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Agent Skill · 研究检索

deepnote(deepnote 搜索)

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。

deepnote 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为调用外部服务;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 64,959。

总安装 291周安装 12GitHub Stars 2,781下载 95核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

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。

来源仓库内路径:skills/deepnote

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/deepnote/deepnote --skill deepnote;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要调用外部服务,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

deepnote 怎么安装?

在终端执行 npx skills add https://github.com/deepnote/deepnote --skill deepnote。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

deepnote 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

deepnote 需要什么权限?

权限级别是调用外部服务。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。

deepnote 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

deepnote 用的人多吗?

公开数据是累计安装 291 次,近一周安装 12 次,下载 95 次,GitHub 2,781 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

deepnote 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 来源仓库有 2,781 星,维护活跃度相对可查。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
deepnote

deepnote 搜索 · 本页

2912,781调用外部服务未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

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
  • timestamp — latest 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.summary — blocksExecuted, blocksSucceeded, blocksFailed, totalDurationMs
  2. execution.error — name, 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

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

调用外部服务

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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