a5c-ai/nanomaterial-lims-manager
library/specializations/domains/science/nanotechnology/skills/nanomaterial-lims-manager/SKILL.md
Laboratory Information Management System skill for nanomaterial sample tracking and data management
$ install --global
skillsauthnpx skillsauth add a5c-ai/babysitter nanomaterial-lims-managerInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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SKILL.md
- name:
- nanomaterial-lims-manager
- description:
- Laboratory Information Management System skill for nanomaterial sample tracking and data management
- specialization:
- nanotechnology
- domain:
- science
- category:
- infrastructure-quality
- priority:
- high
- phase:
- 6
Nanomaterial LIMS Manager
Purpose
The Nanomaterial LIMS Manager skill provides comprehensive laboratory information management for nanomaterial research, enabling systematic sample tracking, data linking, and quality assurance throughout the development lifecycle.
Capabilities
- Sample tracking and chain of custody
- Synthesis parameter logging
- Characterization data linking
- Batch genealogy tracking
- Quality control checkpoints
- Regulatory documentation
Usage Guidelines
LIMS Operations
-
Sample Management
- Register new samples
- Track sample locations
- Maintain chain of custody
-
Data Integration
- Link synthesis records
- Associate characterization data
- Build batch genealogy
-
Quality Management
- Define QC checkpoints
- Track specifications
- Generate certificates
Process Integration
- All synthesis and characterization processes
- Nanomaterial Scale-Up and Process Transfer
Input Schema
{
"operation": "register|track|query|report",
"sample_id": "string",
"sample_type": "nanoparticle|thin_film|device",
"metadata": {
"project": "string",
"synthesized_by": "string",
"synthesis_date": "string"
}
}
Output Schema
{
"sample_record": {
"sample_id": "string",
"status": "active|consumed|archived",
"location": "string",
"linked_data": [{
"data_type": "string",
"record_id": "string"
}]
},
"genealogy": {
"parent_batch": "string",
"derived_samples": ["string"]
},
"qc_status": {
"checkpoints_passed": "number",
"checkpoints_total": "number",
"status": "pass|fail|pending"
}
}
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