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Access notebooks, manage entries\u002Fattachments, backup notebooks, integrate with Protocols.io\u002FJupyter\u002FREDCap, for programmatic ELN workflows.","transaurus\u002Fstaging-davila7-claude-code-templates","transaurus","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F210882017?v=4","01M6JH1R6ZCRXGJCTDP5ZKZBE6","Page Turner Agent","01M6JH1RBBR2P6Y0XWDGM4B0G7",0,"MIT","https:\u002F\u002Fgithub.com\u002Ftransaurus\u002Fstaging-davila7-claude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Flabarchive-integration\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37],"integration","labarchive integration","integrate","for","lab","programmatic","with","io","entries","notebook","api integration","manage","workflows","jupyter","access","api","backup","attachments","protocols","2026-11-10 10:12:30",false,"---\nname: labarchive-integration\ndescription: \"Electronic lab notebook API integration. Access notebooks, manage entries\u002Fattachments, backup notebooks, integrate with Protocols.io\u002FJupyter\u002FREDCap, for programmatic ELN workflows.\"\n---\n\n# LabArchives Integration\n\n## Overview\n\nLabArchives 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.\n\n## When to Use This Skill\n\nThis skill should be used when:\n- Working with LabArchives REST API for notebook automation\n- Backing up notebooks programmatically\n- Creating or managing notebook entries and attachments\n- Generating site reports and analytics\n- Integrating LabArchives with third-party tools (Protocols.io, Jupyter, REDCap)\n- Automating data upload to electronic lab notebooks\n- Managing user access and permissions programmatically\n\n## Core Capabilities\n\n### 1. Authentication and Configuration\n\nSet up API access credentials and regional endpoints for LabArchives API integration.\n\n**Prerequisites:**\n- Enterprise LabArchives license with API access enabled\n- API access key ID and password from LabArchives administrator\n- User authentication credentials (email and external applications password)\n\n**Configuration setup:**\n\nUse the `scripts\u002Fsetup_config.py` script to create a configuration file:\n\n```bash\npython3 scripts\u002Fsetup_config.py\n```\n\nThis creates a `config.yaml` file with the following structure:\n\n```yaml\napi_url: https:\u002F\u002Fapi.labarchives.com\u002Fapi  # or regional endpoint\naccess_key_id: YOUR_ACCESS_KEY_ID\naccess_password: YOUR_ACCESS_PASSWORD\n```\n\n**Regional API endpoints:**\n- US\u002FInternational: `https:\u002F\u002Fapi.labarchives.com\u002Fapi`\n- Australia: `https:\u002F\u002Fauapi.labarchives.com\u002Fapi`\n- UK: `https:\u002F\u002Fukapi.labarchives.com\u002Fapi`\n\nFor detailed authentication instructions and troubleshooting, refer to `references\u002Fauthentication_guide.md`.\n\n### 2. User Information Retrieval\n\nObtain user ID (UID) and access information required for subsequent API operations.\n\n**Workflow:**\n\n1. Call the `users\u002Fuser_access_info` API method with login credentials\n2. Parse the XML\u002FJSON response to extract the user ID (UID)\n3. Use the UID to retrieve detailed user information via `users\u002Fuser_info_via_id`\n\n**Example using Python wrapper:**\n\n```python\nfrom labarchivespy.client import Client\n\n# Initialize client\nclient = Client(api_url, access_key_id, access_password)\n\n# Get user access info\nlogin_params = {'login_or_email': user_email, 'password': auth_token}\nresponse = client.make_call('users', 'user_access_info', params=login_params)\n\n# Extract UID from response\nimport xml.etree.ElementTree as ET\nuid = ET.fromstring(response.content)[0].text\n\n# Get detailed user info\nparams = {'uid': uid}\nuser_info = client.make_call('users', 'user_info_via_id', params=params)\n```\n\n### 3. Notebook Operations\n\nManage notebook access, backup, and metadata retrieval.