[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"extension-skill-langchain-ai-data-visualization-uk":3,"guides-for-langchain-ai-data-visualization":232,"similar-k17anekbzm63w56w6p2464ehfs867yy1":233},{"_creationTime":4,"_id":5,"children":6,"community":7,"display":9,"evaluation":20,"identity":188,"isFallback":193,"parentExtension":194,"providers":195,"relations":201,"repo":203,"workflow":228},1778053968286.492,"k17anekbzm63w56w6p2464ehfs867yy1",[],{"reviewCount":8},0,{"description":10,"name":11,"sourceUrl":12,"tags":13},"Use for creating publication-quality charts and multi-panel analysis summaries. Triggers when tasks involve visualizing data, plotting results, creating charts, or producing visual reports from analysis output.","Data Visualization Skill","https://github.com/langchain-ai/deepagents/tree/HEAD/examples/nvidia_deep_agent/skills/data-visualization",[14,15,16,17,18,19],"visualization","charts","matplotlib","seaborn","data-analysis","python",{"_creationTime":21,"_id":22,"extensionId":5,"locale":23,"result":24,"trustSignals":176,"workflow":186},1778054053159.3105,"kn77vmtetw43d5xjhdhzxnr5s9866b0q","en",{"checks":25,"evaluatedAt":166,"extensionSummary":167,"promptVersionExtension":168,"promptVersionScoring":169,"rationale":170,"score":171,"summary":172,"tags":173,"targetMarket":174,"tier":175},[26,31,34,38,42,46,50,53,57,61,65,68,71,74,77,81,84,87,90,93,96,100,104,107,111,114,117,120,123,126,129,133,136,140,144,147,150,153,156,160,163],{"category":27,"check":28,"severity":29,"summary":30},"Invocation","Precise Purpose","pass","The skill clearly defines its purpose as creating publication-quality charts and analysis summaries, explicitly stating it triggers for tasks involving visualizing data, plotting, and visual reports.",{"category":27,"check":32,"severity":29,"summary":33},"Concise Frontmatter","The frontmatter is concise and self-contained, effectively summarizing the core capability and listing trigger phrases within a reasonable character limit.",{"category":35,"check":36,"severity":29,"summary":37},"Documentation","Concise Body","The skill body is well under 500 lines and effectively delegates detailed procedures and reference material to separate files, adhering to progressive disclosure principles.",{"category":39,"check":40,"severity":29,"summary":41},"Context","Progressive Disclosure","The SKILL.md file outlines the general flow and effectively links into a conceptual `references/` directory for detailed sub-tasks, managing complexity.",{"category":39,"check":43,"severity":44,"summary":45},"Forked exploration","not_applicable","This skill is focused on generating output rather than deep exploration, so the `context: fork` setting is not applicable.",{"category":47,"check":48,"severity":29,"summary":49},"Practical Utility","Usage examples","Sufficient end-to-end examples are provided for various chart types and multi-panel summaries, demonstrating input, invocation, and plausible output.",{"category":47,"check":51,"severity":29,"summary":52},"Edge cases","The skill handles edge cases, such as the requirement for headless rendering and saving to `/workspace/`, with clear instructions and recovery paths.",{"category":54,"check":55,"severity":44,"summary":56},"Code Execution","Tool Fallback","The skill relies on Claude-internal tools (like `matplotlib`, `seaborn`, `read_file`) and does not explicitly reference external tools like MCP that would require fallbacks.",{"category":58,"check":59,"severity":29,"summary":60},"Portability","Stack assumptions","The skill clearly states its stack assumptions, including the requirement for `matplotlib.use('Agg')` for headless rendering and specifies Python as the runtime.",{"category":62,"check":63,"severity":29,"summary":64},"Safety","Halt on unexpected state","The skill mandates specific initialization steps (`matplotlib.use('Agg')`) and output procedures (`plt.close()`, `read_file`), implicitly