targeting-ligand-designer
Active targeting skill for designing and validating nanoparticle targeting strategies
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
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/targeting-ligand-designer/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How targeting-ligand-designer Compares
| Feature / Agent | targeting-ligand-designer | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/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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