\n\n**Key operations:**\n\n- **List notebooks:** Retrieve all notebooks accessible to a user\n- **Backup notebooks:** Download complete notebook data with optional attachment inclusion\n- **Get notebook IDs:** Retrieve institution-defined notebook identifiers for integration with grants\u002Fproject management systems\n- **Get notebook members:** List all users with access to a specific notebook\n- **Get notebook settings:** Retrieve configuration and permissions for notebooks\n\n**Notebook backup example:**\n\nUse the `scripts\u002Fnotebook_operations.py` script:\n\n```bash\n# Backup with attachments (default, creates 7z archive)\npython3 scripts\u002Fnotebook_operations.py backup --uid USER_ID --nbid NOTEBOOK_ID\n\n# Backup without attachments, JSON format\npython3 scripts\u002Fnotebook_operations.py backup --uid USER_ID --nbid NOTEBOOK_ID --json --no-attachments\n```\n\n**API endpoint format:**\n```\nhttps:\u002F\u002F\u003Capi_url>\u002Fnotebooks\u002Fnotebook_backup?uid=\u003CUID>&nbid=\u003CNOTEBOOK_ID>&json=true&no_attachments=false\n```\n\nFor comprehensive API method documentation, refer to `references\u002Fapi_reference.md`.\n\n### 4. Entry and Attachment Management\n\nCreate, modify, and manage notebook entries and file attachments.\n\n**Entry operations:**\n- Create new entries in notebooks\n- Add comments to existing entries\n- Create entry parts\u002Fcomponents\n- Upload file attachments to entries\n\n**Attachment workflow:**\n\nUse the `scripts\u002Fentry_operations.py` script:\n\n```bash\n# Upload attachment to an entry\npython3 scripts\u002Fentry_operations.py upload --uid USER_ID --nbid NOTEBOOK_ID --entry-id ENTRY_ID --file \u002Fpath\u002Fto\u002Ffile.pdf\n\n# Create a new entry with text content\npython3 scripts\u002Fentry_operations.py create --uid USER_ID --nbid NOTEBOOK_ID --title \"Experiment Results\" --content \"Results from today's experiment...\"\n```\n\n**Supported file types:**\n- Documents (PDF, DOCX, TXT)\n- Images (PNG, JPG, TIFF)\n- Data files (CSV, XLSX, HDF5)\n- Scientific formats (CIF, MOL, PDB)\n- Archives (ZIP, 7Z)\n\n### 5. Site Reports and Analytics\n\nGenerate institutional reports on notebook usage, activity, and compliance (Enterprise feature).\n\n**Available reports:**\n- Detailed Usage Report: User activity metrics and engagement statistics\n- Detailed Notebook Report: Notebook metadata, member lists, and settings\n- PDF\u002FOffline Notebook Generation Report: Export tracking for compliance\n- Notebook Members Report: Access control and collaboration analytics\n- Notebook Settings Report: Configuration and permission auditing\n\n**Report generation:**\n\n```python\n# Generate detailed usage report\nresponse = client.make_call('site_reports', 'detailed_usage_report',\n                           params={'start_date': '2025-01-01', 'end_date': '2025-10-20'})\n```\n\n### 6. Third-Party Integrations\n\nLabArchives integrates with numerous scientific software platforms. This skill provides guidance on leveraging these integrations programmatically.\n\n**Supported integrations:**\n- **Protocols.io:** Export protocols directly to LabArchives notebooks\n- **GraphPad Prism:** Export analyses and figures (Version 8+)\n- **SnapGene:** Direct molecular biology workflow integration\n- **Geneious:** Bioinformatics analysis export\n- **Jupyter:** Embed Jupyter notebooks as entries\n- **REDCap:** Clinical data capture integration\n- **Qeios:** Research publishing platform\n- **SciSpace:** Literature management\n\n**OAuth authentication:**\nLabArchives now uses OAuth for all new integrations. Legacy integrations may use API key authentication.\n\nFor detailed integration setup instructions and use cases, refer to `references\u002Fintegrations.md`.\n\n## Common Workflows\n\n### Complete notebook backup workflow\n\n1. Authenticate and obtain user ID\n2. List all accessible notebooks\n3. Iterate through notebooks and backup each one\n4. Store backups with timestamp metadata\n\n```bash\n# Complete backup script\npython3 scripts\u002Fnotebook_operations.py backup-all --email user@example.edu --password AUTH_TOKEN\n```\n\n### Automated data upload workflow\n\n1. Authenticate with LabArchives API\n2. Identify target notebook and entry\n3. Upload experimental data files\n4. Add metadata comments to entries\n5. Generate activity report\n\n### Integration workflow example (Jupyter → LabArchives)\n\n1. Export Jupyter notebook to HTML or PDF\n2. Use entry_operations.py to upload to LabArchives\n3. Add comment with execution timestamp and environment info\n4. Tag entry for easy retrieval\n\n## Python Package Installation\n\nInstall the `labarchives-py` wrapper for simplified API access:\n\n```bash\ngit clone https:\u002F\u002Fgithub.com\u002Fmcmero\u002Flabarchives-py\ncd labarchives-py\nuv pip install .