"""
S2 Decomposed: domain-grounding
==========================================

Auto-generated by S2 Auto-Decomposer.

Original skill: enterprise/domain-grounding
Scale structure:
  L0 (Micro): 3 operations
  L1 (Meso): 2 operations
  L2 (Macro): 1 operations
  L3 (Meta): 1 orchestrator

Model routing:
  L0 -> codegemma
  L1 -> qwen3
  L2 -> qwen3
  L3 -> deepseek_r1
"""

```python
from typing import Any, Dict, List, Optional, Tuple
from skills.s2.context_stack import ScaleLevel
from skills.s2.composer import S2Composer
import re
from datetime import datetime

# L0 MICRO SKILLS
def micro_fetch_enterprise_rule_from_db(rule_id: str, **kwargs) -> Dict[str, Any]:
    """Simulate fetching an enterprise rule from a database."""
    # Simulated database lookup
    enterprise_rules = {
        "rule_001": {
            "id": "rule_001",
            "description": "Data must contain valid company ID",
            "constraint": r"^[A-Z]{3}\d{4}$"
        },
        "rule_002": {
            "id": "rule_002",
            "description": "All dates must be in ISO format",
            "constraint": r"^\d{4}-\d{2}-\d{2}$"
        }
    }
    
    if rule_id in enterprise_rules:
        return {
            "rule_id": rule_id,
            "rule": enterprise_rules[rule_id],
            "timestamp": datetime.now().isoformat()
        }
    return {
        "error": f"Rule {rule_id} not found in database",
        "code": "RULE_NOT_FOUND"
    }

def micro_parse_legal_documentation(text: str, **kwargs) -> Dict[str, Any]:
    """Extract constraints from legal documentation text."""
    constraints = []
    
    # Extract constraints using regex patterns
    pattern = r"Constraint:\s*(.*?)(?=\nConstraint|\n$)"
    matches = re.findall(pattern, text, re.DOTALL)
    
    for match in matches:
        match = match.strip()
        if match:
            constraints.append({
                "type": "legal",
                "content": match,
                "extracted_at": datetime.now().isoformat()
            })
    
    return {
        "extracted_constraints": constraints,
        "document_length": len(text),
        "processing_time": datetime.now().timestamp()
    }

def micro_validate_input_against_rule(input_value: Any, rule: Dict, **kwargs) -> Dict[str, Any]:
    """Validate input against a specific rule."""
    if not rule or "constraint" not in rule:
        return {
            "error": "Invalid rule configuration",
            "code": "INVALID_RULE"
        }
    
    try:
        if not re.match(rule["constraint"], str(input_value)):
            return {
                "input": input_value,
                "rule": rule,
                "valid": False,
                "reason": f"Does not match constraint: {rule['constraint']}"
            }
        return {
            "input": input_value,
            "rule": rule,
            "valid": True,
            "timestamp": datetime.now().isoformat()
        }
    except re.error as e:
        return {
            "error": f"Invalid regex pattern in rule: {e}",
            "code": "INVALID_REGEX"
        }

# L1 MESO SKILLS
def meso_gather_domain_standards(rule_ids: List[str], document_text: str, **kwargs) -> Dict[str, Any]:
    """Aggregate enterprise rules and legal constraints."""
    results = {"rules": [], "constraints": []}
    
    # Fetch enterprise rules
    for rule_id in rule_ids:
        rule_result = micro_fetch_enterprise_rule_from_db(rule_id)
        if "error" not in rule_result:
            results["rules"].append(rule_result["rule"])
        else:
            results["errors"].append(rule_result["error"])
    
    # Parse legal documentation
    doc_result = micro_parse_legal_documentation(document_text)
    results["constraints"].extend(doc_result["extracted_constraints"])
    
    return results

def meso_validate_inputs_compliance(inputs: List[Any], rules: List[Dict], **kwargs) -> Dict[str, Any]:
