[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"extension-plugin-huggingface-transformers-js-zh-CN":3,"guides-for-huggingface-transformers-js":750,"similar-k17745362t936z67p0p8w8mq0h86nmf0-zh-CN":751},{"_creationTime":4,"_id":5,"children":6,"community":7,"display":9,"evaluation":14,"identity":257,"isFallback":254,"parentExtension":262,"providers":297,"relations":301,"repo":302,"tags":748,"workflow":749},1778690773482.4854,"k17745362t936z67p0p8w8mq0h86nmf0",[],{"reviewCount":8},0,{"description":10,"installMethods":11,"name":12,"sourceUrl":13},"Run state-of-the-art machine learning models directly in JavaScript/TypeScript for NLP, computer vision, audio processing, and multimodal tasks. Works in Node.js and browsers with WebGPU/WASM using Hugging Face models.",{"claudeCode":12},"transformers-js","https://github.com/huggingface/skills",{"_creationTime":15,"_id":16,"extensionId":5,"locale":17,"result":18,"trustSignals":238,"workflow":255},1778691120894.9287,"kn71qht26xsjvt1fqgmv0x4g8586n4bj","en",{"checks":19,"evaluatedAt":205,"extensionSummary":206,"features":207,"nonGoals":213,"promptVersionExtension":217,"promptVersionScoring":218,"purpose":219,"rationale":220,"score":221,"summary":222,"tags":223,"targetMarket":231,"tier":232,"useCases":233},[20,25,28,31,35,38,43,47,50,53,57,61,64,68,71,74,77,80,83,86,90,94,98,102,106,109,112,115,119,122,125,128,131,134,137,141,145,150,153,157,160,163,166,169,172,175,178,181,184,187,191,194,197,201],{"category":21,"check":22,"severity":23,"summary":24},"Practical Utility","Problem relevance","pass","The description clearly states the extension addresses the problem of running ML models in JavaScript/TypeScript without a Python backend.",{"category":21,"check":26,"severity":23,"summary":27},"Unique selling proposition","The extension offers significant value by enabling direct ML model execution in JS/TS environments, which is beyond the default LLM capabilities.",{"category":21,"check":29,"severity":23,"summary":30},"Production readiness","The skill covers its stated use case of running ML models, including installation, core concepts, and advanced configuration, making it suitable for production workflows.",{"category":32,"check":33,"severity":23,"summary":34},"Scope","Single responsibility principle","The extension focuses on the domain of running ML models using Transformers.js, with a coherent set of features for this purpose.",{"category":32,"check":36,"severity":23,"summary":37},"Description quality","The description is concise, readable, and accurately reflects the capabilities of running ML models in JavaScript/TypeScript.",{"category":39,"check":40,"severity":41,"summary":42},"Invocation","Scoped tools","not_applicable","This is a plugin that bundles skills, not a direct tool provider with individual commands to evaluate for scoping.",{"category":44,"check":45,"severity":23,"summary":46},"Documentation","Configuration & parameter reference","The SKILL.md provides detailed explanations of core concepts, model selection, advanced configuration with `env` and `ModelRegistry`, and task IDs, covering parameters and options effectively.",{"category":32,"check":48,"severity":41,"summary":49},"Tool naming","This extension provides ML capabilities via a library and SKILL.md, not discrete tools with names to evaluate.",{"category":32,"check":51,"severity":41,"summary":52},"Minimal I/O surface","This extension functions as a library/skill interface, not a direct tool with a schema to evaluate for I/O surface.",{"category":54,"check":55,"severity":23,"summary":56},"License","License usability","The extension is licensed under the Apache-2.0 license, which is a permissive open-source license, clearly indicated in the LICENSE file and SKILL.md.",{"category":58,"check":59,"severity":23,"summary":60},"Maintenance","Commit recency","The last commit was made on 2026-05-12, which is within the last 3 months.",{"category":58,"check":62,"severity":23,"summary":63},"Dependency Management","The extension relies on `@huggingface/transformers` and potentially other NPM packages, which are standard and typically managed well via NPM.",{"category":65,"check":66,"severity":41,"summary":67},"Security","Secret Management","The extension does not appear to handle