\n```\n\nAlternatively, use direct HTTP requests via Python's `requests` library for custom implementations.\n\n## Best Practices\n\n1. **Rate limiting:** Implement appropriate delays between API calls to avoid throttling\n2. **Error handling:** Always wrap API calls in try-except blocks with appropriate logging\n3. **Authentication security:** Store credentials in environment variables or secure config files (never in code)\n4. **Backup verification:** After notebook backup, verify file integrity and completeness\n5. **Incremental operations:** For large notebooks, use pagination and batch processing\n6. **Regional endpoints:** Use the correct regional API endpoint for optimal performance\n\n## Troubleshooting\n\n**Common issues:**\n\n- **401 Unauthorized:** Verify access key ID and password are correct; check API access is enabled for your account\n- **404 Not Found:** Confirm notebook ID (nbid) exists and user has access permissions\n- **403 Forbidden:** Check user permissions for the requested operation\n- **Empty response:** Ensure required parameters (uid, nbid) are provided correctly\n- **Attachment upload failures:** Verify file size limits and format compatibility\n\nFor additional support, contact LabArchives at support@labarchives.com.\n\n## Resources\n\nThis skill includes bundled resources to support LabArchives API integration:\n\n### scripts\u002F\n\n- `setup_config.py`: Interactive configuration file generator for API credentials\n- `notebook_operations.py`: Utilities for listing, backing up, and managing notebooks\n- `entry_operations.py`: Tools for creating entries and uploading attachments\n\n### references\u002F\n\n- `api_reference.md`: Comprehensive API endpoint documentation with parameters and examples\n- `authentication_guide.md`: Detailed authentication setup and configuration instructions\n- `integrations.md`: Third-party integration setup guides and use cases\n","# LabArchives Integration\n\n## Overview\n\nLabArchives 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.\n\n## When to Use This Skill\n\nThis skill should be used when:\n- Working with LabArchives REST API for notebook automation\n- Backing up notebooks programmatically\n- Creating or managing notebook entries and attachments\n- Generating site reports and analytics\n- Integrating LabArchives with third-party tools (Protocols.io, Jupyter, REDCap)\n- Automating data upload to electronic lab notebooks\n- Managing user access and permissions programmatically\n\n## Core Capabilities\n\n### 1. Authentication and Configuration\n\nSet up API access credentials and regional endpoints for LabArchives API integration.\n\n**Prerequisites:**\n- Enterprise LabArchives license with API access enabled\n- API access key ID and password from LabArchives administrator\n- User authentication credentials (email and external applications password)\n\n**Configuration setup:**\n\nUse the `scripts\u002Fsetup_config.py` script to create a configuration file:\n\n```bash\npython3 scripts\u002Fsetup_config.py\n```\n\nThis creates a `config.yaml` file with the following structure:\n\n```yaml\napi_url: https:\u002F\u002Fapi.labarchives.com\u002Fapi  # or regional endpoint\naccess_key_id: YOUR_ACCESS_KEY_ID\naccess_password: YOUR_ACCESS_PASSWORD\n```\n\n**Regional API endpoints:**\n- US\u002FInternational: `https:\u002F\u002Fapi.labarchives.com\u002Fapi`\n- Australia: `https:\u002F\u002Fauapi.labarchives.com\u002Fapi`\n- UK: `https:\u002F\u002Fukapi.labarchives.com\u002Fapi`\n\nFor detailed authentication instructions and troubleshooting, refer to `references\u002Fauthentication_guide.md`.\n\n### 2. User Information Retrieval\n\nObtain user ID (UID) and access information required for subsequent API operations.