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deepnotedeepnote 搜索

Agent Skill

deepnote 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

291

周安装

12

GitHub Stars

2,781

下载量

95
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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:deepnote(deepnote 搜索)
来源仓库:https://github.com/deepnote/deepnote
仓库路径:skills/deepnote
安装命令:
npx skills add https://github.com/deepnote/deepnote --skill deepnote
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/deepnote/deepnote --skill deepnote

简介

deepnote 解析 .deepnote 项目文件与快照格式,支持 Notebook 结构与块级内容管理。

  • 适用于 Jupyter-like 交互式文档的跨平台协作与版本控制友好存储。
  • 采用 YAML 定义 notebook 顺序与 block 类型(代码/SQL/Markdown),兼容 Git 操作。
  • 快照文件包含执行输出,可用于分享可复现的分析过程而无需传递原始数据。
  • deepnote 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Deepnote Skill

.deepnote files are YAML-based, portable, git-friendly project files that can contain multiple notebooks. Each notebook holds an ordered list of blocks (code, SQL, markdown, inputs, visualizations, etc.). Snapshot files (.snapshot.deepnote) use the same format but include execution outputs.

File Structure

A minimal valid .deepnote file:

version: 1.0.0
metadata:
  createdAt: "2025-01-08T10:00:00.000Z"
project:
  id: 2e814690-4f02-465c-8848-5567ab9253b7
  name: My Project
  notebooks:
    - id: e132b172-b114-410e-8331-011517db664f
      name: Main
      blocks:
        - id: b75d3ada977549b29f4c7f2183d52fcf
          blockGroup: 9dd9578e604a4235a552d1f4a53336ee
          type: code
          content: |
            print("Hello World!")
          sortingKey: a0
          metadata: {}

Top-level fields: version (required, "1.0.0"), metadata (required), project (required), integrations (optional), environment (optional).

Schema Reference

Notebooks

Each entry in project.notebooks has:

  • id - UUID v4 identifier
  • name - Human-readable name
  • executionMode - block (run individually) or downstream (run with dependents)
  • blocks - Array of content blocks
  • workingDirectory - Optional base directory for file operations

Blocks

Every block has these common fields:

FieldDescription
idUnique hex identifier (32 chars)
blockGroupGroups related blocks (same format as id)
typeBlock type string
contentSource code, text, or query (YAML multi-line `\` syntax)
sortingKeyDetermines display order (lexicographic, e.g. a0, a1, a2)
metadataType-specific configuration object

Block Types

CategoryTypes
Codecode
SQLsql
Textmarkdown, text-cell-h1, text-cell-h2, text-cell-h3, text-cell-p, text-cell-bullet, text-cell-todo, text-cell-callout
Inputinput-text, input-textarea, input-checkbox, input-select, input-slider, input-date, input-date-range, input-file
Displayvisualization, big-number, image, separator
Otherbutton, notebook-function

Block Type References

Integrations

Database connections stored in the top-level integrations array:

integrations:
  - id: 084f5334-5dbe-41c7-9020-3f66b9418062
    name: Production DB
    type: pgsql

Each integration has id (UUID), name, and type. Supported types: alloydb, athena, big-query, clickhouse, databricks, dremio, mariadb, materialize, mindsdb, mongodb, mysql, pgsql, redshift, snowflake, spanner, sql-server, trino. (Note: pandas-dataframe exists as a type but is not configurable via CLI.)

SQL blocks reference integrations via metadata.sql_integration_id.

Snapshots

Snapshot files (.snapshot.deepnote) store execution outputs separately from source.

Location

Snapshots are saved in a snapshots/ directory adjacent to the source file:

project.deepnote
snapshots/
  my-project_<uuid>_latest.snapshot.deepnote
  my-project_<uuid>_2025-01-08T10-30-00.snapshot.deepnote

Naming: {slug}_{projectId}_{timestamp}.snapshot.deepnote

  • slug — slugified project name
  • projectId — UUID from project.id
  • timestamplatest or ISO 8601 (e.g. 2025-01-08T10-30-00)

Reading Snapshot Data (token-efficient)

Use CLI commands — they're cross-platform and avoid loading the full YAML:

deepnote cat snapshots/*_latest.snapshot.deepnote                    # All block outputs
deepnote cat snapshots/*_latest.snapshot.deepnote --type code        # Only code outputs
deepnote inspect snapshots/*_latest.snapshot.deepnote                # Metadata + summary
deepnote inspect snapshots/*_latest.snapshot.deepnote -o json        # JSON for parsing

Do not read snapshot files directly — always use CLI commands or MCP tools to inspect them.

Diagnosing Errors

When execution fails, check the latest snapshot:

  1. execution.summaryblocksExecuted, blocksSucceeded, blocksFailed, totalDurationMs
  2. execution.errorname, message, traceback (top-level error)
  3. Per-block outputs — individual blocks have error output_type with ename, evalue, traceback

Quick error check:

deepnote inspect snapshots/*_latest.snapshot.deepnote -o json
deepnote run project.deepnote -o json   # Errors inline in output

Content Hash Verification

Each block in a snapshot has contentHash (SHA-256). If block content changed since the snapshot, the hash won't match — the output is stale.