halting or failing if these are not met.",{"category":58,"check":66,"severity":29,"summary":67},"Cross-skill coupling","The skill is self-contained and focuses solely on data visualization, with no implicit reliance on other skills.",{"category":47,"check":69,"severity":29,"summary":70},"Problem relevance","The description clearly names the user problem of creating publication-quality charts and analysis summaries.",{"category":47,"check":72,"severity":29,"summary":73},"Unique selling proposition","The skill offers a distinct value proposition by providing a specialized environment and defaults for creating publication-quality charts, going beyond basic plotting.",{"category":47,"check":75,"severity":29,"summary":76},"Production readiness","The skill is production-ready, providing all necessary code, initialization steps, and output guidelines for creating charts in a headless environment.",{"category":78,"check":79,"severity":29,"summary":80},"Scope","Single responsibility principle","The skill has a clear, single responsibility: data visualization using Python libraries like matplotlib and seaborn.",{"category":78,"check":82,"severity":29,"summary":83},"Description quality","The description is concise, readable, and accurately reflects the skill's behavior and capabilities.",{"category":27,"check":85,"severity":44,"summary":86},"Scoped tools","This skill does not expose tools directly but rather provides Python code snippets to be executed within a Python environment. Therefore, the concept of 'scoped tools' is not directly applicable.",{"category":35,"check":88,"severity":29,"summary":89},"Configuration & parameter reference","All necessary configuration and parameters, such as headless rendering settings and saving locations, are clearly documented within the SKILL.md.",{"category":78,"check":91,"severity":44,"summary":92},"Tool naming","This skill does not define explicit tools with names; it provides code snippets for execution within a Python environment. Therefore, tool naming conventions are not applicable.",{"category":78,"check":94,"severity":29,"summary":95},"Minimal I/O surface","The provided code snippets focus on generating charts and saving them to a specific location, with minimal extraneous output.",{"category":97,"check":98,"severity":29,"summary":99},"License","License usability","The extension includes an MIT license file, which is a permissive open-source license.",{"category":101,"check":102,"severity":44,"summary":103},"Maintenance","Commit recency","No commit data is available for this specific skill within the provided context; this check is not applicable without repository access.",{"category":101,"check":105,"severity":44,"summary":106},"Dependency Management","This skill does not manage external dependencies directly; it relies on the Python environment it's executed within. Therefore, dependency management checks are not applicable.",{"category":108,"check":109,"severity":44,"summary":110},"Security","Secret Management","The skill does not handle or expose any secrets.",{"category":108,"check":112,"severity":29,"summary":113},"Injection","The skill provides Python code snippets that are executed within a controlled environment. It does not load or execute untrusted third-party data as instructions.",{"category":108,"check":115,"severity":29,"summary":116},"Transitive Supply-Chain Grenades","The skill's code is bundled and does not fetch external content at runtime that could be manipulated.",{"category":108,"check":118,"severity":29,"summary":119},"Sandbox Isolation","The skill operates within a defined sandbox and saves output to a specified directory (`/workspace/`), adhering to isolation principles.",{"category":108,"check":121,"severity":29,"summary":122},"Sandbox escape primitives","The provided Python code does not contain any obvious sandbox escape primitives.",{"category":108,"check":124,"severity":29,"summary":125},"Data