\n\n**Workflow:**\n\n1. Call the `users\u002Fuser_access_info` API method with login credentials\n2. Parse the XML\u002FJSON response to extract the user ID (UID)\n3. Use the UID to retrieve detailed user information via `users\u002Fuser_info_via_id`\n\n**Example using Python wrapper:**\n\n```python\nfrom labarchivespy.client import Client\n\n# Initialize client\nclient = Client(api_url, access_key_id, access_password)\n\n# Get user access info\nlogin_params = {'login_or_email': user_email, 'password': auth_token}\nresponse = client.make_call('users', 'user_access_info', params=login_params)\n\n# Extract UID from response\nimport xml.etree.ElementTree as ET\nuid = ET.fromstring(response.content)[0].text\n\n# Get detailed user info\nparams = {'uid': uid}\nuser_info = client.make_call('users', 'user_info_via_id', params=params)\n```\n\n### 3. Notebook Operations\n\nManage notebook access, backup, and metadata retrieval.\n\n**Key operations:**\n\n- **List notebooks:** Retrieve all notebooks accessible to a user\n- **Backup notebooks:** Download complete notebook data with optional attachment inclusion\n- **Get notebook IDs:** Retrieve institution-defined notebook identifiers for integration with grants\u002Fproject management systems\n- **Get notebook members:** List all users with access to a specific notebook\n- **Get notebook settings:** Retrieve configuration and permissions for notebooks\n\n**Notebook backup example:**\n\nUse the `scripts\u002Fnotebook_operations.py` script:\n\n```bash\n# Backup with attachments (default, creates 7z archive)\npython3 scripts\u002Fnotebook_operations.py backup --uid USER_ID --nbid NOTEBOOK_ID\n\n# Backup without attachments, JSON format\npython3 scripts\u002Fnotebook_operations.py backup --uid USER_ID --nbid NOTEBOOK_ID --json --no-attachments\n```\n\n**API endpoint format:**\n```\nhttps:\u002F\u002F\u003Capi_url>\u002Fnotebooks\u002Fnotebook_backup?uid=\u003CUID>&nbid=\u003CNOTEBOOK_ID>&json=true&no_attachments=false\n```\n\nFor comprehensive API method documentation, refer to `references\u002Fapi_reference.md`.\n\n### 4. Entry and Attachment Management\n\nCreate, modify, and manage notebook entries and file attachments.\n\n**Entry operations:**\n- Create new entries in notebooks\n- Add comments to existing entries\n- Create entry parts\u002Fcomponents\n- Upload file attachments to entries\n\n**Attachment workflow:**\n\nUse the `scripts\u002Fentry_operations.py` script:\n\n```bash\n# Upload attachment to an entry\npython3 scripts\u002Fentry_operations.py upload --uid USER_ID --nbid NOTEBOOK_ID --entry-id ENTRY_ID --file \u002Fpath\u002Fto\u002Ffile.pdf\n\n# Create a new entry with text content\npython3 scripts\u002Fentry_operations.py create --uid USER_ID --nbid NOTEBOOK_ID --title \"Experiment Results\" --content \"Results from today's experiment...\"\n```\n\n**Supported file types:**\n- Documents (PDF, DOCX, TXT)\n- Images (PNG, JPG, TIFF)\n- Data files (CSV, XLSX, HDF5)\n- Scientific formats (CIF, MOL, PDB)\n- Archives (ZIP, 7Z)\n\n### 5. Site Reports and Analytics\n\nGenerate institutional reports on notebook usage, activity, and compliance (Enterprise feature).\n\n**Available reports:**\n- Detailed Usage Report: User activity metrics and engagement statistics\n- Detailed Notebook Report: Notebook metadata, member lists, and settings\n- PDF\u002FOffline Notebook Generation Report: Export tracking for compliance\n- Notebook Members Report: Access control and collaboration analytics\n- Notebook Settings Report: Configuration and permission auditing\n\n**Report generation:**\n\n```python\n# Generate detailed usage report\nresponse = client.make_call('site_reports', 'detailed_usage_report',\n                           params={'start_date': '2025-01-01', 'end_date': '2025-10-20'})\n```\n\n### 6. Third-Party Integrations\n\nLabArchives integrates with numerous scientific software platforms. This skill provides guidance on leveraging these integrations programmatically.