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Use NotebookLM through MCP or a local REST API to run cited Q&A, generate Studio artifacts, and manage high-volume research batches.

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Sync high-value dev knowledge (skills, decisions, lessons) into Google NotebookLM for cloud recall, podcasts, and flashcards. Pairs with Dockit/deep-search. Use for NotebookLM, nlm, knowledge base, skill sync, or cross-machine AI memory.

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Validate the GenAI stack (services, authentication, models, notebooks, GPU). Arguments: [all|services|auth|models|notebooks|vram] [--full] [--auth-only] [--nodes-only] [--notebooks]

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Execute Jupyter notebooks using local scripts or MCP Jupyter. Arguments: <notebook_path> [--mode] [--cells] [--timeout] [--batch] [--save]

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Skill de pesquisa profunda alimentado por NotebookLM MCP. Conduz pesquisa estruturada em múltiplas fontes (análise de mercado, inteligência competitiva, análise de tendências, pesquisa de prospects) usando Google NotebookLM como mecanismo de pesquisa, depois entrega briefs formatados e artefatos opcionais de estúdio (slides, podcasts de áudio, vídeos, infográficos, relatórios, mapas mentais).

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Set up notebook-connector configuration for Exasol AI workflows through the Secrets Python API. Covers secure config store (`scs`) creation, the `AILabConfig` and `StorageBackend` key sources, backend-specific config values such as `db_host_name`, `db_schema`, `storage_backend`, and `huggingface_token`, Python validation, and handoff to downstream notebook-connector skills.

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Учебные аудиоподкасты для Антона в NotebookLM: выбирает, чему учить (труба собеседований, дыры сверки), пишет пакет и промпт ведущим, генерирует аудио RU+EN через CLI notebooklm, кладёт в волт, ведёт учебный план и YouTube-очередь. Триггеры: /teach-podcast, /teach, сделай подкаст, обучи меня, подкаст в машину, что мне послушать. НЕ /notebooklm (общий слой артефактов).

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Drive NotebookLM over a programmatic CLI with no browser: turn a vault slice into an audio overview, study guide or mind map, and fold the artifacts back into the vault. Browser automation is the fallback if CLI auth breaks. Triggers: "/notebooklm", "make an audio digest of <topic>", "podcast from the vault".

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Review Jupyter notebooks for side effects, dependencies, and safe execution strategy before running or editing them.

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Review homework notebooks for completeness, reproducibility, safe execution, and academic-integrity boundaries.

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Use this skill to query your Google NotebookLM notebooks directly from Claude Code for source-grounded, citation-backed answers from Gemini. Browser automation, library management, persistent auth. Drastically reduced hallucinations through document-only responses.

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帮助将机器学习实验整理为生产系统，明确数据规格、可复现训练、质量评估、部署、监控与回退，并形成实施计划和审查事项。

• 将实验代码整理为训练流水线
• 制定模型发布前的质量标准
• 调查数据泄漏与预处理差异

将文件编辑范围限定在指定目录内，阻止范围外的编辑、写入及笔记本修改，帮助调试或单个模块修复避免无关改动，限制会持续到主动解除。

• 缩小调试时的编辑范围
• 只修改指定模块
• 防止误改无关文件

Automate Joplin note management through its terminal application. Create and organize notes and notebooks, update to-dos, manage tags and attachments, and run synchronization or import and export workflows with structured results.

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• Create notes and organize them into notebooks
• Update to-do completion status
• Organize notes with tags and attachments

Helps build LabArchives connections for electronic lab notebooks and laboratory inventory. Guides endpoint selection, request signing for authentication, and user authorization, with local tools to inspect container files and prepare redacted request plans before remote operations.

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• Plan an electronic lab notebook API connection
• Check authentication for laboratory inventory requests
• Inspect an LA container file locally

Automate lab data tasks in Benchling using its Python SDK and REST API. Import and export sequences, inspect sample inventory, and work with electronic lab notebooks and workflow tasks while checking schemas, permissions, and operation results.

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• Importing DNA sequences from FASTA files
• Auditing sample inventory at a storage location
• Exporting sequences for a specific schema to CSV

Save research findings, fixes, and decisions in a shared Markdown notebook on disk. Search and organize notes across sessions, record when they inform actual work, and let unused notes expire automatically.

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• Saving research findings for future sessions
• Reusing fixes for difficult bugs
• Recording design decisions and their reasoning

Search an agent's long-term memory for people, projects, and other facts. Save important corrections immediately, update outdated entries, and remove errors or duplicates while respecting which notebooks the current conversation can read or change.

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• Recall a person's role or current work
• Save facts that should be remembered later
• Correct outdated or inaccurate information

Choose, build, and review charts that answer a clear analytical question. The skill checks chart types, labels, units, colors, and data sufficiency, then refines the visual in its intended report, dashboard, notebook, or other output.

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• Choose a chart for a specific analytical question
• Improve charts that are hard to interpret
• Review charts for reports or dashboards

Prepare scientific figures for papers, reports, and saved deliverables by checking data fidelity, chart choice, labels, axes, and color consistency. Verify exported figures for overlapping text and readability while keeping fonts, palettes, and framing configurable.

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• Preparing scientific figures for a paper or report
• Checking excluded data and summary statistics
• Improving labels, axes, and color consistency

Save decisions, research findings, and work updates to Obsidian, then update related notes, daily entries, and task boards. Maintain existing pages, preserve changing facts with their history, and check for duplicates and broken links.

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• Save decisions and tasks from a conversation
• Connect development logs to project notes
• Check a vault for duplicates and broken links

Search Kaggle datasets, competitions, notebooks, and models through its official command-line tool. Download public data into a chosen directory and preserve audit records and file hashes, identifiers used to check downloaded files.

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• Finding Kaggle datasets and inspecting metadata
• Downloading public data into a chosen directory
• Discovering competitions, notebooks, and models

Converts LabArchives notebook data, entry metadata, and authorized ELN exports into manuscript-ready academic writing outputs such as Methods sections, data-availability statements, reproducibility appendices, experiment timelines, and submission support notes. Optional bundled scripts can be used to collect or validate source notebook data before writing.

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Authoring conventions for exploratory data analysis notebooks and analytical dashboards, covering section sequence, visualization selection, scale thresholds, caching and state, and dashboard validation budgets. Use when composing or reviewing an EDA notebook, an analytical dashboard, or a dashboard test pass.

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