Exfiltration","The skill focuses on chart generation and saving outputs locally; there are no instructions for exfiltrating data.",{"category":108,"check":127,"severity":29,"summary":128},"Hidden Text Tricks","The bundled files are free of hidden-steering tricks, control characters, or invisible Unicode characters designed to mislead the model.",{"category":130,"check":131,"severity":29,"summary":132},"Hooks","Opaque code execution","The Python code is readable and not obfuscated, base64-decoded, or dynamically fetched.",{"category":58,"check":134,"severity":29,"summary":135},"Structural Assumption","The skill makes a reasonable structural assumption about saving files to `/workspace/`, which is a common and documented output directory.",{"category":137,"check":138,"severity":44,"summary":139},"Trust","Issues Attention","No issue tracking data is available for this specific skill within the provided context.",{"category":141,"check":142,"severity":44,"summary":143},"Versioning","Release Management","No versioning information is available for this specific skill within the provided context. The `Manifest Version` is `n/a`.",{"category":54,"check":145,"severity":29,"summary":146},"Validation","The provided code snippets include checks for data types and structures indirectly through Python's type system and library usage, and the saving mechanism is well-defined.",{"category":108,"check":148,"severity":29,"summary":149},"Unguarded Destructive Operations","The skill is not destructive; it generates and saves image files, which are not considered destructive operations.",{"category":54,"check":151,"severity":29,"summary":152},"Error Handling","The Python code includes necessary imports and error handling logic (e.g., `plt.close()` to free memory), and the instructions imply that failures would be reported through the execution environment.",{"category":54,"check":154,"severity":44,"summary":155},"Logging","The skill does not perform destructive actions or outbound calls that would require local audit logging.",{"category":157,"check":158,"severity":44,"summary":159},"Compliance","GDPR","The skill does not operate on personal data.",{"category":157,"check":161,"severity":29,"summary":162},"Target market","The skill is general-purpose for data visualization and does not contain any regional or jurisdictional logic. `targetMarket` is set to `global`.",{"category":58,"check":164,"severity":29,"summary":165},"Runtime stability","The skill specifies Python and its necessary libraries, and the use of `matplotlib.use('Agg')` ensures headless operation, promoting runtime stability.",1778054017873,"This skill enables the creation of various charts (bar, line, scatter, heatmap, histogram, box plot) and multi-panel analysis summaries using matplotlib and seaborn. It includes explicit initialization steps for headless rendering and output guidelines for saving charts to `/workspace/` and displaying them inline.","2.0.0","3.4.0","The data-visualization skill is exceptionally well-documented and production-ready, with clear instructions, comprehensive examples, and robust error handling. It adheres to best practices for security and portability, making it a high-quality extension.",95,"A high-quality data visualization skill that provides comprehensive examples and clear instructions for generating publication-quality