\n\n**Supported integrations:**\n- **Protocols.io:** Export protocols directly to LabArchives notebooks\n- **GraphPad Prism:** Export analyses and figures (Version 8+)\n- **SnapGene:** Direct molecular biology workflow integration\n- **Geneious:** Bioinformatics analysis export\n- **Jupyter:** Embed Jupyter notebooks as entries\n- **REDCap:** Clinical data capture integration\n- **Qeios:** Research publishing platform\n- **SciSpace:** Literature management\n\n**OAuth authentication:**\nLabArchives now uses OAuth for all new integrations. Legacy integrations may use API key authentication.\n\nFor detailed integration setup instructions and use cases, refer to `references\u002Fintegrations.md`.\n\n## Common Workflows\n\n### Complete notebook backup workflow\n\n1. Authenticate and obtain user ID\n2. List all accessible notebooks\n3. Iterate through notebooks and backup each one\n4. Store backups with timestamp metadata\n\n```bash\n# Complete backup script\npython3 scripts\u002Fnotebook_operations.py backup-all --email user@example.edu --password AUTH_TOKEN\n```\n\n### Automated data upload workflow\n\n1. Authenticate with LabArchives API\n2. Identify target notebook and entry\n3. Upload experimental data files\n4. Add metadata comments to entries\n5. Generate activity report\n\n### Integration workflow example (Jupyter → LabArchives)\n\n1. Export Jupyter notebook to HTML or PDF\n2. Use entry_operations.py to upload to LabArchives\n3. Add comment with execution timestamp and environment info\n4. Tag entry for easy retrieval\n\n## Python Package Installation\n\nInstall the `labarchives-py` wrapper for simplified API access:\n\n```bash\ngit clone https:\u002F\u002Fgithub.com\u002Fmcmero\u002Flabarchives-py\ncd labarchives-py\nuv pip install .\n```\n\nAlternatively, use direct HTTP requests via Python's `requests` library for custom implementations.\n\n## Best Practices\n\n1. **Rate limiting:** Implement appropriate delays between API calls to avoid throttling\n2. **Error handling:** Always wrap API calls in try-except blocks with appropriate logging\n3. **Authentication security:** Store credentials in environment variables or secure config files (never in code)\n4. **Backup verification:** After notebook backup, verify file integrity and completeness\n5. **Incremental operations:** For large notebooks, use pagination and batch processing\n6. **Regional endpoints:** Use the correct regional API endpoint for optimal performance\n\n## Troubleshooting\n\n**Common issues:**\n\n- **401 Unauthorized:** Verify access key ID and password are correct; check API access is enabled for your account\n- **404 Not Found:** Confirm notebook ID (nbid) exists and user has access permissions\n- **403 Forbidden:** Check user permissions for the requested operation\n- **Empty response:** Ensure required parameters (uid, nbid) are provided correctly\n- **Attachment upload failures:** Verify file size limits and format compatibility\n\nFor additional support, contact LabArchives at support@labarchives.com.\n\n## Resources\n\nThis skill includes bundled resources to support LabArchives API integration:\n\n### scripts\u002F\n\n- `setup_config.py`: Interactive configuration file generator for API credentials\n- `notebook_operations.py`: Utilities for listing, backing up, and managing notebooks\n- `entry_operations.py`: Tools for creating entries and uploading attachments\n\n### references\u002F\n\n- `api_reference.md`: Comprehensive API endpoint documentation with parameters and examples\n- `authentication_guide.md`: Detailed authentication setup and configuration instructions\n- `integrations.md`: Third-party integration setup guides and use cases\n",{"name":5,"description":7},"main","34fa6acf794b9a6310d298cbb8fb8c9420a5edcf","cli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Flabarchive-integration",2,"https:\u002F\u002Fgithub.com\u002Ftransaurus\u002Fstaging-davila7-claude-code-templates","https:\u002F\u002Fgithub.com\u002Ftransaurus","Automated works of Page Turner","2026-03-28 10:12:59",{"source":8,"skillName":5,"commands":52,"prompt":62,"zipAvailable":63},[53,56,59],{"tool":54,"command":55},"npx","npx skills add transaurus\u002Fstaging-davila7-claude-code-templates --skill labarchive-integration",{"tool":57,"command":58},"bunx","bunx skills add transaurus\u002Fstaging-davila7-claude-code-templates --skill labarchive-integration",{"tool":60,"command":61},"pnpm","pnpm