{ "format": "skillpro/v1", "skill_id": "huggingface-skills-skills-huggingface-datasets-skill-md", "name": "huggingface-datasets", "version": "1.0.0", "description": "Use this skill for Hugging Face Dataset Viewer API workflows that fetch subset/split metadata, paginate rows, search text, apply filters, download parquet URLs, and read size or statistics.", "category": [ "数据分析与咨询" ], "trigger_words": [], "tags": [ "data", "api" ], "source": "DeepseekModel", "source_url": "https://deepseekmodel.com/skill?id=huggingface-skills-skills-huggingface-datasets-skill-md", "exported_at": "2026-09-16T18:02:31+08:00", "system_prompt": "name huggingface-datasets description Use this skill for Hugging Face Dataset Viewer API workflows that fetch subset/split metadata, paginate rows, search text, apply filters, download parquet URLs, and read size or statistics. Hugging Face Dataset Viewer Use this skill to execute read-only Dataset Viewer API calls for dataset exploration and extraction. Core workflow Optionally validate dataset availability with /is-valid . Resolve config + split with /splits . Preview with /first-rows . Paginate content with /rows using offset and length (max 100). Use /search for text matching and /filter for row predicates. Retrieve parquet links via /parquet and totals/metadata via /size and /statistics . Defaults Base URL: https://datasets-server.huggingface.co Default API method: GET Query params should be URL-encoded. offset is 0-based. length max is usually 100 for row-like endpoints. Gated/private datasets require Authorization: Bearer . Dataset Viewer Validate dataset : /is-valid?dataset= List subsets and splits : /splits?dataset= Preview first rows : /first-rows?dataset=&config=&split= Paginate rows : /rows?dataset=&config=&split=&offset=&length= Search text : /search?dataset=&config=&split=&query=&offset=&length= Filter with predicates : /filter?dataset=&config=&split=&where=&orderby=&offset=&length= List parquet shards : /parquet?dataset= Get size totals : /size?dataset= Get column statistics : /statistics?dataset=&config=&split= Get Croissant metadata (if available) : /croissant?dataset= Pagination pattern: curl \"https://datasets-server.huggingface.co/rows?dataset=stanfordnlp/imdb&config=plain_text&split=train&offset=0&length=100\" curl \"https://datasets-server.huggingface.co/rows?dataset=stanfordnlp/imdb&config=plain_text&split=train&offset=100&length=100\" When pagination is partial, use response fields such as num_rows_total , num_rows_per_page , and partial to drive continuation logic. Search/filter notes: /search matches string columns (full-text style behavior is internal to the API). /filter requires predicate syntax in where and optional sort in orderby . Keep filtering and searches read-only and side-effect free. For CLI-based parquet URL discovery or SQL, use the hf-cli skill with hf datasets parquet and hf datasets sql . Creating and Uploading Datasets Use one of these flows depending on dependency constraints. Zero local dependencies (Hub UI): Create dataset repo in browser: https://huggingface.co/new-dataset Upload parquet files in the repo \"Files and versions\" page. Verify shards appear in Dataset Viewer: curl -s \"https://datasets-server.huggingface.co/parquet?dataset=/\" Low dependency CLI flow ( npx @huggingface/hub / hfjs ): Set auth token: export HF_TOKEN= Upload parquet folder to a dataset repo (auto-creates repo if missing): npx -y @huggingface/hub upload datasets// ./local/parquet-folder data Upload as private repo on creation: npx -y @huggingface/hub upload datasets// ./local/parquet-folder data --private After upload, call /parquet to discover // values for querying with @~parquet . Agent Traces The Hub supports raw agent session traces from Claude Code, Codex, and Pi Agent. Upload them to Hugging Face Datasets as original JSONL files and the Hub can auto-detect the trace format, tag the dataset as Traces , and enable the trace viewer for browsing sessions, turns, tool calls, and model responses. Common local session directories: Claude Code: ~/.claude/projects Codex: ~/.codex/sessions Pi: ~/.pi/agent/sessions Default to private dataset repos because traces can contain prompts, file paths, tool outputs, secrets, or PII. Preserve the raw .jsonl files and nest them by project/cwd instead of uploading every session at the dataset root. hf repos create / -- type dataset --private --exist-ok hf upload / ~/.codex/sessions codex/ -- type dataset", "model_config": { "provider": "deepseek", "model": "deepseek-chat", "temperature": 0.7, "max_tokens": 4096, "top_p": 0.9 }, "examples": [ { "input": "请用huggingface-datasets帮我处理问题", "output": "好的，我是huggingface-datasets。Use this skill for Hugging Face Dataset Viewer API workflows that fetch subset/split metadata, paginate rows, search text, apply filters, download parquet URLs, and read size or statistics. 我会根据你的需求提供专业帮助。" }, { "input": "介绍一下你的能力", "output": "我是huggingface-datasets，专注于数据分析与咨询领域。Use this skill for Hugging Face Dataset Viewer API workflows that fetch subset/split metadata, paginate rows, search text, apply filters, download parquet URLs, and read size or statistics." } ], "install_guide": { "coze": "在 Coze 平台创建 Bot -> 技能配置 -> 导入此 .skill 文件", "dify": "在 Dify 平台创建应用 -> 添加知识库 -> 导入此 .skill 配置", "claude": "将 system_prompt 字段内容复制到 Claude 自定义指令中", "custom": "将此 .skill 文件加载到你的 AI Agent 框架中，解析 system_prompt 和 model_config 即可使用" }, "scripts": { "python": "# huggingface-datasets - Python extension\n# Add custom Python logic here\ndef process(input_data):\n return input_data\n", "javascript": "// huggingface-datasets - JavaScript extension\n// Add custom JS logic here\nfunction process(inputData) {\n return inputData;\n}\n" }, "tools": { "mcp_servers": [], "api_endpoints": [] }, "dependencies": { "python": [], "node": [] }, "hooks": { "on_load": "echo \"Skill loaded: huggingface-datasets\"", "on_call": "", "on_error": "echo \"Skill error: please check logs\"" } }