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Implement and execute approved research Experiment, Tuning, or Design Cards with reproducible logs, metrics, environment, and artifacts. Use for bounded coding, debugging, and runs; not for changing claims, priorities, budgets, or the Research Spine.
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Use when the user needs to search or navigate code with Sourcegraph MCP tools. Provides disciplined search workflows for finding implementations, understanding systems, debugging issues, fixing bugs, and reviewing code.
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Build applications and agents with Exa's API Platform: search, contents, answer, context, Agent API, monitors, websets, OpenAI-compatible endpoints, and exa-py / exa-js. Use when choosing Exa endpoints, writing Exa API calls, integrating semantic web search or research into products, or debugging Exa request shapes. Load references/ on demand for endpoint details.
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Search and analyze Estuary task logs with jq filtering. Use when investigating task failures, debugging connector errors, analyzing behavior patterns, or streaming live logs. Use when user says "check logs", "show me logs", "task failing", "why is my capture failing", "why is my materialization failing", "error messages", "why did it fail", "search task logs", "shard failed", "follow logs", "increase log level", "debug logging", "is this log message normal", "what does this message mean", "connection timeout", or "i/o timeout".
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使用 Kotlin Coroutines 和 Flow 实现 Android 与 Kotlin Multiplatform 的异步任务和数据更新，涵盖并行加载、界面状态、取消、错误处理及测试。
按连接、认证和收发数据等层次排查REST与GraphQL API故障，整理复现命令、原因及修复建议，并编写回归测试以检测问题是否再次出现。
梳理Hermes Docker镜像中s6的服务监控配置，帮助添加常驻服务，检查各配置档案gateway的启动与重启故障，并排查文件所有权和退出码问题。
帮助实现和排查使用PyTorch FSDP的大模型分布式训练代码。通过源自官方文档的说明与示例，比较分片策略，并查看混合精度和训练状态保存的实现。
Search current library documentation and code examples with Context7 CLI, a command-line tool. Find API usage and configuration guidance, select available version-specific documentation, and prioritize examples in the programming language you use.
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Find current documentation and code examples through the Context7 MCP server. Look up library setup, API usage, migration steps, and library-specific problems, using documentation for the requested version when available.
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Retrieve current documentation and code examples from Context7 for libraries, frameworks, and developer tools. Use the results to answer questions about API syntax, configuration, installation, version migration, and library-specific problems.
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Plan Claude Code agent teams by choosing team size, roles, and agent types with the tools each task needs. Preset compositions cover reviews, debugging, implementation, research, security audits, and migrations, alongside display settings for local or CI environments.
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Investigate SGLang runs that freeze across multiple GPUs. It uses stack traces, communication logs, GPU memory dumps, and comparisons between processes to locate state differences, trace their causes, and guide fixes.
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Investigate production issues by searching Datadog logs, querying metrics, and following request traces across services. Compare error counts across time periods, inspect surrounding logs, and manage dashboards through a command-line tool.
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Investigate bugs using a graph of code relationships. Find relevant functions, trace calls and execution paths, check recent changes, and assess what a proposed fix could affect before reading and changing the implementation.
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Search past coding sessions across Claude Code, Codex, and Cursor to recover earlier attempts, failed approaches, decisions, and findings. It filters history by topic and time, then summarizes technical details relevant to the question.
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Build and maintain interfaces with shadcn/ui by finding, adding, and combining components. The skill uses project settings, component documentation, and change previews to guide styling, debugging, preset changes, and updates that preserve local edits.
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Turn plain-language requests into Cloud Logging queries for Google Cloud. Generate service-specific filters to find errors, investigate issues, or review audit logs using LQL, the language used to search these logs.
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Use Phoenix to record execution traces, detailed records of an AI application's operations, and investigate problems. Evaluate answers on datasets, compare prompts and models, and set up monitoring through a self-hosted server.
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Guides adapting OpenPI robot models to custom datasets and serving them to produce actions from observations. Covers JAX and PyTorch training, checkpoint conversion, and troubleshooting for normalization statistics and GPU memory.
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Get guidance on adapting LLMs through additional training with LLaMA-Factory. The skill covers a visual interface requiring no code, LoRA and QLoRA training methods, and documentation-based help with implementation, features, and debugging.
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Get guidance on fine-tuning language models with Unsloth, including LoRA and QLoRA methods for training with fewer resources. The skill points to documentation for understanding APIs, implementing training code, debugging problems, and exploring speed and memory optimizations.
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Add PyTorch FSDP2 to training scripts so model state can be split across GPUs. Covers distributed initialization, mixed precision, CPU offloading, and checkpoint saving and loading for models that exceed a single GPU's memory.
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Build and maintain interfaces with shadcn/ui by finding, adding, and combining components. The skill uses project settings, component documentation, and change previews to guide styling, debugging, preset changes, and updates that preserve local edits.
中文简介正在准备中。当前显示英语简介。