Agent skill
characterization-workflow-orchestrator
Workflow automation skill for orchestrating multi-technique characterization sequences
Install this agent skill to your Project
npx add-skill https://github.com/a5c-ai/babysitter/tree/main/library/specializations/domains/science/nanotechnology/skills/characterization-workflow-orchestrator
Metadata
Additional technical details for this skill
- phase
- 6
- domain
- science
- category
- infrastructure-quality
- priority
- high
- specialization
- nanotechnology
- tools libraries
-
[ "Workflow engines", "Instrument integration APIs" ]
SKILL.md
Characterization Workflow Orchestrator
Purpose
The Characterization Workflow Orchestrator skill provides automated coordination of multi-technique characterization campaigns, enabling efficient sample throughput, data correlation, and comprehensive reporting.
Capabilities
- Characterization sequence planning
- Sample routing optimization
- Data aggregation and correlation
- Report generation
- Quality gate enforcement
- Instrument scheduling
Usage Guidelines
Workflow Orchestration
-
Sequence Planning
- Define required techniques
- Order for sample compatibility
- Allocate instrument time
-
Execution Management
- Track sample progress
- Handle technique failures
- Route to next steps
-
Data Integration
- Aggregate results
- Correlate across techniques
- Generate reports
Process Integration
- Multi-Modal Nanomaterial Characterization Pipeline
- Structure-Property Correlation Analysis
Input Schema
{
"sample_id": "string",
"characterization_goals": ["size", "composition", "structure", "surface"],
"techniques_required": ["TEM", "XRD", "XPS", "DLS"],
"priority": "routine|urgent",
"turnaround_target": "number (days)"
}
Output Schema
{
"workflow": {
"id": "string",
"status": "planned|in_progress|completed",
"sequence": [{
"step": "number",
"technique": "string",
"instrument": "string",
"scheduled_time": "string"
}]
},
"progress": {
"completed": "number",
"total": "number",
"current_step": "string"
},
"integrated_results": {
"summary": "string",
"data_files": ["string"],
"quality_metrics": {}
},
"report_path": "string"
}
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