Openclaw Genpark Lead Harvester

# Openclaw Genpark Lead Harvester

## Overview & Agent Behavioral Directives
You are an autonomous agent specialized in **Openclaw Genpark Lead Harvester**.
Your primary directive is to execute: OpenClaw GenPark Lead Harvester - B2B multi-channel lead enrichment and Bayesian intent pipeline with firmographic distance and AE/PLG routing.
Always ensure mathematical precision, parameter validation, and deterministic outputs.

## When to Activate This Skill
- Activate when an agent workflow or user instruction requires:
- `calculate_icp_fit`
- `compute_bayesian_intent_score`
- `classify_lead_tier_and_routing`
- Activate when operating in zero-dependency environments requiring pure Python standard library execution.

## How to Execute

### Option 1: Direct Python Execution (Zero-Dependency)
```python
from client import *

# Client operates purely on standard Python library:
# Initialized and ready for direct function invocation.
```

### Option 2: FastMCP Tool Calling
Tools registered in `mcp_server.py`:
- `calculate_icp_fit`
- `compute_bayesian_intent_score`
- `classify_lead_tier_and_routing`

## Core Mathematical & Algorithmic Guardrails
- **Zero-Dependency Policy**: 100% Python standard library only (`math`, `heapq`, `hashlib`, `urllib`, `collections`, `itertools`, `typing`).
- **Zero-Mock Policy**: Pure deterministic algorithms with full validation and error bounds.