or require secrets directly; model loading is configured via environment variables or passed parameters, not secrets that need secure management.",{"category":65,"check":69,"severity":23,"summary":70},"Injection","The SKILL.md explicitly states that models are downloaded from Hugging Face Hub and implies they are treated as data, with no indication of executing arbitrary instructions from loaded content.",{"category":65,"check":72,"severity":23,"summary":73},"Transitive Supply-Chain Grenades","Models are downloaded from Hugging Face Hub and loaded as assets; there are no indications of runtime script execution from remote sources or symlinks outside the bundle.",{"category":65,"check":75,"severity":23,"summary":76},"Sandbox Isolation","The extension runs within a JavaScript/TypeScript environment (Node.js or browser) and interacts with models as data, without modifying files outside its intended scope.",{"category":65,"check":78,"severity":23,"summary":79},"Sandbox escape primitives","No detached process spawns or deny-retry loops are evident in the provided documentation or typical usage patterns of the Transformers.js library.",{"category":65,"check":81,"severity":23,"summary":82},"Data Exfiltration","The extension's primary function is model inference; there are no imperative instructions to read or submit confidential data to third parties.",{"category":65,"check":84,"severity":23,"summary":85},"Hidden Text Tricks","The bundled content and documentation appear to be free of hidden text tricks or obfuscation characters.",{"category":87,"check":88,"severity":41,"summary":89},"Hooks","Opaque code execution","This extension is a library interface and SKILL.md, not a plugin with hooks that would involve opaque code execution.",{"category":91,"check":92,"severity":23,"summary":93},"Portability","Structural Assumption","The skill primarily relies on standard JavaScript module loading and Hugging Face Hub model discovery, making it portable across compatible runtimes without assuming specific project structures.",{"category":95,"check":96,"severity":23,"summary":97},"Trust","Issues Attention","Opened 4 issues, closed 6 issues in the last 90 days, indicating active maintenance and a healthy closure rate.",{"category":99,"check":100,"severity":23,"summary":101},"Versioning","Release Management","The SKILL.md frontmatter includes a version '4.x' and points to a GitHub repository with recent commits and a tagged release, indicating clear versioning.",{"category":103,"check":104,"severity":41,"summary":105},"Code Execution","Validation","This extension is a JavaScript library and skill definition. Validation of inputs and outputs would be handled by the Transformers.js library itself, which is outside the scope of this plugin evaluation.",{"category":65,"check":107,"severity":23,"summary":108},"Unguarded Destructive Operations","The core functionality of running ML models is not inherently destructive, and there are no documented operations that require special confirmation gates.",{"category":103,"check":110,"severity":23,"summary":111},"Error Handling","The SKILL.md includes an 'Error Handling' section with examples of using try-catch blocks to manage potential errors during pipeline execution.",{"category":103,"check":113,"severity":23,"summary":114},"Logging","The SKILL.md mentions logging levels via `env.logLevel` and progress callbacks, suggesting configurable logging for operations.",{"category":116,"check":117,"severity":23,"summary":118},"Compliance","GDPR","The extension primarily processes ML models and user-provided data for inference, without explicit operations on personal data requiring specific sanitization beyond what the models themselves handle.",{"category":116,"check":120,"severity":23,"summary":121},"Target market","The extension is designed to run in various JavaScript environments (Node.js, browsers, Bun, Deno) and is not geographically restricted, hence 'global'.",{"category":91,"check":123,"severity":23,"summary":124},"Runtime stability","The skill explicitly lists compatibility with Node.js, Bun, Deno, and modern browsers, indicating multi-platform support.",{"category":44,"check":126,"severity":23,"summary":127},"README","The README provides a clear overview