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Apply to multi-step work (sweeps, migrations, runs of similar edits) and to how you stack commits and PRs. Break work into small units that each end in a verifiable state, check each before the next, and order delivery so the sequence proves itself to a reviewer.
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用于排查多个EVM链上代币余额和价格的数量级偏差，通过运行时获取小数位数、按链和地址缓存、精确计算及统一单位，避免换算结果错位。
从服务运维中的实际问题出发选择指标，为Grafana或SigNoz创建监控仪表板，按用途组织面板，帮助判断服务健康状况、延迟、吞吐量和资源瓶颈。
将文本拆分为供AI模型使用的小单位，并转换为数字序列。支持批量处理、自定义词表训练、原文位置对应，以及通过截断和填充统一输入长度。
支持整理、共享和搜索Box中的文件，并通过Box AI总结文档、回答问题及提取信息。还可保存元数据、批量处理文件，以及开发与Box连接的应用。
Inspect AI costs, token usage—the units used to measure model input and output—and call logs from the OmniRoute command line. Filter records, review spending by connection, and export usage reports for further review.
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通过OmniRoute命令行查看AI费用明细、令牌用量和调用日志，按时间、提供商或模型筛选信息，检查各连接支出，并导出使用报告。
根据自有设备的耗电、购置成本和实测生成速度，估算本地模型每百万词元的费用，并按不同利用率与外部API比较，判断成本平衡点。
Work with large scientific arrays by storing data in smaller blocks and reading selected portions. Guides compression, cloud storage, format migration, and NumPy, Dask, or Xarray integration while preserving dimensions, units, and other metadata.
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Simulate quantum dynamics, steady states, and spectra with QuTiP 5. The skill guides solver selection and checks physical assumptions, units, state validity, and numerical convergence so local simulation results can be reviewed with their limitations.
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Plan experiments before collecting data. Helps choose study designs, randomly assign subjects or samples, organize treatment combinations, and generate reproducible schedules while checking for confounding and repeated measurements incorrectly counted as independent samples.
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Review and improve statistical reporting in manuscript methods, results, and figure captions. It checks sample definitions, repeated measurements, tests, and uncertainty, then provides revised wording and identifies missing information or issues reviewers may raise.
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Build Java applications that store, query, update, and delete data in Azure Cosmos DB. Covers synchronous and asynchronous clients, partition keys for distributing data, consistency settings, request usage, and error handling.
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Use Python to analyze astronomical data, convert celestial coordinates, units, and times, and read or write FITS astronomy files. It also guides catalog matching and calculations of cosmic distances and ages using cosmological models.
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Build concurrent Go applications with goroutines, lightweight execution units, and channels for communication. Apply patterns for worker pools, cancellation, synchronization, and orderly shutdown, and investigate race conditions when concurrent operations access shared data.
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Consult a field reference for slide JSON, the structured data behind each page. It explains where content and styling live, how edits are validated, and why a saved change may display differently or have no visible effect.
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Split a large goal into clearly bounded tasks that can run in parallel. Coordinate existing agent and worktree tools, then combine and verify the results. The skill starts only when explicitly requested.
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Create and fix Adobe Illustrator automation scripts using ExtendScript, Adobe’s JavaScript-based scripting language. Automate changes to artwork, text, layers, and artboards, process multiple files, and prepare exports such as PDF, SVG, and PNG.
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Rewrite lengthy prompts, tool descriptions, and agent instructions into compact text while preserving requirements, exceptions, and exact values. The process records removed content and compares token counts, the units models use to measure text length.
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Use Wireshark and tshark to capture and inspect network packets, the small units of network communication. Investigate suspicious connections and protocol problems, extract transferred files, and export evidence and summaries for incident investigations.
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Design pricing and subscription plans around customer value and willingness to pay. The skill guides pricing surveys, billing units, feature bundles, free plans, trials, and price increases, helping organize options and define how to evaluate changes.
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Prepare text for language models using HuggingFace Tokenizers, which splits text into model-readable units. Train custom vocabularies, process batches, track original text positions, and configure input lengths for use with transformers.
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Build text tokenizers that split multilingual text into small units for AI models. Learn how to train SentencePiece on raw text, configure BPE or Unigram splitting methods, and convert text to token IDs and back.
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Analyze CSV files with Python and get concise numerical summaries. The skill checks column structure before calculating requested aggregates, includes units when available, and explains assumptions when data is missing or incorrectly formatted.
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