charts.",[14,15,16,17,18,19],"global","verified",{"codeQuality":177,"collectedAt":178,"documentation":179,"maintenance":181,"popularity":182,"security":183,"testCoverage":185},{},1778054006851,{"descriptionLength":180,"readmeSize":8},210,{},{"smitheryUniqueUsers":8,"smitheryUseCount":8},{"hasNpmPackage":184,"smitheryVerified":184},false,{"hasCi":184,"hasTests":184},{"updatedAt":187},1778054053159,{"githubOwner":189,"githubRepo":190,"locale":23,"slug":191,"type":192},"langchain-ai","deepagents","data-visualization","skill",true,null,{"extract":196,"llm":199,"smithery":200},{"commitSha":197,"license":198},"b108c71d0c570e16c7050c1eac482e15dc35a5ed","MIT",{"promptVersionExtension":168,"promptVersionScoring":169,"score":171,"targetMarket":174,"tier":175},{"qualityScore":8,"totalActivations":8,"uniqueUsers":8,"useCount":8,"verified":184},{"repoId":202},"kd76dna2fvfbnjvzcpd2cwqnyd865xz7",{"_creationTime":204,"_id":202,"identity":205,"providers":207,"workflow":225},1777995558409.8704,{"githubOwner":189,"githubRepo":190,"sourceUrl":206},"https://github.com/langchain-ai/deepagents",{"discover":208,"github":212},{"sources":209},[210,211],"skills-sh","smithery",{"closedIssues90d":213,"forks":214,"homepage":215,"license":198,"openIssues90d":216,"pushedAt":217,"readmeSize":218,"stars":219,"topics":220},256,3140,"https://docs.langchain.com/deepagents",142,1778033560000,6232,22320,[190,221,222,223,19,224],"langchain","langgraph","ai","typescript",{"discoverAt":226,"extractAt":227,"githubAt":227,"updatedAt":227},1777995558409,1778053970345,{"anyEnrichmentAt":229,"extractAt":230,"githubAt":231,"llmAt":187,"smitheryAt":229,"updatedAt":187},1778053994907,1778053968286,1778053969344,[],[234,263,291,319,338,367],{"_creationTime":235,"_id":236,"community":237,"display":238,"identity":249,"providers":252,"relations":257,"workflow":259},1778053100136.2417,"k172f9k8w7xg3bzb9t320dj0cn866517",{"reviewCount":8},{"description":239,"installMethods":240,"name":241,"sourceUrl":242,"tags":243},"Use this skill when the user uploads Excel (.xlsx/.xls) or CSV files and wants to perform data analysis, generate statistics, create summaries, pivot tables, SQL queries, or any form of structured data exploration. Supports multi-sheet Excel workbooks, aggregation, filtering, joins, and exporting results to CSV/JSON/Markdown.",{},"Data Analysis Skill","https://github.com/bytedance/deer-flow/tree/HEAD/skills/public/data-analysis",[18,244,245,246,247,19,248],"excel","csv","sql","duckdb","analytics",{"githubOwner":250,"githubRepo":251,"locale":23,"slug":18,"type":192},"bytedance","deer-flow",{"extract":253,"llm":255},{"commitSha":254,"license":198},"1336872b15c25d45ebcb7c1cf72369c2bdd53187",{"promptVersionExtension":168,"promptVersionScoring":169,"score":256,"targetMarket":174,"tier":175},96,{"repoId":258},"kd789sm7egx1h0t1jag6zzhcq98656wv",{"anyEnrichmentAt":260,"extractAt":261,"githubAt":260,"llmAt":262,"updatedAt":262},1778053101076,1778053100136,1778053169012,{"_creationTime":264,"_id":265,"community":266,"display":267,"identity":276,"providers":280,"relations":285,"workflow":287},1778054663200.07,"k173n530j4dqq0ya45bpgxve95866jae",{"reviewCount":8},{"description":268,"installMethods":269,"name":270,"sourceUrl":271,"tags":272},"Transform raw data from CSVs, Google Sheets, or databases into executive-ready reports with visualizations, key metrics, trend analysis, and actionable recommendations. Creates data-driven narratives for leadership. Use when users need to turn spreadsheets into executive summaries or board reports.",{},"Executive Dashboard Generator","https://github.com/onewave-ai/claude-skills/tree/HEAD/executive-dashboard-generator",[18,273,14,274,275],"reporting","business-intelligence","executive-summary",{"githubOwner":277,"githubRepo":278,"locale":23,"slug":279,"type":192},"onewave-ai","claude-skills","executive-dashboard-generator",{"extract":281,"llm":283},{"commitSha":282,"license":198},"eb3d80be32b6cafcf0d5df1c1b8a95df75838271",{"promptVersionExtension":168,"promptVersionScoring":169,"score":284,"targetMarket":174,"tier":175},88,{"repoId":286},"kd71e43dj0b7ak5e55pyshxp4n864t6p",{"anyEnrichmentAt":288,"extractAt":289,"githubAt":288,"llmAt":290,"updatedAt":290},1778054667983,1778054663200,1778055270278,{"_creationTime":292,"_id":293,"community":294,"display":295,"identity":304,"providers":307,"relations":313,"workflow":315},1778053890293.347,"k171b0557ddsdezxc78vx226jd86622b",{"reviewCount":8},{"description":296,"installMethods":297,"name":298,"sourceUrl":299,"tags":300},"Create