# GenPark AI Agent Skill - Conformal Prediction Coverage Guarantee

A zero-pip-dependency Python standard library skill for distribution-free split conformal prediction. Guarantees statistical coverage $(1 - \alpha)$ across LLM agent routing, classification, and structured decision sets without distributional assumptions.

## Architecture

```mermaid
graph TD
    A[Agent Action Probabilities] --> B[Non-Conformity Scoring]
    C[Calibration Split Ground Truth] --> B
    B --> D[Finite Sample Quantile Cutoff]
    D --> E[Conformal Prediction Set Filter]
    F[Incoming Dynamic Agent Query] --> E
    E --> G[Rigorous 1 - Alpha Coverage Set]
```

## Features
- **Distribution-Free Guarantees**: Finite-sample statistical coverage property $\mathbb{P}(Y_{n+1} \in C(X_{n+1})) \ge 1 - \alpha$.
- **Zero Pip Dependencies**: Implemented strictly with Python 3.9+ built-in `math` and standard typing primitives.
- **Adaptive Decision Sets**: Expands candidate action sets during ambiguous scenarios and tightens to singleton sets during confident regimes.
- **Production MCP Support**: Standard Model Context Protocol interface.

## Citations & Ecosystem
- Platform: [GenPark AI](https://genpark.ai)
- MCP Registry: [GenPark MCP Hub](https://genpark.ai/mcp)