of the Hugging Face Skills repository, installation instructions for various agents, and details about the included skills.",{"category":32,"check":129,"severity":41,"summary":130},"Tool surface size","This extension is a plugin that bundles multiple skills, not a single tool with a surface area to evaluate.",{"category":39,"check":132,"severity":41,"summary":133},"Overlapping near-synonym tools","As a plugin bundling skills, this check is not applicable to the overall plugin structure.",{"category":44,"check":135,"severity":23,"summary":136},"Phantom features","All advertised features related to running ML models in JavaScript/TypeScript are directly supported by the Transformers.js library and its pipeline API as described.",{"category":138,"check":139,"severity":23,"summary":140},"Install","Installation instruction","The README provides clear installation instructions for Claude Code, Codex, Gemini CLI, and Cursor, including copy-paste examples.",{"category":142,"check":143,"severity":23,"summary":144},"Errors","Actionable error messages","The SKILL.md includes a dedicated section on 'Error Handling' with examples showing how to catch and interpret common errors.",{"category":146,"check":147,"severity":148,"summary":149},"Execution","Pinned dependencies","info","While the SKILL.md mentions NPM installation, it does not explicitly detail if dependencies are pinned via a lockfile for the extension's own scripts.",{"category":32,"check":151,"severity":41,"summary":152},"Dry-run preview","The core functionality is running ML models, which is not a state-changing operation requiring a dry-run preview.",{"category":154,"check":155,"severity":41,"summary":156},"Protocol","Idempotent retry & timeouts","The extension's functionality does not involve remote calls or state-changing operations that require idempotency or timeouts at this level of evaluation.",{"category":116,"check":158,"severity":23,"summary":159},"Telemetry opt-in","The documentation mentions logging levels via `env.logLevel` but does not indicate any mandatory or opt-out telemetry being sent externally.",{"category":39,"check":161,"severity":148,"summary":162},"Name collisions","The skill 'transformers-js' is distinct and does not appear to collide with Claude Code built-ins or other provided Hugging Face skills.",{"category":39,"check":164,"severity":41,"summary":165},"Hooks-off mechanism","This extension is a plugin that bundles skills and does not appear to expose a hooks-off mechanism at the plugin level.",{"category":39,"check":167,"severity":41,"summary":168},"Hook matcher tightness","This extension does not utilize hooks in a way that requires evaluating hook matcher tightness.",{"category":65,"check":170,"severity":41,"summary":171},"Hook security","There are no custom hooks implemented by this plugin that would require security evaluation.",{"category":87,"check":173,"severity":41,"summary":174},"Silent prompt rewriting","This extension does not implement any UserPromptSubmit hooks that would rewrite prompts.",{"category":65,"check":176,"severity":41,"summary":177},"Permission Hook","This extension does not implement any PermissionRequest hooks.",{"category":116,"check":179,"severity":41,"summary":180},"Hook privacy","The extension does not implement hooks that handle logging or telemetry data transmission.",{"category":103,"check":182,"severity":41,"summary":183},"Hook dependency","There are no custom hooks in this plugin that require evaluating code execution dependencies.",{"category":44,"check":185,"severity":23,"summary":186},"Feature Transparency","The README and SKILL.md clearly document the capabilities of running ML models with Transformers.js.",{"category":188,"check":189,"severity":23,"summary":190},"Convention","Layout convention adherence","The repository structure appears to follow standard conventions, with skills organized and metadata files present.",{"category":188,"check":192,"severity":41,"summary":193},"Plugin state","This extension primarily provides a skill interface and does not appear to manage persistent plugin state that would require `${CLAUDE_PLUGIN_DATA}`.",{"category":65,"check":195,"severity":41,"summary":196},"Keychain-stored secrets","The extension does not handle secrets that