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Agent Skill · 研究检索

labarchive-integration(实验室档案整合)

labarchive-integration 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。

labarchive-integration 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,权限为接触敏感数据;许可证为 MIT,第三方扫描有未通过项,按安装量在研究检索类的 73,675 个 Skill 里排第 52,401。

总安装 559周安装 24GitHub Stars 14下载 196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
MIT

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:labarchive-integration(实验室档案整合)
来源仓库:https://github.com/jackspace/claudeskillz
仓库路径:skills/labarchive-integration
安装命令:
npx skills add https://github.com/jackspace/claudeskillz --skill labarchive-integration
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/jackspace/claudeskillz --skill labarchive-integration

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。

labarchive-integration 用于查找、检索和筛选相关信息。适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词或任务场景快速定位候选结果。通过 npx skills add 命令从指定 GitHub 仓库安装,需确认权限和维护状态。

使用前建议核实是否会触发联网、命令执行或文件读写操作。可结合原始 README 进一步核验具体用法和功能边界。

来源仓库内路径:skills/labarchive-integration

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/jackspace/claudeskillz --skill labarchive-inte…;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

    它需要接触敏感数据,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

labarchive-integration 怎么安装?

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

labarchive-integration 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。

labarchive-integration 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

labarchive-integration 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

labarchive-integration 用的人多吗?

公开数据是累计安装 559 次,近一周安装 24 次,下载 196 次,GitHub 14 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。

labarchive-integration 安全吗?

第三方扫描有未通过项,风险较高。除非你确认过源码,否则不建议直接安装到常用环境。

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。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 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

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 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
labarchive-integration

实验室档案整合 · 本页

55914接触敏感数据MIT未通过

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

LabArchives Integration

Overview

LabArchives is an electronic lab notebook platform for research documentation and data management. Access notebooks, manage entries and attachments, generate reports, and integrate with third-party tools programmatically via REST API.

When to Use This Skill

This skill should be used when:

  • Working with LabArchives REST API for notebook automation
  • Backing up notebooks programmatically
  • Creating or managing notebook entries and attachments
  • Generating site reports and analytics
  • Integrating LabArchives with third-party tools (Protocols.io, Jupyter, REDCap)
  • Automating data upload to electronic lab notebooks
  • Managing user access and permissions programmatically

Core Capabilities

1. Authentication and Configuration

Set up API access credentials and regional endpoints for LabArchives API integration.

Prerequisites:

  • Enterprise LabArchives license with API access enabled
  • API access key ID and password from LabArchives administrator
  • User authentication credentials (email and external applications password)

Configuration setup:

Use the scripts/setup_config.py script to create a configuration file:

python3 scripts/setup_config.py

This creates a config.yaml file with the following structure:

api_url: https://api.labarchives.com/api  # or regional endpoint
access_key_id: YOUR_ACCESS_KEY_ID
access_password: YOUR_ACCESS_PASSWORD

Regional API endpoints:

  • US/International: https://api.labarchives.com/api
  • Australia: https://auapi.labarchives.com/api
  • UK: https://ukapi.labarchives.com/api

For detailed authentication instructions and troubleshooting, refer to references/authentication_guide.md.

2. User Information Retrieval

Obtain user ID (UID) and access information required for subsequent API operations.

Workflow:

  1. Call the users/user_access_info API method with login credentials
  2. Parse the XML/JSON response to extract the user ID (UID)
  3. Use the UID to retrieve detailed user information via users/user_info_via_id

Example using Python wrapper:

from labarchivespy.client import Client

# Initialize client
client = Client(api_url, access_key_id, access_password)

# Get user access info
login_params = {'login_or_email': user_email, 'password': auth_token}
response = client.make_call('users', 'user_access_info', params=login_params)

# Extract UID from response
import xml.etree.ElementTree as ET
uid = ET.fromstring(response.content)[0].text

# Get detailed user info
params = {'uid': uid}
user_info = client.make_call('users', 'user_info_via_id', params=params)

3. Notebook Operations

Manage notebook access, backup, and metadata retrieval.

Key operations:

  • List notebooks: Retrieve all notebooks accessible to a user
  • Backup notebooks: Download complete notebook data with optional attachment inclusion
  • Get notebook IDs: Retrieve institution-defined notebook identifiers for integration with grants/project management systems
  • Get notebook members: List all users with access to a specific notebook
  • Get notebook settings: Retrieve configuration and permissions for notebooks

Notebook backup example:

Use the scripts/notebook_operations.py script:

# Backup with attachments (default, creates 7z archive)
python3 scripts/notebook_operations.py backup --uid USER_ID --nbid NOTEBOOK_ID

# Backup without attachments, JSON format
python3 scripts/notebook_operations.py backup --uid USER_ID --nbid NOTEBOOK_ID --json --no-attachments

API endpoint format:

https://<api_url>/notebooks/notebook_backup?uid=<UID>&nbid=<NOTEBOOK_ID>&json=true&no_attachments=false

For comprehensive API method documentation, refer to references/api_reference.md.

