# CorpusFetch Method Slice (Zero-Prose Python Stdlib Reference)
# Canonical Residual: https://corpusfetch.com/c/how-must-an-instance-reason-about-infinite-tailed-consequences-of-finite-actions.md
# Remnant Warrant:    https://corpusfetch.com/c/how-must-an-instance-reason-about-infinite-tailed-consequences-of-finite-actions.warrant.json
# Markdown SHA-256:   942cfc42f9553e0eb2c91b6f264c6c7f5f623b936d95d0e088697a2e97e16523
# Code AST SHA-256:   693ee48385f9606b30b3412d9a563fc6a3c69f4ab9ab2e45525926bd92ed35c3
# Verified Classes:   TailRiskVerdict, ActionTailProfile, TailRiskState, TailRiskPolicy, TailRiskManifest, InfiniteTailGuard
# Defensive Guards:   0 fail-closed invariants (zero external deps)

from dataclasses import dataclass
from enum import Enum, auto
import hashlib
import json

class TailRiskVerdict(Enum):
    BOUNDED_CONSEQUENCES = auto()
    TAIL_WITHIN_BUDGET = auto()
    TAIL_EXCEEDS_BUDGET = auto()
    COMPOUNDED_TAIL_RISK = auto()

@dataclass(frozen=True)
class ActionTailProfile:
    action_id: str
    has_unbounded_tail: bool
    tail_probability: float  # P(consequence > threshold)
    tail_magnitude_estimate: float  # expected magnitude given tail
    is_always_reversible: bool

@dataclass(frozen=True)
class TailRiskState:
    actions: tuple[ActionTailProfile, ...]
    tail_risk_budget: float  # max acceptable cumulative tail probability
    threshold_magnitude: float

@dataclass(frozen=True)
class TailRiskPolicy:
    require_worst_case_bounding: bool

@dataclass(frozen=True)
class TailRiskManifest:
    verdict: TailRiskVerdict
    cumulative_tail_probability: float
    directive: str
    manifest_digest: str

class InfiniteTailGuard:
    @staticmethod
    def _hash(data: str) -> str:
        return hashlib.sha256(data.encode("utf-8")).hexdigest()

    @classmethod
    def evaluate_actions(
        cls, state: TailRiskState, policy: TailRiskPolicy
    ) -> TailRiskManifest:
        
        # Gate 1: Any unbounded tails?
        unbounded = [a for a in state.actions if a.has_unbounded_tail]
        if not unbounded:
            digest = cls._hash(json.dumps({
                "actions": str(len(state.actions)),
                "tails": "BOUNDED"
            }, sort_keys=True))
            return TailRiskManifest(
                verdict=TailRiskVerdict.BOUNDED_CONSEQUENCES,
                cumulative_tail_probability=0.0,
                directive=f"PROCEED: All {len(state.actions)} actions have bounded consequences.",
                manifest_digest=digest
            )

        # Gate 2: Reversibility
        non_reversible_unbounded = [a for a in unbounded if not a.is_always_reversible]
        if not non_reversible_unbounded:
            digest = cls._hash(json.dumps({
                "unbounded": str(len(unbounded)),
                "reversible": "ALL"
            }, sort_keys=True))
            return TailRiskManifest(
                verdict=TailRiskVerdict.TAIL_WITHIN_BUDGET,
                cumulative_tail_probability=0.0,
                directive=f"PROCEED: Unbounded tails are all reversible.",
                manifest_digest=digest
            )

        # Gate 3: Compounding
        cumulative_tail_prob = 1.0
        for action in non_reversible_unbounded:
            cumulative_tail_prob *= (1.0 - action.tail_probability)
        cumulative_tail_prob = 1.0 - cumulative_tail_prob

        if cumulative_tail_prob > state.tail_risk_budget:
            return TailRiskManifest(
                verdict=TailRiskVerdict.COMPOUNDED_TAIL_RISK,
                cumulative_tail_probability=cumulative_tail_prob,
                directive=f"HALT: Cumulative tail probability {cumulative_tail_prob:.4f} > {state.tail_risk_budget:.4f}.",
                manifest_digest=cls._hash(f"COMPOUNDED:{cumulative_tail_prob:.4f}")
            )

        # Gate 4: Within budget
        digest = cls._hash(json.dumps({
            "unbounded_non_reversible": str(len(non_reversible_unbounded)),
            "cumulative_tail": f"{cumulative_tail_prob:.4f}",
            "budget": f"{state.tail_risk_budget:.4f}"
        }, sort_keys=True))
        
        return TailRiskManifest(
            verdict=TailRiskVerdict.TAIL_WITHIN_BUDGET,
            cumulative_tail_probability=cumulative_tail_prob,
            directive=f"PROCEED: Cumulative tail probability {cumulative_tail_prob:.4f} within budget {state.tail_risk_budget:.4f}.",
            manifest_digest=digest
        )