    """Validate multiple inputs against a set of rules."""
    validation_results = []
    
    for input_value in inputs:
        for rule in rules:
            validation_result = micro_validate_input_against_rule(
                input_value=input_value,
                rule=rule
            )
            validation_results.append(validation_result)
    
    return {
        "validations": validation_results,
        "total_checks": len(validation_results),
        "passed": sum(1 for r in validation_results if r.get("valid", False)),
        "failed": len(validation_results) - sum(1 for r in validation_results if r.get("valid", False))
    }

# L2 MACRO SKILLS
def macro_comprehensive_domain_check(
    rule_ids: List[str],
    document_text: str,
    inputs: List[Any],
    **kwargs
) -> Dict[str, Any]:
    """Perform comprehensive domain validation."""
    # Gather all domain standards
    standards_result = meso_gather_domain_standards(rule_ids, document_text)
    
    # Validate inputs against gathered standards
    validation_result = meso_validate_inputs_compliance(
        inputs=inputs,
        rules=standards_result["rules"]
    )
    
    return {
        "standards": standards_result,
        "validation": validation_result,
        "timestamp": datetime.now().isoformat()
    }

# L3 META ORCHESTRATOR
def meta_domain_grounding_orchestrator(
    capability: str,
    params: dict = None,
    **kwargs
) -> Dict[str, Any]:
    """Orchestrate domain grounding operations."""
    if not params:
        params = {}
    
    # Execute comprehensive domain check
    result = macro_comprehensive_domain_check(
        rule_ids=params.get("rule_ids", []),
        document_text=params.get("document_text", ""),
        inputs=params.get("inputs", [])
    )
    
    # Add orchestration metadata
    result["orchestrated"] = True
    result["capability"] = capability
    result["orchestration_time"] = datetime.now().isoformat()
    
    return result

def create_composer() -> S2Composer:
    """Create and register all domain grounding skills."""
    composer = S2


# Skill metadata
SKILL_METADATA = {
    "original_id": "enterprise/domain-grounding",
    "original_name": "domain-grounding",
    "scale_structure": {
    "L0": [
        "fetch_enterprise_rule_from_db: Look up a specific rule from the enterprise standards databa",
        "parse_legal_documentation: Parse text-based legal documents to extract constraints and ",
        "validate_input_against_rule: Check if an input (e.g., data, request) complies with a sing"
    ],
    "L1": [
        "gather_domain_standards: Composes `fetch_enterprise_rule_from_db` and `parse_legal_do",
        "validate_inputs_compliance: Composes a set of atomic validations (likely multiple instan"
    ],
    "L2": [
        "comprehensive_domain_check: Bundles the operations above (`gather_domain_standards`, `va"
    ],
    "L3": [
        "enterprise_domain_grounding_orchestrator"
    ]
},
    "skill_tree": {
    "enterprise/domain_grounding/orchestrator": [
        "enterprise/domain_grounding/comprehensive_domain_check"
    ],
    "enterprise/domain_grounding/comprehensive_domain_check": [
        "enterprise/domain_grounding/gather_domain_standards",
        "enterprise/domain_grounding/validate_inputs_compliance"
    ],
    "enterprise/domain_grounding/gather_domain_standards": [
        "enterprise/domain_grounding/fetch_enterprise_rule_from_db",
        "enterprise/domain_grounding/parse_legal_documentation",
        "enterprise/domain_grounding/validate_input_against_rule"
    ],
    "enterprise/domain_grounding/validate_inputs_compliance": [
        "enterprise/domain_grounding/fetch_enterprise_rule_from_db",
        "enterprise/domain_grounding/parse_legal_documentation",
        "enterprise/domain_grounding/validate_input_against_rule"
    ]
},
    "model_routing": {
    "L0": "codegemma",
    "L1": "qwen3",
    "L2": "qwen3",
    "L3": "deepseek_r1"
},
}
