and the presence of the `ljg-skills` repository with multiple installation methods suggest a focus on portability across different environments where the `skills` CLI is available.",{"category":46,"check":129,"severity":30,"summary":130},"Precise Purpose","The description clearly defines the artifact (papers), the user intent (read, analyze, create cards), and lists specific trigger phrases and use cases, making its purpose and scope precise.",{"category":46,"check":132,"severity":30,"summary":133},"Concise Frontmatter","The frontmatter is concise, clearly stating the core capability ('Paper workflow: read papers + cast cards in one go.') and providing specific trigger phrases.",{"category":50,"check":135,"severity":30,"summary":136},"Concise Body","The SKILL.md body is reasonably concise, outlining the workflow steps and delegating deeper details to the underlying tools' implicit functionality.",{"category":138,"check":139,"severity":30,"summary":140},"Context","Progressive Disclosure","The SKILL.md outlines the workflow and relies on the underlying tools (`ljg-paper`, `ljg-card`) to perform their specific tasks, implying progressive disclosure through tool execution rather than embedding extensive content.",{"category":138,"check":142,"severity":62,"summary":143},"Forked exploration","This skill is not an exploration or audit-style skill; it performs a defined, sequential processing task, so `context: fork` is not applicable.",{"category":28,"check":145,"severity":146,"summary":147},"Usage examples","warning","While the SKILL.md describes the parameters and execution flow, it lacks concrete, end-to-end examples showing the input, invocation, and expected output for processing papers.",{"category":28,"check":149,"severity":150,"summary":151},"Edge cases","info","The SKILL.md mentions the parameters like `-l`, `-i`, `-c` for card generation modes but does not explicitly document failure modes or recovery steps for issues like invalid paper sources or tool errors.",{"category":106,"check":153,"severity":62,"summary":154},"Tool Fallback","The skill directly calls other skills (`ljg-paper`, `ljg-card`) from the same repository, implying they are available locally. There's no mention of external dependencies that would require fallback mechanisms.",{"category":94,"check":156,"severity":30,"summary":157},"Stack assumptions","The README indicates installation via the `skills CLI` and mentions `npm install` for a dependency, suggesting a Node.js environment and adherence to common development tooling, which is clearly declared.",{"category":159,"check":160,"severity":30,"summary":161},"Safety","Halt on unexpected state","The documented execution flow implies a sequential process where errors in one step would halt the workflow, and the skill operates on provided inputs, suggesting it would report issues with unexpected pre-state.",{"category":94,"check":163,"severity":30,"summary":164},"Cross-skill coupling","The skill orchestrates other specific skills (`ljg-paper`, `ljg-card`) from the same repository, and this coupling is explicit and necessary for its defined workflow. It does not appear to implicitly rely on other unrelated skills.",1778053376785,"This skill takes one or more paper sources (Arxiv links, URLs, PDFs, names) and processes them sequentially: first using `ljg-paper` for analysis, then `ljg-card` for visual card generation. It supports parallel processing of multiple papers and offers different card output modes via parameters.","2.0.0","3.4.0","The extension is well-documented, has a clear and single responsibility, and orchestrates underlying tools effectively. The lack of concrete usage examples and detailed edge case documentation prevents a perfect score, but its overall quality and production readiness are high.",85,"This skill automates the process of reading academic papers, generating an org-mode analysis, and creating a visual sketchnote card.",[15,16,17,18,19,20],"global","verified",{"codeQuality":176,"collectedAt":177,"documentation":178,"maintenance":180,"security":181,"testCoverage":183},{},1778053364472,{"descriptionLength":179,"readmeSize":8},344,{},{"hasNpmPackage":182,"smitheryVerified":182},false,{"hasCi":182,"hasTests":182},{"updatedAt":185},1778053415028,{"githubOwner":187,"githubRepo":188,"locale":24,"slug":12,"type":189},"lijigang","ljg-skills","skill",true,{"_creationTime":192,"_id":193,"community":194,"display":195,"identity":209,"parentExtension":211,"providers":236,"relations":240,"workflow":241},1778053348890.7798,"k1704g81mbxzdxt81951f8s6g1866ry3",{"reviewCount":8},{"description":196,"installMethods":197,"name":198,"sourceUrl":199,"tags":200},"LJG's