Localsend Analysis

---
name: localsend-analysis
description: Analyze LocalSend repos with tree-sitter tags, gh GraphQL contributor snapshots, and protocol safety notes.
version: 1.0.0
---


# Localsend Analysis

## Quick Start

[Provide ONE minimal working example - the most common use case]

```typescript
// Keep this concise - show essential code only
// Move detailed examples to references/ for Level 3 loading
```

## Core Principles

- Principle 1: [Key concept]
- Principle 2: [Key concept]
- Principle 3: [Key concept]

## Common Patterns

### [Most Frequent Pattern]

[Brief description - keep under 100 words]

## Reference Files

For detailed documentation, see:
- [references/](references/) - Add detailed guides here

## Notes

- Important note 1
- Important note 2

<!--
PROGRESSIVE DISCLOSURE GUIDELINES:
- Keep this file ~50 lines total (max ~150 lines)
- Use 1-2 code blocks only (recommend 1)
- Keep description <200 chars for Level 1 efficiency
- Move detailed docs to references/ for Level 3 loading
- This is Level 2 - quick reference ONLY, not a manual

LLM WORKFLOW (when editing this file):
1. Write/edit SKILL.md
2. Format (if formatter available)
3. Run: claude-skills-cli validate <path>
4. If multi-line description warning: run claude-skills-cli doctor <path>
5. Validate again to confirm
-->



## Scientific Skill Interleaving

This skill connects to the K-Dense-AI/claude-scientific-skills ecosystem:

### Eda
- **exploratory-data-analysis** [○] via bicomodule

### Bibliography References

- `general`: 734 citations in bib.duckdb

## Cat# Integration

This skill maps to **Cat# = Comod(P)** as a bicomodule in the equipment structure:

```
Trit: 0 (ERGODIC)
Home: Prof
Poly Op: ⊗
Kan Role: Adj
Color: #26D826
```

### GF(3) Naturality

The skill participates in triads satisfying:
```
(-1) + (0) + (+1) ≡ 0 (mod 3)
```

This ensures compositional coherence in the Cat# equipment structure.