would require keychain storage; model loading parameters are user-provided.",{"category":198,"check":199,"severity":23,"summary":200},"Dependencies","Tagged release sourcing","The plugin references Hugging Face Hub models, which are versioned and available via specific identifiers, and the repository itself has tagged releases.",{"category":202,"check":203,"severity":23,"summary":204},"Installation","Clean uninstall","The extension is a JavaScript library and skill definition, and its installation/uninstallation would be managed by the agent's plugin system, which is expected to handle clean removal.",1778691120774,"This plugin provides the `transformers-js` skill, allowing users to run state-of-the-art machine learning models for various tasks (NLP, computer vision, audio, multimodal) directly in JavaScript/TypeScript environments like Node.js and browsers. It leverages WebGPU/WASM and models from Hugging Face Hub, offering pipeline APIs, model selection, device configuration, and quantization options.",[208,209,210,211,212],"Run ML models directly in JS/TS","Supports NLP, computer vision, audio, and multimodal tasks","Works in Node.js, browsers, Bun, and Deno","Leverages WebGPU/WASM for acceleration","Uses Hugging Face Hub models",[214,215,216],"Providing a Python-based ML server","Requiring a separate backend for model inference","Replacing native ML frameworks on their respective platforms","3.0.0","4.4.0","To empower JavaScript/TypeScript developers to integrate powerful machine learning capabilities into their applications without needing a separate Python backend or ML server.","The extension is well-documented, secure, and actively maintained. Minor info finding on dependency pinning for internal scripts.",96,"High-quality plugin enabling advanced ML model execution directly in JavaScript/TypeScript environments.",[224,225,226,227,228,229,230],"machine-learning","javascript","typescript","nlp","computer-vision","audio","multimodal","global","verified",[234,235,236,237],"Adding ML features to web applications","Client-side AI processing for privacy and speed","Prototyping ML workflows in JavaScript","Building multimodal AI applications",{"codeQuality":239,"collectedAt":241,"documentation":242,"maintenance":245,"security":251,"testCoverage":253},{"hasLockfile":240},false,1778691060910,{"descriptionLength":243,"readmeSize":244},218,9821,{"closedIssues90d":246,"forks":247,"hasChangelog":240,"openIssues90d":248,"pushedAt":249,"stars":250},6,663,4,1778593131000,10482,{"hasNpmPackage":240,"license":252,"smitheryVerified":240},"Apache-2.0",{"hasCi":254,"hasTests":240},true,{"updatedAt":256},1778691120894,{"basePath":258,"githubOwner":259,"githubRepo":260,"locale":17,"slug":12,"type":261},"skills/transformers-js","huggingface","skills","plugin",{"_creationTime":263,"_id":264,"community":265,"display":266,"identity":271,"parentExtension":274,"providers":275,"relations":291,"tags":293,"workflow":294},1778690773482.4824,"k17es3r8wd37t5rrwqcpp5kwrh86mxx8",{"reviewCount":8},{"description":267,"installMethods":268,"name":270,"sourceUrl":13},"Agent Skills for AI/ML tasks including dataset creation, model training, evaluation, and research paper publishing on Hugging Face Hub",{"claudeCode":269},"huggingface/skills","huggingface-skills",{"basePath":272,"githubOwner":259,"githubRepo":260,"locale":17,"slug":260,"type":273},"","marketplace",null,{"evaluate":276,"extract":285},{"promptVersionExtension":277,"promptVersionScoring":218,"score":278,"tags":279,"targetMarket":231,"tier":232},"3.1.0",95,[280,259,281,282,283,284],"ai-ml","datasets","models","research","developer-tools",{"commitSha":286,"marketplace":287,"plugin":289},"HEAD",{"name":270,"pluginCount":288},14,{"mcpCount":8,"provider":290,"skillCount":8},"classify",{"repoId":292},"kd72xwt5xnc0ktc4p7smzfcp3986m959",[280,281,284,259,282,283],{"evaluatedAt":295,"extractAt":296,"updatedAt":295},1778690814090,1778690773482,{"evaluate":298,"extract":300},{"promptVersionExtension":217,"promptVersionScoring":218,"score":221,"tags":299,"targetMarket":231,"tier":232},[224,225,226,227,228,229,230],{"commitSha":286},{"parentExtensionId":264,"repoId":292},{"_creationTime":303,"_id":292,"identity":304,"providers":305,"workflow":744},1778689536128.5474,{"githubOwner":259,"githubRepo":260,"sourceUrl":13},{"classify":306,"discover":737,"github":740},{"commitSha":286,"extensions":307},[308,321,330,338,346,354,362,370,378,386,394,402,410,415,423,431,474,483,489,495,512,518,525,567,578,597,603,623,635,659,717],{"basePath":272,"description":267,"displayName":270,"installMethods":309,"rationale":310,"selectedPaths":311,"source":320,"sourceLanguage":17,"type":273},{"claudeCode":269},"marketplace.json