dlx skills add transaurus\u002Fstaging-davila7-claude-code-templates --skill labarchive-integration","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Ftransaurus\u002Fstaging-davila7-claude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Flabarchive-integration\u002FSKILL.md",true,[65,71,75,79,85,89],{"path":66,"resourceType":67,"resourceTypeDesc":68,"sizeBytes":69,"sourceHtmlUrl":70},"references\u002Fapi_reference.md","REFERENCE","参考文档",9012,"https:\u002F\u002Fgithub.com\u002Ftransaurus\u002Fstaging-davila7-claude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Flabarchive-integration\u002Freferences\u002Fapi_reference.md",{"path":72,"resourceType":67,"resourceTypeDesc":68,"sizeBytes":73,"sourceHtmlUrl":74},"references\u002Fauthentication_guide.md",10709,"https:\u002F\u002Fgithub.com\u002Ftransaurus\u002Fstaging-davila7-claude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Flabarchive-integration\u002Freferences\u002Fauthentication_guide.md",{"path":76,"resourceType":67,"resourceTypeDesc":68,"sizeBytes":77,"sourceHtmlUrl":78},"references\u002Fintegrations.md",12645,"https:\u002F\u002Fgithub.com\u002Ftransaurus\u002Fstaging-davila7-claude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Flabarchive-integration\u002Freferences\u002Fintegrations.md",{"path":80,"resourceType":81,"resourceTypeDesc":82,"sizeBytes":83,"sourceHtmlUrl":84},"scripts\u002Fentry_operations.py","SCRIPT","脚本",10576,"https:\u002F\u002Fgithub.com\u002Ftransaurus\u002Fstaging-davila7-claude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Flabarchive-integration\u002Fscripts\u002Fentry_operations.py",{"path":86,"resourceType":81,"resourceTypeDesc":82,"sizeBytes":87,"sourceHtmlUrl":88},"scripts\u002Fnotebook_operations.py",8677,"https:\u002F\u002Fgithub.com\u002Ftransaurus\u002Fstaging-davila7-claude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Flabarchive-integration\u002Fscripts\u002Fnotebook_operations.py",{"path":90,"resourceType":81,"resourceTypeDesc":82,"sizeBytes":91,"sourceHtmlUrl":92},"scripts\u002Fsetup_config.py",6412,"https:\u002F\u002Fgithub.com\u002Ftransaurus\u002Fstaging-davila7-claude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Flabarchive-integration\u002Fscripts\u002Fsetup_config.py",[94,125,146,168,188,214],{"skillNo":95,"name":96,"nameZh":6,"description":97,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":98,"categories":99,"keywords":105,"publishedAt":38},"01M6JMRJR3BE0HGWFWDZSB853S","zapier-make-patterns","No-code automation democratizes workflow building. 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Key insight: Zapier optimizes for simplicity and integrations (7000+ apps), Make optimizes for power","https:\u002F\u002Fgithub.com\u002Ftransaurus\u002Fstaging-davila7-claude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fworkflow-automation\u002Fzapier-make-patterns\u002FSKILL.md",[100],{"categoryNo":101,"categoryName":102,"taxonomyType":103,"taxonomyTypeDesc":104},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,22,124],"zapier make patterns","patterns","make","zapier","writing","workflow","automation","code","integrations","business","use","power","complexity","platform","apps","how to","No-Code","which","spawner",{"skillNo":126,"name":127,"nameZh":6,"description":128,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":129,"categories":130,"keywords":131,"publishedAt":38},"01M6JMR8YK6SWPCTG1MCQTMN9S","yeet","Use only when the user explicitly asks to stage, commit, push, and open a GitHub pull request in one flow using the GitHub CLI (`gh`).","https:\u002F\u002Fgithub.com\u002Ftransaurus\u002Fstaging-davila7-claude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fworkflow-automation\u002Fyeet\u002FSKILL.md",[],[127,132,133,134,135,136,137,138,139,140,141,142,116,143,144,145],"cli","github","commit","pull request","openai","pull","push","flow","open","gh","user","only","stage","github cli",{"skillNo":147,"name":148,"nameZh":6,"description":149,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":150,"categories":151,"keywords":153,"publishedAt":38},"01M6JMQNFE64ZASQK90HARRXW8","workflow-automation","Workflow automation is the infrastructure that makes AI agents reliable. Without durable execution, a network hiccup during a 10-step payment flow means lost money and angry customers. With it, workflows resume exactly where they left off.  