Latest vs Timestamped

Aspect_latestTimestamped
UpdatedOverwritten on each runImmutable, one per run
ConsistencyMay mix outputs from different runsAll from same run
Use caseQuick access to recent resultsAudit trail

Editing Guidelines

When creating or modifying .deepnote files:

  1. Block IDs - Generate random 32-character hex strings (e.g. crypto.randomUUID().replace(/-/g, ''))
  2. Block groups - Each block needs a blockGroup (same hex format); blocks in the same group share a group ID
  3. Sorting keys - Use lexicographic strings: a0, a1,..., a9, b0, etc. Insert between existing keys for ordering
  4. Content - Use YAML literal block scalar (|) for multi-line content to preserve newlines
  5. Metadata - Use {} for defaults; add type-specific fields as needed

Important Policies

  • Stay in.deepnote format. When something goes wrong, do not fall back to converting to .ipynb and working in Jupyter format. The .deepnote format has better debugging tools (deepnote inspect, deepnote cat, deepnote lint, deepnote dag) that are not available for .ipynb files. Stay in .deepnote and use these tools to diagnose and fix issues.
  • Only convert on explicit request. Only use deepnote convert to export when the user explicitly asks for a format conversion.

Running After Edits

After creating or modifying blocks, always run the project to verify changes.

Prerequisites

Check if the CLI is installed:

deepnote --version

If not installed, find the best available Python and install via pip:

  1. IDE environment — check for a deepnote.json file in .vscode/, .cursor/, or .agent/ (see IDE Environment Detection below) and use its venvPath
  2. Project instructions — if the project has a .python-version file or pyproject.toml with requires-python, use the specified version
  3. Project venv — look for .venv/bin/python, venv/bin/python, or env/bin/python
  4. Homebrew Python — check if /opt/homebrew/bin/python3 or brew --prefix python3 exists
  5. System Python — use python3 (preferred) or python

Install with the best available Python (must be >= 3.9):

<best-python> -m pip install deepnote-cli

If no suitable Python is available, install via npm instead:

npm install -g @deepnote/cli

IDE Environment Detection

The Deepnote extension for VS Code, Cursor, and Antigravity creates a virtual environment for each project. Before running, check if an IDE-configured environment exists so the CLI uses the same Python interpreter.

Look for a deepnote.json file in these directories (in order):

  • .vscode/deepnote.json
  • .cursor/deepnote.json
  • .agent/deepnote.json (Antigravity)

The file maps project IDs to virtual environments:

{
  "mappings": {
    "<project-id>": {
      "environmentId": "<env-id>",
      "venvPath": "/path/to/deepnote-envs/<env-id>"
    }
  }
}

To use the IDE environment:

  1. Read the project.id from the .deepnote file
  2. Check each deepnote.json for a matching key in mappings
  3. If found, pass the venvPath to the CLI with --python:
deepnote run project.deepnote --python /path/to/deepnote-envs/<env-id>

If no IDE environment is found, omit --python and the CLI will use the system Python.

Running

deepnote run project.deepnote                         # Run full project
deepnote run project.deepnote --notebook "Analysis"    # Specific notebook
deepnote run project.deepnote --block abc123           # Specific block
deepnote run project.deepnote --dry-run                # Preview only
deepnote run project.deepnote -o json                  # JSON output

Checking Results

  1. Inline output — stdout/stderr printed directly
  2. Snapshot — outputs saved to snapshots/ directory (see Snapshots section above)
  3. Exit codes — 0 success, 1 runtime error, 2 invalid usage
  4. JSON — use -o json for structured per-block results

Workflow

  1. Edit the .deepnote file
  2. Run: deepnote run project.deepnote
  3. If errors, check snapshot for details
  4. Fix and re-run

CLI Quick Reference

CommandDescription
deepnote run [path]Execute notebooks (.deepnote,.ipynb,.py,.qmd)
deepnote convert <path>Convert between formats (Jupyter, Quarto, Percent, Marimo)
deepnote inspect [path]Display file metadata
deepnote cat <path>Display block contents
deepnote diff <a> <b>Compare two files
deepnote validate <path>Schema validation
deepnote lint <path>Check for issues (variables, integrations, inputs)
deepnote stats <path>Project statistics
deepnote analyze <path>Comprehensive analysis with quality score
`deepnote dag show\vars\downstream`Dependency analysis
deepnote open <path>Open in Deepnote Cloud

CLI Command References

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

35.78%
按下载量换算34

Claude

29.25%
按下载量换算28

Cursor

18.63%
按下载量换算18

Gemini CLI

9.74%
按下载量换算9

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

external-service

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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