at .claude-plugin/marketplace.json",[312,315,317],{"path":313,"priority":314},".claude-plugin/marketplace.json","mandatory",{"path":316,"priority":314},"README.md",{"path":318,"priority":319},"LICENSE","high","rule",{"basePath":322,"description":323,"displayName":324,"installMethods":325,"rationale":326,"selectedPaths":327,"source":320,"sourceLanguage":17,"type":261},"skills/huggingface-llm-trainer","Train or fine-tune language models using TRL on Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment. Includes hardware selection, cost estimation, Trackio monitoring, and Hub persistence.","huggingface-llm-trainer",{"claudeCode":324},"inline plugin source from marketplace.json at skills/huggingface-llm-trainer",[328],{"path":329,"priority":319},"SKILL.md",{"basePath":331,"description":332,"displayName":333,"installMethods":334,"rationale":335,"selectedPaths":336,"source":320,"sourceLanguage":17,"type":261},"skills/huggingface-local-models","Use to select models to run locally with llama.cpp and GGUF on CPU, Mac Metal, CUDA, or ROCm. Covers finding GGUFs, quant selection, running servers, exact GGUF file lookup, conversion, and OpenAI-compatible local serving.","huggingface-local-models",{"claudeCode":333},"inline plugin source from marketplace.json at skills/huggingface-local-models",[337],{"path":329,"priority":319},{"basePath":339,"description":340,"displayName":341,"installMethods":342,"rationale":343,"selectedPaths":344,"source":320,"sourceLanguage":17,"type":261},"skills/huggingface-paper-publisher","Publish and manage research papers on Hugging Face Hub. Supports creating paper pages, linking papers to models/datasets, claiming authorship, and generating professional markdown-based research articles.","huggingface-paper-publisher",{"claudeCode":341},"inline plugin source from marketplace.json at skills/huggingface-paper-publisher",[345],{"path":329,"priority":319},{"basePath":347,"description":348,"displayName":349,"installMethods":350,"rationale":351,"selectedPaths":352,"source":320,"sourceLanguage":17,"type":261},"skills/huggingface-papers","Look up and read Hugging Face paper pages in markdown, and use the papers API for structured metadata like authors, linked models, datasets, Spaces, and media URLs when needed.","huggingface-papers",{"claudeCode":349},"inline plugin source from marketplace.json at skills/huggingface-papers",[353],{"path":329,"priority":319},{"basePath":355,"description":356,"displayName":357,"installMethods":358,"rationale":359,"selectedPaths":360,"source":320,"sourceLanguage":17,"type":261},"skills/huggingface-community-evals","Add and manage evaluation results in Hugging Face model cards. Supports extracting eval tables from README content, importing scores from Artificial Analysis API, and running custom evaluations with vLLM/lighteval.","huggingface-community-evals",{"claudeCode":357},"inline plugin source from marketplace.json at skills/huggingface-community-evals",[361],{"path":329,"priority":319},{"basePath":363,"description":364,"displayName":365,"installMethods":366,"rationale":367,"selectedPaths":368,"source":320,"sourceLanguage":17,"type":261},"skills/huggingface-best","Find the best AI model for any task by querying Hugging Face leaderboards and benchmarks. Recommends top models based on task type, hardware constraints, and benchmark scores.","huggingface-best",{"claudeCode":365},"inline plugin source from marketplace.json at skills/huggingface-best",[369],{"path":329,"priority":319},{"basePath":371,"description":372,"displayName":373,"installMethods":374,"rationale":375,"selectedPaths":376,"source":320,"sourceLanguage":17,"type":261},"skills/hf-cli","Execute Hugging Face Hub operations using the hf CLI. Download models/datasets, upload files, manage repos, and run cloud compute