personal Claude Code skills collection",{},"LJG Skills Collection","https://github.com/lijigang/ljg-skills",[201,202,203,204,205,206,207,208],"skills","content-creation","writing","research","documentation","visualization","productivity","academic",{"githubOwner":187,"githubRepo":188,"locale":24,"slug":188,"type":210},"plugin",{"_creationTime":212,"_id":213,"community":214,"display":215,"identity":219,"providers":221,"relations":231,"workflow":233},1778053348890.7793,"k17axkces4ykqysd5mgcmajr89867sm1",{"reviewCount":8},{"description":216,"installMethods":217,"name":198,"sourceUrl":199,"tags":218},"Personal Claude Code skills collection for paper reading, content casting, and writing workflows",{},[201,202,204,203,207],{"githubOwner":187,"githubRepo":188,"locale":24,"slug":188,"type":220},"marketplace",{"extract":222,"llm":228},{"commitSha":223,"license":224,"marketplace":225},"d2d6a0313baaeee789d00aa5c3841d4622147f23","MIT",{"name":188,"pluginCount":226,"version":227},1,"1.17.15",{"promptVersionExtension":167,"promptVersionScoring":168,"score":229,"targetMarket":173,"tier":230},88,"flagged",{"repoId":232},"kd71hhp7w2dcgt37rznesw08cx864k8w",{"anyEnrichmentAt":234,"extractAt":235,"githubAt":234,"llmAt":185,"updatedAt":185},1778053349620,1778053348890,{"extract":237,"llm":238},{"commitSha":223,"license":224},{"promptVersionExtension":167,"promptVersionScoring":168,"score":239,"targetMarket":173,"tier":174},90,{"parentExtensionId":213,"repoId":232},{"anyEnrichmentAt":234,"extractAt":235,"githubAt":234,"llmAt":185,"updatedAt":185},{"extract":243,"llm":244},{"commitSha":223,"license":62},{"promptVersionExtension":167,"promptVersionScoring":168,"score":170,"targetMarket":173,"tier":174},{"parentExtensionId":193,"repoId":232},{"_creationTime":247,"_id":232,"identity":248,"providers":249,"workflow":261},1777995558409.893,{"githubOwner":187,"githubRepo":188,"sourceUrl":199},{"discover":250,"github":253},{"sources":251},[252],"skills-sh",{"closedIssues90d":254,"forks":255,"openIssues90d":256,"pushedAt":257,"readmeSize":258,"stars":259,"topics":260},5,458,2,1777870782000,4594,3935,[],{"discoverAt":262,"extractAt":263,"githubAt":263,"updatedAt":263},1777995558409,1778053350730,{"anyEnrichmentAt":234,"extractAt":235,"githubAt":234,"llmAt":185,"updatedAt":185},[],[267,297,316,344,370,399],{"_creationTime":268,"_id":269,"community":270,"display":271,"identity":282,"providers":286,"relations":291,"workflow":293},1778053622473.6682,"k171xwg814163s51767b0q0pn1866cwe",{"reviewCount":8},{"description":272,"installMethods":273,"name":274,"sourceUrl":275,"tags":276},"Orchestrate multiple worker agents to implement groomed tasks in Gitea repositories. Use when multiple ready tasks need implementation, when you want autonomous multi-task execution, or when coordinating batch development work with Gitea. Keywords: coordinator, orchestrator, multi-task, parallel, workers, batch, autonomous, gitea, tea.",{},"Gitea Coordinator","https://github.com/jwynia/agent-skills/tree/HEAD/skills/tech/development/workflow/gitea-coordinator",[277,278,20,279,280,19,281],"gitea","orchestration","agile","development","multi-agent",{"githubOwner":283,"githubRepo":284,"locale":24,"slug":285,"type":189},"jwynia","agent-skills","gitea-coordinator",{"extract":287,"llm":289},{"commitSha":288,"license":224},"e02ec7e226a6e4f8419fd3b88a1d8e472d421b32",{"promptVersionExtension":167,"promptVersionScoring":168,"score":290,"targetMarket":173,"tier":174},98,{"repoId":292},"kd7efn3mprpa8rd8vm5hw5ebzx864fph",{"anyEnrichmentAt":294,"extractAt":295,"githubAt":294,"llmAt":296,"updatedAt":296},1778053625386,1778053622473,1778054012696,{"_creationTime":298,"_id":299,"community":300,"display":301,"identity":309,"providers":311,"relations":314,"workflow":315},1778053622473.6672,"k178b0dafhyecx3y6cbxkne8mh866zc4",{"reviewCount":8},{"description":302,"installMethods":303,"name":304,"sourceUrl":305,"tags":306},"Orchestrate multiple worker agents to implement groomed tasks. Use when multiple ready tasks need implementation, when you want autonomous multi-task execution, or when coordinating batch development work. Keywords: coordinator, orchestrator, multi-task, parallel, workers, batch, autonomous.",{},"Agile