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Found 15 Skills
飞书电子表格：创建和操作电子表格。创建表格并写入表头和数据、读取和写入单元格、追加行数据、在已知电子表格中查找单元格内容、导出表格文件。当用户需要创建电子表格、批量读写数据、在已知表格中查找内容、导出或下载表格时使用。若用户是想按名称或关键词搜索云空间里的表格文件，请改用 lark-doc 的 docs +search 先定位资源。
Guidance for counting tokens in datasets, particularly from HuggingFace or similar sources. This skill should be used when tasks involve counting tokens in datasets, understanding dataset schemas, filtering by categories/domains, or working with tokenizers. It helps avoid common pitfalls like incomplete field identification and ambiguous terminology interpretation.
Generate synthetic training data when you don't have enough real examples. Use when you're starting from scratch with no data, need a proof of concept fast, have too few examples for optimization, can't use real customer data for privacy or compliance, need to fill gaps in edge cases, have unbalanced categories, added new categories, or changed your schema. Covers DSPy synthetic data generation, quality filtering, and bootstrapping from zero.
Query Google Analytics 4 (GA4) data via the Analytics Data API. Use when you need to pull website analytics like top pages, traffic sources, user counts, sessions, conversions, or any GA4 metrics/dimensions. Supports custom date ranges and filtering.
Search for financial reports using Exa advanced search. Near-full filter support for finding SEC filings, earnings reports, and financial documents. Use when searching for 10-K filings, quarterly earnings, or annual reports.
Convert data between formats (JSON, XML, CSV, YAML, TOML). Use when transforming data structures or migrating between data formats.
彙整今日中國宏觀經濟新聞消息，從華爾街日報、36氪等來源抓取並篩選宏觀相關新聞，輸出雜誌風格的新聞摘要。適用於交易/研究開盤前快速掌握中國宏觀動態。
Implement Syncfusion Blazor Dropdown Tree component for hierarchical data selection with single/multi-selection, checkboxes, filtering, and advanced customization. Use this skill whenever the user needs to display tree-structured data in a dropdown, select single or multiple hierarchical items, implement checkboxes for multi-item selection, filter tree data, customize templates, bind to remote data sources, or handle tree-related events and validation.
Query Chrome browsing history with natural language. Filter by date range, article type, keywords, and specific sites.
Summarize deep research results into markdown report, cover all fields, skip uncertain values.
Process Excel files, supporting reading, analysis, statistics and export of xlsx data
Which of these addresses are smart money? Batch-profile a list in one call.