AgentSkin

Standard Pruning Example

A typical implementation of the protocol standardizing a verbose meteorological API payload.

The MCP Request

{
  "url": "https://api.weather.gov/gridpoints/TOP/31,80/forecast",
  "signals": ["temperature", "windspeed", "shortforecast"],
  "aliases": {
    "temperature": "temp",
    "shortforecast": "forecast"
  }
}
            

The Resulting Skin

periods[0].temp: 45
periods[0].windspeed: 10 mph
periods[0].forecast: Mostly Clear
periods[1].temp: 38
periods[1].windspeed: 5 mph
periods[1].forecast: Sunny
            

Measured Performance

Real-world compression metrics from the reference implementation.

Token Analysis

Input (raw JSON):    ~27 estimated tokens
Output (skin):       ~5 estimated tokens
Savings:             83.02%
Platform Fee:        5 tokens
            

Compression Ratio

The analysis function calculates exact token estimates before and after transformation, enabling precise cost modeling for production pipelines.

Web Page Extraction

AgentSkin handles both APIs and web pages. When fetching HTML content, the engine parses semantic structure and converts to structured JSON before pruning.

Processing Pipeline

1. Fetch HTML content
2. Parse with cheerio (HTML parser)
3. Extract: title, h1/h2, paragraphs, links, meta
4. Convert to structured JSON
5. Prune with signals/aliases
6. Output clean Markdown skin