characterization-workflow-orchestrator

Workflow automation skill for orchestrating multi-technique characterization sequences

509 stars

Best use case

characterization-workflow-orchestrator is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Workflow automation skill for orchestrating multi-technique characterization sequences

Teams using characterization-workflow-orchestrator should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/characterization-workflow-orchestrator/SKILL.md --create-dirs "https://raw.githubusercontent.com/a5c-ai/babysitter/main/library/specializations/domains/science/nanotechnology/skills/characterization-workflow-orchestrator/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/characterization-workflow-orchestrator/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How characterization-workflow-orchestrator Compares

Feature / Agentcharacterization-workflow-orchestratorStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Workflow automation skill for orchestrating multi-technique characterization sequences

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# 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": {
    "completed": "number",
    "total": "number",
    "current_step": "string"
  },
  "integrated_results": {
    "summary": "string",
    "data_files": ["string"],
    "quality_metrics": {}
  },
  "report_path": "string"
}
```

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