targeting-ligand-designer

Active targeting skill for designing and validating nanoparticle targeting strategies

509 stars

Best use case

targeting-ligand-designer is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Active targeting skill for designing and validating nanoparticle targeting strategies

Teams using targeting-ligand-designer 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/targeting-ligand-designer/SKILL.md --create-dirs "https://raw.githubusercontent.com/a5c-ai/babysitter/main/library/specializations/domains/science/nanotechnology/skills/targeting-ligand-designer/SKILL.md"

Manual Installation

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

How targeting-ligand-designer Compares

Feature / Agenttargeting-ligand-designerStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Active targeting skill for designing and validating nanoparticle targeting strategies

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.

SKILL.md Source

# Targeting Ligand Designer

## Purpose

The Targeting Ligand Designer skill provides systematic design of active targeting strategies for nanoparticle drug delivery, enabling selection and validation of targeting moieties for specific cellular or tissue targets.

## Capabilities

- Targeting ligand selection (antibodies, peptides, aptamers)
- Conjugation chemistry optimization
- Binding affinity assessment
- Biodistribution prediction
- Receptor expression analysis
- In vitro targeting validation

## Usage Guidelines

### Targeting Design

1. **Ligand Selection**
   - Identify target receptor
   - Evaluate ligand options
   - Consider size and stability

2. **Conjugation Optimization**
   - Select chemistry
   - Optimize ligand density
   - Preserve binding activity

3. **Validation**
   - Measure binding affinity
   - Test cellular uptake
   - Assess selectivity

## Process Integration

- Nanoparticle Drug Delivery System Development
- Nanosensor Development and Validation Pipeline

## Input Schema

```json
{
  "target_receptor": "string",
  "cell_type": "string",
  "nanoparticle_type": "string",
  "ligand_candidates": ["string"],
  "required_specificity": "number (fold)"
}
```

## Output Schema

```json
{
  "recommended_ligand": {
    "name": "string",
    "type": "antibody|peptide|aptamer|small_molecule",
    "Kd": "number (nM)"
  },
  "conjugation_strategy": {
    "chemistry": "string",
    "ligand_density": "number (ligands/NP)",
    "orientation": "string"
  },
  "predicted_performance": {
    "specificity": "number (fold)",
    "uptake_enhancement": "number (fold)"
  }
}
```

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