Characterization Workflow Orchestrator
SkillDev toolsWorkflow automation skill for orchestrating multi-technique characterization sequences
Use Characterization Workflow Orchestrator in Claude, ChatGPT or Ahel Desktop
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Then ask your AI: use the Characterization Workflow Orchestrator skill
Details
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
Account requirements not reviewed. Check the skill instructions before use; Ahel provides instructions and does not run this skill.
No other account needed.
Add Ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
What this skill tells your AI
The instructions your AI receives, as published by a5c-ai/babysitter in library/specializations/domains/science/nanotechnology/skills/characterization-workflow-orchestrator/SKILL.md and read by Ahel’s review.
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"
}
Signals
- GitHub stars
- 2k
- Forks
- 113
- Last commit
- Sep 2026
Advanced
- Item type
- skill
- Key
characterization-workflow-orchestrator- Source
- github.com/a5c-ai/babysitter