Characterization workflow orchestrator

Skill a5c-ai/babysitter/library/specializations/domains/science/nanotechnology/skills/characterization-workflow-orchestrator

Babysitter enforces obedience on agentic workforces and enables them to manage extremely complex tasks and workflows through deterministic, hallucination-free self-orchestration

Install

npx -y skills add a5c-ai/babysitter --skill characterization-workflow-orchestrator

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Workflow automation skill for orchestrating multi-technique characterization sequences

SKILL.md

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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"
}