「ebooks」の検索結果

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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Open-source embedding database for AI applications. Store embeddings and metadata, perform vector and full-text search, filter by metadata. Simple 4-function API. Scales from notebooks to production clusters. Use for semantic search, RAG applications, or document retrieval. Best for local development and open-source projects.

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Develop and deploy Lakeflow Jobs on Databricks via DABs, Python SDK, or the CLI. Use when creating data engineering jobs with notebooks, Python wheels, SQL, dbt, or pipelines. Invoke BEFORE starting implementation.

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Migrate Databricks workloads from classic compute to serverless compute. Use when migrating notebooks, jobs, pipelines, or Scala JARs (`spark_jar_task`) from classic clusters to serverless, checking if existing code is serverless-compatible, or writing new serverless-compatible code. Provides concrete fixes for the serverless Spark Connect architecture and guides the full migration. Not for classic DBR version upgrades or cluster configuration changes within classic compute.

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When the user wants to plan, evaluate, or build a free tool for marketing purposes — lead generation, SEO value, or brand awareness. Also use when the user mentions "engineering as marketing," "free tool," "marketing tool," "calculator," "generator," "interactive tool," "lead gen tool," "build a tool for leads," "free resource," "ROI calculator," "grader tool," "audit tool," "should I build a free tool," or "tools for lead gen." Use this whenever someone wants to build something useful and give it away to attract leads or earn links. For downloadable content lead magnets (ebooks, checklists, templates), see lead-magnets.

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Query Google NotebookLM notebooks for source-grounded, citation-backed answers from user-uploaded documents. Manages notebook library, handles Google authentication, and supports smart discovery. Works standalone via /blog notebooklm or internally from blog-write and blog-researcher for Tier 1 research data. Falls back gracefully when not configured. Use when user says "notebooklm", "notebook", "query notebook", "ask notebook", "notebook research", "source grounded research", "document query", "notebook library".

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This skill should be considered when you need to normalize testing engineers' written defect reasons following the provided product codebooks. This skill will correct the typos, misused abbreviations, ambiguous descriptions, mixed Chinese-English text or misleading text and provide explanations. This skill will do segmentation, semantic matching, confidence calibration and station validation.

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Use when reviewing Python changes - Django, Flask and FastAPI handlers, subprocess, SQL, Jinja2, format strings, and data/ML code that loads pickles, models, notebooks or remote model code

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Unified Kaggle skill. Use when the user explicitly mentions Kaggle, kaggle.com, a Kaggle URL, Kaggle competitions, Kaggle datasets/models/notebooks, Kaggle forums/discussions/writeups, Kaggle benchmarks, hackathons hosted on Kaggle, Kaggle badges, or Kaggle account setup. Do not use for generic ML, GPU/TPU, notebook, dataset, benchmark, or data-science tasks unless the user clearly ties them to Kaggle.

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Use this skill when a file has been uploaded but its content is NOT in your context — only its path at /mnt/user-data/uploads/ is listed in an uploaded_files block. This skill is a router: it tells you which tool to use for each file type (pdf, docx, xlsx, csv, json, images, archives, ebooks) so you read the right amount the right way instead of blindly running cat on a binary. Triggers: any mention of /mnt/user-data/uploads/, an uploaded_files section, a file_path tag, or a user asking about an uploaded file you have not yet read. Do NOT use this skill if the file content is already visible in your context inside a documents block — you already have it.

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Builds local-first note vault retrieval for Obsidian, markdown notebooks, and NotebookLM-adjacent exports. Use when packaging notes into LLM-ready context.

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Generate SQL validation notebooks for dbt changes. Pass a GitHub PR URL or local dbt repo path.

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Use this when managing Python dependencies with uv, running tests with pytest, linting with ruff, formatting code, type checking with mypy, or executing notebooks.

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When the user wants to plan, evaluate, or build a free tool for marketing purposes — lead generation, SEO value, or brand awareness. Also use when the user mentions "engineering as marketing," "free tool," "marketing tool," "calculator," "generator," "interactive tool," "lead gen tool," "build a tool for leads," "free resource," "ROI calculator," "grader tool," "audit tool," "should I build a free tool," or "tools for lead gen." Use this whenever someone wants to build something useful and give it away to attract leads or earn links. For downloadable content lead magnets (ebooks, checklists, templates), see lead-magnets.

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Configures ExDoc for Elixir projects including mix.exs setup, extras, groups, cheatsheets, and livebooks. Use when setting up or modifying ExDoc documentation generation.

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Field observation, data collection, and research methods for geographic inquiry. Covers site selection and sampling strategies, field observation techniques (landscape reading, transects, quadrats), survey and interview methods for human geography, GPS and field mapping, environmental monitoring and instrumentation, data recording and field notebooks, ethical considerations in fieldwork, and the integration of field data with GIS analysis. Use when planning geographic field research, designing data collection protocols, evaluating field evidence, or connecting field observations to broader geographic analysis.

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Apply best practices for Jupyter notebooks: cell ordering, reproducibility, parameterisation. Use when working with .ipynb files.

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Lets agents operate Google NotebookLM/Gemini Notebook through a Python API, CLI, skill, MCP server, or REST server to create notebooks, add sources, ask cited questions, generate artifacts, and download exports.

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Guidelines for structuring and documenting Jupyter notebooks for reproducibility and clarity.

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Create high-converting free resources that capture emails and build trust. Produces complete lead magnets (ebooks, checklists, templates, toolkits, quizzes) with landing page copy, thank-you page, and follow-up email sequence. Use when someone needs a list-building asset, wants to grow their email list, needs an opt-in incentive, a content upgrade, a gated download, or top-of-funnel content. Triggers on 'lead magnet', 'ebook', 'checklist', 'template', 'free resource', 'opt-in', 'grow my list', 'email capture', 'content upgrade', 'list building', 'gated content', or 'free download'. Even if someone just says 'I need something to capture emails' or 'how do I get more subscribers', this is the skill. Every lead magnet passes a 4-gate quality test before shipping.

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EPUB ebook creation and processing — structure, metadata, validation — use when generating or parsing ebooks.

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Query Google NotebookLM notebooks for source-grounded, citation-backed answers from user-uploaded documents. Manages notebook library, handles Google authentication, and supports smart discovery. Works standalone via /blog notebooklm or internally from blog-write and blog-researcher for source-grounded research context. Falls back gracefully when not configured. Use when user says "notebooklm", "notebook", "query notebook", "ask notebook", "notebook research", "source grounded research", "document query", "notebook library".

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Use when selecting the right Salesforce CPQ pricing model for a product line — the four native Pricing Methods (List, Cost Plus Markup, Block, Percent of Total) and Range vs Slab Discount Schedule types — before any configuration begins. Trigger keywords: CPQ pricing method, SBQQ__PricingMethod__c, Cost Plus Markup, Block Pricing design, Percent of Total design, discount schedule type, Range vs Slab discount, pricing model strategy, which CPQ pricing mechanism to use. NOT for configuring Price Rule objects — use admin/cpq-pricing-rules. NOT for pricing without CPQ — use admin/products-and-pricebooks.

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Use when configuring or troubleshooting Salesforce CPQ pricing: Price Rules, Price Conditions, Price Actions, Lookup Queries, Discount Schedules, Block Pricing, Percent of Total, and Contracted Prices. Trigger keywords: CPQ price rule, price action, discount schedule, block pricing, percent of total, contracted price, SBQQ__PriceRule__c, CPQ quote calculation engine, price waterfall. NOT for picking the pricing method — use admin/pricing-model-design. NOT for pricebook pricing without CPQ — use admin/products-and-pricebooks.

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