Use when reading, reviewing, inspecting, or reasoning about hosted Deepnote notebooks, blocks, inputs, SQL, Python, or notebook outputs through the Deepnote app tools.
npx skills add https://github.com/openai/plugins --skill deepnote-notebooks
search or project context before using get_notebook.get_notebook before answering questions about structure, inputs, blocks, or latest run state.name, type, current value, and label when useful.list_integrations and the integration usage tools to confirm project, notebook, or block references instead of inferring solely from names. When table, schema, or column context matters, use get_integration for cached structure.deepnote-notebook-editing skill.list_notebook_runs before selecting a run for get_run.Great notebook-inspection output should help the user decide what the notebook does, whether it is safe to run, and what to do next. Prefer this structure:
Keep notebook inspection brief and high signal by default. Lead with the answer, then include only the tables or cautions that materially help the user. Omit exhaustive block listings, raw code, and long outputs unless the user asks for more detail.
Notebook "Name" in project "Project" has 12 blocks, 2 inputs, 1 visible connection, and last ran successfully on YYYY-MM-DD HH:MM UTC.| Field | Value |
| --- | --- |
| Project | Project name |
| Notebook | Notebook name |
| Notebook ID | notebook-id |
| Scheduled | Yes or No |
| Last Run | status/date/run id or No run visible |
| Visible Connections | Integration name (type) or None visible via app tools |
| Input | Type | Current Value | Label |
| --- | --- | --- | --- |
| input_name | text | safe summary or value | Human label |
| Order | Type | Purpose | Connection / Output |
| --- | --- | --- | --- |
| 1 | sql | SELECT demo.gapminder sample | Clickhouse (clickhouse) |
Cautions only when actionable: cells that print environment variables, hard-coded credentials, mutating external calls, long-running servers, large dataset dumps, missing inputs, failed/pending last runs, SQL blocks whose integration is not visible, or integration usage that was not checked when it matters.Useful Next Actions only when it helps, such as run notebook, inspect latest run, list recent runs, map integrations, summarize outputs, or review risky cells.When the Deepnote app tools do not expose a detail, say Not visible via app tools rather than inferring from names. Keep raw code excerpts short; summarize large cells and mention block IDs when useful.
deepnote-notebook-editing.create_run.inputs using the input name fields returned by get_notebook, then capture run status with get_run. Omit snapshotDelivery for status checks so the default download URL delivery is used; request snapshotDelivery: "inline" when you need to summarize snapshot content or errors.get_integration for cached table/column context when needed.os.environ, environment variables, credentials, tokens, or broad secret dumps. Do not run those notebooks unless the user explicitly confirms after the risk is named.Use Deepnote app reads to verify notebook structure before making claims. If execution was not run, say so plainly and mention the remaining risk. For larger reviews, summarize relevant sections rather than listing every block.
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
Automatically creates user-facing changelogs from git commits by analyzing commit history, categorizing changes, and transforming technical commits into clear, customer-friendly release notes. Turns hours of manual changelog writing into minutes of automated generation.
Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
React Native and Expo best practices for building performant mobile apps. Use when building React Native components, optimizing list performance, implementing animations, or working with native modules. Triggers on tasks involving React Native, Expo, mobile performance, or native platform APIs.
React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
Next.js best practices - file conventions, RSC boundaries, data patterns, async APIs, metadata, error handling, route handlers, image/font optimization, bundling
Use when starting feature work that needs isolation from current workspace or before executing implementation plans - creates isolated git worktrees with smart directory selection and safety verification
Take openai/deepnote-notebooks from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.