jobs.","hf-cli",{"claudeCode":373},"inline plugin source from marketplace.json at skills/hf-cli",[377],{"path":329,"priority":319},{"basePath":379,"description":380,"displayName":381,"installMethods":382,"rationale":383,"selectedPaths":384,"source":320,"sourceLanguage":17,"type":261},"skills/huggingface-trackio","Track and visualize ML training experiments with Trackio. Log metrics via Python API and retrieve them via CLI. Supports real-time dashboards synced to HF Spaces.","huggingface-trackio",{"claudeCode":381},"inline plugin source from marketplace.json at skills/huggingface-trackio",[385],{"path":329,"priority":319},{"basePath":387,"description":388,"displayName":389,"installMethods":390,"rationale":391,"selectedPaths":392,"source":320,"sourceLanguage":17,"type":261},"skills/huggingface-datasets","Explore, query, and extract data from any Hugging Face dataset using the Dataset Viewer REST API and npx tooling. Zero Python dependencies — covers split/config discovery, row pagination, text search, filtering, SQL via parquetlens, and dataset upload via CLI.","huggingface-datasets",{"claudeCode":389},"inline plugin source from marketplace.json at skills/huggingface-datasets",[393],{"path":329,"priority":319},{"basePath":395,"description":396,"displayName":397,"installMethods":398,"rationale":399,"selectedPaths":400,"source":320,"sourceLanguage":17,"type":261},"skills/huggingface-tool-builder","Build reusable scripts for Hugging Face Hub and API workflows. Useful for chaining API calls, enriching Hub metadata, or automating repeated tasks.","huggingface-tool-builder",{"claudeCode":397},"inline plugin source from marketplace.json at skills/huggingface-tool-builder",[401],{"path":329,"priority":319},{"basePath":403,"description":404,"displayName":405,"installMethods":406,"rationale":407,"selectedPaths":408,"source":320,"sourceLanguage":17,"type":261},"skills/huggingface-gradio","Build Gradio web UIs and demos in Python. Use when creating or editing Gradio apps, components, event listeners, layouts, or chatbots.","huggingface-gradio",{"claudeCode":405},"inline plugin source from marketplace.json at skills/huggingface-gradio",[409],{"path":329,"priority":319},{"basePath":258,"description":10,"displayName":12,"installMethods":411,"rationale":412,"selectedPaths":413,"source":320,"sourceLanguage":17,"type":261},{"claudeCode":12},"inline plugin source from marketplace.json at skills/transformers-js",[414],{"path":329,"priority":319},{"basePath":416,"description":417,"displayName":418,"installMethods":419,"rationale":420,"selectedPaths":421,"source":320,"sourceLanguage":17,"type":261},"skills/huggingface-vision-trainer","Train and fine-tune object detection models (RTDETRv2, YOLOS, DETR and others) and image classification models (timm and transformers models — MobileNetV3, MobileViT, ResNet, ViT/DINOv3) using Transformers Trainer API on Hugging Face Jobs infrastructure or locally. Includes COCO dataset format support, Albumentations augmentation, mAP/mAR metrics, trackio tracking, hardware selection, and Hub persistence.","huggingface-vision-trainer",{"claudeCode":418},"inline plugin source from marketplace.json at skills/huggingface-vision-trainer",[422],{"path":329,"priority":319},{"basePath":424,"description":425,"displayName":426,"installMethods":427,"rationale":428,"selectedPaths":429,"source":320,"sourceLanguage":17,"type":261},"skills/train-sentence-transformers","Train or fine-tune sentence-transformers models across all three architectures: SentenceTransformer (bi-encoder embeddings), CrossEncoder (rerankers), and SparseEncoder (SPLADE). Covers loss selection, hard-negative mining, evaluators, distillation, LoRA, Matryoshka, and Hugging Face Hub publishing.","train-sentence-transformers",{"claudeCode":426},"inline plugin source from marketplace.json at skills/train-sentence-transformers",[430],{"path":329,"priority":319},{"basePath":272,"description":267,"displayName":270,"installMethods":432,"license":252,"rationale":433,"selectedPaths":434,"source":320,"sourceLanguage":17,"type":261},{"claudeCode":270},"plugin manifest at .claude-plugin/plugin.json",[435,437,438,439,442,444,446,448,450,452,454,456,458,460,462,464,466,468,470,472],{"path":436,"priority":314},".claude-plugin/plugin.json",{"path":316,"priority":314},{"path":318,"priority":319},{"path":440,"priority":441},"skills/hf-cli/SKILL.md","medium",{"path":443,"priority":441},"skills/huggingface-best/SKILL.md",{"path":445,"priority":441},"skills/huggingface-community-evals/SKILL.md",{"path":447,"priority":441},"skills/huggingface-datasets/SKILL.md",{"path":449,"priority":441},"skills/huggingface-gradio/SKILL.md",{"path":451,"priority":441},"skills/huggingface-llm-trainer/SKILL.md",{"path":453,"priority":441},"skills/huggingface-local-models/SKILL.md",{"path":455,"priority":441},"skills/huggingface-paper-publisher/SKILL.md",{"path":457,"priority":441},"skills/huggingface-papers/SKILL.md",{"path":459,"priority":441},"skills/huggingface-tool-builder/SKILL.md",{"path":461,"priority":441},"skills/huggingface-trackio/SKILL.md",{"path":463,"priority":441},"skills/huggingface-vision-trainer/SKILL.md",{"path":465,"priority":441},"skills/train-sentence-transformers/SKILL.md",{"path":467,"priority":441},"skills/transformers-js/SKILL.md",{"path":469,"priority":314},".mcp.json",{"path":471,"priority":319},"agents/AGENTS.md",{"path":473,"priority":319},".cursor-plugin/plugin.json",{"basePath":475,"description":476,"displayName":477,"installMethods":478,"rationale":479,"selectedPaths":480,"source":320,"sourceLanguage":17,"type":482},"hf-mcp/skills/hf-mcp","Use Hugging Face Hub via MCP server tools. Search models, datasets, Spaces, papers. Get repo details, fetch documentation, run compute jobs, and use Gradio Spaces as AI tools. Available when connected to the HF MCP server.","hf-mcp",{"claudeCode":269},"SKILL.md frontmatter at hf-mcp/skills/hf-mcp/SKILL.md",[481],{"path":329,"priority":314},"skill",{"basePath":371,"description":484,"displayName":373,"installMethods":485,"rationale":486,"selectedPaths":487,"source":320,"sourceLanguage":17,"type":482},"Hugging Face Hub CLI (`hf`) for downloading, uploading, and managing models, datasets, spaces, buckets, repos, papers, jobs, and more on the Hugging Face Hub. Use when: handling authentication; managing local cache; managing Hugging Face Buckets; running or scheduling jobs on Hugging Face infrastructure; managing Hugging Face repos; discussions and pull requests; browsing models, datasets and spaces; reading, searching, or browsing academic papers; managing collections; querying datasets; configuring spaces; setting up webhooks; or deploying and managing HF Inference Endpoints. Make sure to use this skill whenever the user mentions 'hf', 'huggingface', 'Hugging Face', 'huggingface-cli', or 'hugging face cli', or wants to do anything related to the Hugging Face ecosystem and to AI and ML in general. Also use for cloud storage needs like training checkpoints, data pipelines, or agent traces. Use even if the user doesn't explicitly ask for a CLI command. Replaces the deprecated `huggingface-cli`.",{"claudeCode":269},"SKILL.md frontmatter at skills/hf-cli/SKILL.md",[488],{"path":329,"priority":314},{"basePath":363,"description":490,"displayName":365,"installMethods":491,"rationale":492,"selectedPaths":493,"source":320,"sourceLanguage":17,"type":482},"Use when the user asks about finding the best, top, or recommended model for a task, wants to know what AI model to use, or wants to compare models by benchmark scores. Triggers on: \"best model for X\", \"what model should I use for\", \"top models for [task]\", \"which model runs on my laptop/machine/device\", \"recommend a model for\", \"what LLM should I use for\", \"compare models for\", \"what's state of the art for\", or any question about choosing an AI model for a specific use case. Always use this skill when the user wants model recommendations or comparisons, even if they don't explicitly mention HuggingFace or benchmarks.\n",{"claudeCode":269},"SKILL.md frontmatter at skills/huggingface-best/SKILL.md",[494],{"path":329,"priority":314},{"basePath":355,"description":496,"displayName":357,"installMethods":497,"rationale":498,"selectedPaths":499,"source":320,"sourceLanguage":17,"type":482},"Run evaluations for Hugging Face Hub models using inspect-ai and lighteval on local hardware. Use for backend selection, local GPU evals, and choosing between vLLM / Transformers / accelerate. 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