data-driven charts with Vega-Lite (declarative) and Vega (programmatic). Best for statistical visualization of numeric data — bar, line, scatter, heatmap, area, radar charts, and word clouds.",{},"Vega / Vega-Lite Visualizer","https://github.com/markdown-viewer/skills/tree/HEAD/vega",[14,15,301,302,303],"vega","vega-lite","data",{"githubOwner":305,"githubRepo":306,"locale":23,"slug":301,"type":192},"markdown-viewer","skills",{"extract":308,"llm":311},{"commitSha":309,"license":310},"c9c64d1fe2bcf630c5534a6e32f201fc3c2be0f9","GPL-3.0-or-later",{"promptVersionExtension":168,"promptVersionScoring":169,"score":284,"targetMarket":174,"tier":312},"flagged",{"repoId":314},"kd79wd89yemg344r17397n4hws865t8k",{"anyEnrichmentAt":316,"extractAt":317,"githubAt":316,"llmAt":318,"updatedAt":318},1778053890873,1778053890293,1778053931762,{"_creationTime":320,"_id":321,"community":322,"display":323,"identity":331,"providers":333,"relations":336,"workflow":337},1778053100136.2397,"k170dx3btrwts3r3v7e0g52nt9866gsg",{"reviewCount":8},{"description":324,"installMethods":325,"name":326,"sourceUrl":327,"tags":328},"This skill should be used when the user wants to visualize data. It intelligently selects the most suitable chart type from 26 available options, extracts parameters based on detailed specifications, and generates a chart image using a JavaScript script.",{},"Chart Visualization Skill","https://github.com/bytedance/deer-flow/tree/HEAD/skills/public/chart-visualization",[14,15,303,329,330],"javascript","api",{"githubOwner":250,"githubRepo":251,"locale":23,"slug":332,"type":192},"chart-visualization",{"extract":334,"llm":335},{"commitSha":254,"license":198},{"promptVersionExtension":168,"promptVersionScoring":169,"score":284,"targetMarket":174,"tier":175},{"repoId":258},{"anyEnrichmentAt":260,"extractAt":261,"githubAt":260,"llmAt":262,"updatedAt":262},{"_creationTime":339,"_id":340,"community":341,"display":342,"identity":352,"providers":355,"relations":361,"workflow":363},1778054691785.2554,"k179r3z09h3t0ed62ac4yy0qzn867erz",{"reviewCount":8},{"description":343,"name":344,"sourceUrl":345,"tags":346},"Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas","Excel Spreadsheet Operations","https://github.com/answerzhao/agent-skills/tree/HEAD/glm-skills/document-skills/xlsx",[347,244,348,245,349,350,351,18,14],"spreadsheet","xlsx","pandas","openpyxl","formulas",{"githubOwner":353,"githubRepo":354,"locale":23,"slug":348,"type":192},"answerzhao","agent-skills",{"extract":356,"llm":359},{"commitSha":357,"license":358},"aad73edbd0d9ffbc3d6a402b6eafa6dab96d5ebb","Proprietary",{"promptVersionExtension":168,"promptVersionScoring":169,"score":360,"targetMarket":174,"tier":312},75,{"repoId":362},"kd712v2g1pay70swwj0jpv2ggs864zgh",{"anyEnrichmentAt":364,"extractAt":365,"githubAt":364,"llmAt":366,"updatedAt":366},1778054692243,1778054691785,1778054738050,{"_creationTime":368,"_id":369,"community":370,"display":371,"identity":381,"providers":383,"relations":388,"workflow":390},1778053148350.4324,"k174n1jd975yr6a1gceyf5q3gd8674w1",{"reviewCount":8},{"description":372,"installMethods":373,"name":374,"sourceUrl":375,"tags":376},"Analyze spreadsheet data, generate insights, create visualizations, and build reports from Excel/CSV data.",{},"Data Analysis Assistant","https://github.com/claude-office-skills/skills/tree/HEAD/data-analysis",[303,377,347,244,14,378,379,380],"analysis","insights","finance","mcp",{"githubOwner":382,"githubRepo":306,"locale":23,"slug":18,"type":192},"claude-office-skills",{"extract":384,"llm":386},{"commitSha":385,"license":198},"9c4c7d5cd2813a8936bf2c9fdb174ea883b85a11",{"promptVersionExtension":168,"promptVersionScoring":169,"score":387,"targetMarket":174,"tier":175},98,{"repoId":389},"kd7fw7xbj58qc2z8whrrjptbed8659db",{"anyEnrichmentAt":391,"extractAt":392,"githubAt":391,"llmAt":393,"updatedAt":393},1778053151766,1778053148350,1778053561145]