4. Entry and Attachment Management

Create, modify, and manage notebook entries and file attachments.

Entry operations:

  • Create new entries in notebooks
  • Add comments to existing entries
  • Create entry parts/components
  • Upload file attachments to entries

Attachment workflow:

Use the scripts/entry_operations.py script:

# Upload attachment to an entry
python3 scripts/entry_operations.py upload --uid USER_ID --nbid NOTEBOOK_ID --entry-id ENTRY_ID --file /path/to/file.pdf

# Create a new entry with text content
python3 scripts/entry_operations.py create --uid USER_ID --nbid NOTEBOOK_ID --title "Experiment Results" --content "Results from today's experiment..."

Supported file types:

  • Documents (PDF, DOCX, TXT)
  • Images (PNG, JPG, TIFF)
  • Data files (CSV, XLSX, HDF5)
  • Scientific formats (CIF, MOL, PDB)
  • Archives (ZIP, 7Z)

5. Site Reports and Analytics

Generate institutional reports on notebook usage, activity, and compliance (Enterprise feature).

Available reports:

  • Detailed Usage Report: User activity metrics and engagement statistics
  • Detailed Notebook Report: Notebook metadata, member lists, and settings
  • PDF/Offline Notebook Generation Report: Export tracking for compliance
  • Notebook Members Report: Access control and collaboration analytics
  • Notebook Settings Report: Configuration and permission auditing

Report generation:

# Generate detailed usage report
response = client.make_call('site_reports', 'detailed_usage_report',
                           params={'start_date': '2025-01-01', 'end_date': '2025-10-20'})

6. Third-Party Integrations

LabArchives integrates with numerous scientific software platforms. This skill provides guidance on leveraging these integrations programmatically.

Supported integrations:

  • Protocols.io: Export protocols directly to LabArchives notebooks
  • GraphPad Prism: Export analyses and figures (Version 8+)
  • SnapGene: Direct molecular biology workflow integration
  • Geneious: Bioinformatics analysis export
  • Jupyter: Embed Jupyter notebooks as entries
  • REDCap: Clinical data capture integration
  • Qeios: Research publishing platform
  • SciSpace: Literature management

OAuth authentication: LabArchives now uses OAuth for all new integrations. Legacy integrations may use API key authentication.

For detailed integration setup instructions and use cases, refer to references/integrations.md.

Common Workflows

Complete notebook backup workflow

  1. Authenticate and obtain user ID
  2. List all accessible notebooks
  3. Iterate through notebooks and backup each one
  4. Store backups with timestamp metadata
# Complete backup script
python3 scripts/notebook_operations.py backup-all --email user@example.edu --password AUTH_TOKEN

Automated data upload workflow

  1. Authenticate with LabArchives API
  2. Identify target notebook and entry
  3. Upload experimental data files
  4. Add metadata comments to entries
  5. Generate activity report

Integration workflow example (Jupyter → LabArchives)

  1. Export Jupyter notebook to HTML or PDF
  2. Use entry_operations.py to upload to LabArchives
  3. Add comment with execution timestamp and environment info
  4. Tag entry for easy retrieval

Python Package Installation

Install the labarchives-py wrapper for simplified API access:

git clone https://github.com/mcmero/labarchives-py
cd labarchives-py
pip install .

Alternatively, use direct HTTP requests via Python's requests library for custom implementations.

Best Practices

  1. Rate limiting: Implement appropriate delays between API calls to avoid throttling
  2. Error handling: Always wrap API calls in try-except blocks with appropriate logging
  3. Authentication security: Store credentials in environment variables or secure config files (never in code)
  4. Backup verification: After notebook backup, verify file integrity and completeness
  5. Incremental operations: For large notebooks, use pagination and batch processing
  6. Regional endpoints: Use the correct regional API endpoint for optimal performance

Troubleshooting

Common issues:

  • 401 Unauthorized: Verify access key ID and password are correct; check API access is enabled for your account
  • 404 Not Found: Confirm notebook ID (nbid) exists and user has access permissions
  • 403 Forbidden: Check user permissions for the requested operation
  • Empty response: Ensure required parameters (uid, nbid) are provided correctly
  • Attachment upload failures: Verify file size limits and format compatibility

For additional support, contact LabArchives at support@labarchives.com.

Resources

This skill includes bundled resources to support LabArchives API integration:

scripts/

  • setup_config.py: Interactive configuration file generator for API credentials
  • notebook_operations.py: Utilities for listing, backing up, and managing notebooks
  • entry_operations.py: Tools for creating entries and uploading attachments

references/

  • api_reference.md: Comprehensive API endpoint documentation with parameters and examples
  • authentication_guide.md: Detailed authentication setup and configuration instructions
  • integrations.md: Third-party integration setup guides and use cases

平台分布

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27.09%
按下载量换算53

windsurf

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OpenCode

15.97%
按下载量换算31

Codex

11.97%
按下载量换算23

Antigravity

7.91%
按下载量换算16

Gemini CLI

3.8%
按下载量换算7

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

未通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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。

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