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.
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Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionlabarchive-integrationExecute the skills CLI command in your project's root directory to begin installation:
Fetches labarchive-integration from davila7/claude-code-templates and configures it for Cursor.
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Confirm successful installation by checking the skill directory location:
Restart Cursor to activate labarchive-integration. Access via /labarchive-integration in your agent's command palette.
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Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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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.
This skill should be used when:
Set up API access credentials and regional endpoints for LabArchives API integration.
Prerequisites:
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:
https://api.labarchives.com/apihttps://auapi.labarchives.com/apihttps://ukapi.labarchives.com/apiFor detailed authentication instructions and troubleshooting, refer to references/authentication_guide.md.
Obtain user ID (UID) and access information required for subsequent API operations.
Workflow:
users/user_access_info API method with login credentialsusers/user_info_via_idExample 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)
Manage notebook access, backup, and metadata retrieval.
Key operations:
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.
Create, modify, and manage notebook entries and file attachments.
Entry operations:
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:
Generate institutional reports on notebook usage, activity, and compliance (Enterprise feature).
Available reports:
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'})
LabArchives integrates with numerous scientific software platforms. This skill provides guidance on leveraging these integrations programmatically.
Supported integrations:
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.
# Complete backup script
python3 scripts/notebook_operations.py backup-all --email [email protected] --password AUTH_TOKEN
Install the labarchives-py wrapper for simplified API access:
git clone https://github.com/mcmero/labarchives-py
cd labarchives-py
uv pip install .
Alternatively, use direct HTTP requests via Python's requests library for custom implementations.
Common issues:
For additional support, contact LabArchives at [email protected].
This skill includes bundled resources to support LabArchives API integration:
setup_config.py: Interactive configuration file generator for API credentialsnotebook_operations.py: Utilities for listing, backing up, and managing notebooksentry_operations.py: Tools for creating entries and uploading attachmentsapi_reference.md: Comprehensive API endpoint documentation with parameters and examplesauthentication_guide.md: Detailed authentication setup and configuration instructionsintegrations.md: Third-party integration setup guides and use casesMake data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
davila7/claude-code-templates
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
Useful defaults in labarchive-integration — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
I recommend labarchive-integration for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
labarchive-integration has been reliable in day-to-day use. Documentation quality is above average for community skills.
labarchive-integration fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Solid pick for teams standardizing on skills: labarchive-integration is focused, and the summary matches what you get after install.
labarchive-integration is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
labarchive-integration has been reliable in day-to-day use. Documentation quality is above average for community skills.
I recommend labarchive-integration for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
labarchive-integration reduced setup friction for our internal harness; good balance of opinion and flexibility.
labarchive-integration reduced setup friction for our internal harness; good balance of opinion and flexibility.
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