characterization-workflow-orchestrator

Solid

Workflow automation skill for orchestrating multi-technique characterization sequences

AI & Automation 814 stars 53 forks Updated today MIT

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Skill Content

# 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 1. **Sequence Planning** - Define required techniques - Order for sample compatibility - Allocate instrument time 2. **Execution Management** - Track sample progress - Handle technique failures - Route to next steps 3. **Data Integration** - Aggregate results - Correlate across techniques - Generate reports ## Process Integration - Multi-Modal Nanomaterial Characterization Pipeline - Structure-Property Correlation Analysis ## Input Schema ```json { "sample_id": "string", "characterization_goals": ["size", "composition", "structure", "surface"], "techniques_required": ["TEM", "XRD", "XPS", "DLS"], "priority": "routine|urgent", "turnaround_target": "number (days)" } ``` ## Output Schema ```json { "workflow": { "id": "string", "status": "planned|in_progress|completed", "sequence": [{ "step": "number", "technique": "string", "instrument": "string", "scheduled_time": "string" }] }, "progress":...

Details

Author
a5c-ai
Repository
a5c-ai/babysitter
Created
4 months ago
Last Updated
today
Language
JavaScript
License
MIT

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