This skill covers the platforms (n8n, Temporal, Inngest) and patterns (sequential, parallel, orchestrator-worker) that turn brittle scripts into production-grade automation.  Key insight: The platforms make different tradeoffs. n8n optimizes for accessibility","https:\u002F\u002Fgithub.com\u002Ftransaurus\u002Fstaging-davila7-claude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fworkflow-automation\u002Fworkflow-automation\u002FSKILL.md",[152],{"categoryNo":101,"categoryName":102,"taxonomyType":103,"taxonomyTypeDesc":104},[111,112,154,155,156,31,157,158,159,160,161,162,163,164,165,166,167,25,22,124],"Workflow Automation","ai agents","accessibility","apache","execution","inngest","parallel","orchestrator","resume","n8n","payment","worker","scripts","temporal",{"skillNo":169,"name":170,"nameZh":6,"description":171,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":172,"categories":173,"keywords":174,"publishedAt":38},"01M6JMQDYJ0XETERPHGDR3EVGN","trigger-dev","Trigger.dev expert for background jobs, AI workflows, and reliable async execution with excellent developer experience and TypeScript-first design. Use when: trigger.dev, trigger dev, background task, ai background job, long running task.","https:\u002F\u002Fgithub.com\u002Ftransaurus\u002Fstaging-davila7-claude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fworkflow-automation\u002Ftrigger-dev\u002FSKILL.md",[],[175,176,177,178,179,31,180,157,158,181,116,182,183,184,185,186,187,25,22,124],"dev","trigger dev","trigger","design","typescript","async execution","first","async","developer experience","expert","task","background jobs","long",{"skillNo":189,"name":190,"nameZh":6,"description":191,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":192,"categories":193,"keywords":197,"publishedAt":38},"01M6JMQ5J6KK3GSX9FJCWWK6G6","planning-with-files","Transforms workflow to use Manus-style persistent markdown files for planning, progress tracking, and knowledge storage. Use when starting complex tasks, multi-step projects, research tasks, or when the user mentions planning, organizing work, tracking progress, or wants structured output.","https:\u002F\u002Fgithub.com\u002Ftransaurus\u002Fstaging-davila7-claude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fworkflow-automation\u002Fplanning-with-files\u002FSKILL.md",[194],{"categoryNo":195,"categoryName":196,"taxonomyType":103,"taxonomyTypeDesc":104},"01JBSEEDCAT000000000000021","资料检索与研究",[198,199,200,25,201,111,202,203,204,205,206,207,116,208,209,210,211,212,213,22],"planning with files","planning","files","with files","storage","tasks","markdown","knowledge","projects","work","manus","structured output","progress","transforms","multi","output",{"skillNo":215,"name":216,"nameZh":6,"description":217,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":218,"categories":219,"keywords":224,"publishedAt":38},"01M6JMPWAT60RXXNEC4V9TRBRS","n8n-workflow-patterns","Proven workflow architectural patterns from real n8n workflows. Use when building new workflows, designing workflow structure, choosing workflow patterns, planning workflow architecture, or asking about webhook processing, HTTP API integration, database operations, AI agent workflows, or scheduled tasks.","https:\u002F\u002Fgithub.com\u002Ftransaurus\u002Fstaging-davila7-claude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fworkflow-automation\u002Fn8n\u002Fn8n-workflow-patterns\u002FSKILL.md",[220,223],{"categoryNo":221,"categoryName":222,"taxonomyType":103,"taxonomyTypeDesc":104},"01JBSEEDCAT000000000000010","后端与接口",{"categoryNo":101,"categoryName":102,"taxonomyType":103,"taxonomyTypeDesc":104},[111,225,163,226,107,227,228,31,229,203,199,230,34,231,232,233,234,235,236,237],"n8n workflow patterns","workflow patterns","n8n workflow","ai agent","architecture","database","planning workflow","structure","database operations","webhook","processing","http api","scheduled"]