Coordinator","https://github.com/jwynia/agent-skills/tree/HEAD/skills/tech/development/workflow/agile-coordinator",[279,19,278,307,308,20],"developer-tools","git",{"githubOwner":283,"githubRepo":284,"locale":24,"slug":310,"type":189},"agile-coordinator",{"extract":312,"llm":313},{"commitSha":288,"license":224},{"promptVersionExtension":167,"promptVersionScoring":168,"score":290,"targetMarket":173,"tier":174},{"repoId":292},{"anyEnrichmentAt":294,"extractAt":295,"githubAt":294,"llmAt":296,"updatedAt":296},{"_creationTime":317,"_id":318,"community":319,"display":320,"identity":330,"providers":333,"relations":338,"workflow":340},1778053148350.472,"k173y3pwnb1drb2gbyz8f6z35h867n6c",{"reviewCount":8},{"description":321,"installMethods":322,"name":323,"sourceUrl":324,"tags":325},"Google Sheets automation workflows - data sync, task management, reporting dashboards, and multi-platform integrations",{},"Google Sheets Automation","https://github.com/claude-office-skills/skills/tree/HEAD/sheets-automation",[326,20,327,328,329,207,19],"google-sheets","data-sync","reporting","n8n",{"githubOwner":331,"githubRepo":201,"locale":24,"slug":332,"type":189},"claude-office-skills","sheets-automation",{"extract":334,"llm":336},{"commitSha":335,"license":224},"9c4c7d5cd2813a8936bf2c9fdb174ea883b85a11",{"promptVersionExtension":167,"promptVersionScoring":168,"score":337,"targetMarket":173,"tier":174},96,{"repoId":339},"kd7fw7xbj58qc2z8whrrjptbed8659db",{"anyEnrichmentAt":341,"extractAt":342,"githubAt":341,"llmAt":343,"updatedAt":343},1778053151766,1778053148350,1778053561145,{"_creationTime":345,"_id":346,"community":347,"display":348,"identity":355,"providers":359,"relations":364,"workflow":366},1778054781976.5938,"k17asp96sbhz0w88jtzw1tnjp1867es7",{"reviewCount":8},{"description":349,"installMethods":350,"name":351,"sourceUrl":352,"tags":353},"AI Native Camp Day 4 Wrap & Analyze. session-wrap 스킬을 직접 만들고, history-insight와 session-analyzer로 세션을 분석한다. \"4일차\", \"Day 4\", \"wrap\", \"세션 분석\", \"session wrap\", \"세션 래핑\" 요청에 사용.",{},"Day 4: Wrap & Analyze","https://github.com/ai-native-camp/camp-1/tree/HEAD/.agents/skills/day4-wrap-and-analyze",[189,354,17,281,19,205],"session-wrap",{"githubOwner":356,"githubRepo":357,"locale":24,"slug":358,"type":189},"ai-native-camp","camp-1","day4-wrap-and-analyze",{"extract":360,"llm":362},{"commitSha":361,"license":150},"9ffaf358dc8c88567d8f0450966b5518071da4f0",{"promptVersionExtension":167,"promptVersionScoring":168,"score":363,"targetMarket":173,"tier":174},95,{"repoId":365},"kd72seepns71xx9ksxrb02bs1n8645k6",{"anyEnrichmentAt":367,"extractAt":368,"githubAt":367,"llmAt":369,"updatedAt":369},1778054782298,1778054781976,1778054817045,{"_creationTime":371,"_id":372,"community":373,"display":374,"identity":383,"providers":387,"relations":392,"workflow":394},1777999890864.4045,"k17dhangy7zd7hdz90rr1qvhgn865qpt",{"reviewCount":8},{"description":375,"installMethods":376,"name":377,"sourceUrl":378,"tags":379},"Extension from shoumikdc/arXiv-mcp",{},"arXiv MCP Server","https://github.com/shoumikdc/arXiv-mcp",[16,380,381,204,15,382],"mcp","python","feedparser",{"githubOwner":384,"githubRepo":385,"locale":24,"slug":386,"type":189},"shoumikdc","arXiv-mcp","arxiv-mcp",{"extract":388,"smithery":391},{"commitSha":389,"license":390},"f15fcc3844557ec39adf54c240d45bf31089b6b8","critical",{"qualityScore":8,"totalActivations":8,"uniqueUsers":8,"useCount":8,"verified":182},{"repoId":393},"kd7c6x0414kpcgvtabd03re5t9865kjr",{"anyEnrichmentAt":395,"extractAt":396,"githubAt":397,"invalidatedAt":395,"llmAt":398,"smitheryAt":395,"updatedAt":395},1778007780389,1777999890864,1777999891196,1778005088200,{"_creationTime":400,"_id":401,"community":402,"display":403,"identity":413,"providers":417,"relations":422,"workflow":424},1778053327521.585,"k17eftejnaapgr7mnfajqgng2h866syh",{"reviewCount":8},{"description":404,"installMethods":405,"name":406,"sourceUrl":407,"tags":408},"Systematic fact verification and misinformation identification using evidence-based analysis. Use when: verifying claims, checking facts, identifying misinformation, evaluating source credibility, or when user asks to \"fact check\", \"verify\", \"is this true\", or mentions claims that need validation.",{},"Fact Checker","https://github.com/shubhamsaboo/awesome-llm-apps/tree/HEAD/awesome_agent_skills/fact-checker",[409,410,411,412,17],"fact-checking","misinformation","verification","llm-skill",{"githubOwner":414,"githubRepo":415,"locale":24,"slug":416,"type":189},"shubhamsaboo","awesome-llm-apps","fact-checker",{"extract":418,"llm":420},{"commitSha":419,"license":224},"a35897449fe8b0fab12e8f0fd9f2e2a40e872ab7",{"promptVersionExtension":167,"promptVersionScoring":168,"score":421,"targetMarket":173,"tier":174},100,{"repoId":423},"kd73kvct1kme7748mpsbddhhmx865wd3",{"anyEnrichmentAt":425,"extractAt":426,"githubAt":425,"llmAt":427,"updatedAt":427},1778053329769,1778053327521,1778053376632]