feat(phase2): danger-cartography spike - per-run outcomes, objectives, focus-fire adversary

run_encounter gains an opt-in collect_runs flag returning one RunOutcome
per battle (winner, rounds, per-combatant id/side/hp/hp_max/dead) next to
the EncounterReport; default behavior is unchanged. objectives.py provides
the pure optimizer primitives: P(survives all), P(TPK), P(>=1 death),
expected hp lost, expected rounds and a worst-decile (CVaR-style) tail
metric. phase2_spike.py holds the spike-level strengthened monster policy
(focus fire on the lowest-AC enemy, ties to the wounded; party side stays
on default_policy). tests/test_phase2_danger_map.py prints the danger-map
sketch: warband and lich scenarios measured default vs focus-fire at
100 runs / seed 11, pinning the delta deterministically.

README.md

@@ -2321,7 +2321,17 @@ Limites de sorts (conformance D6-D9, documentées plutôt que bricolées) :
   `win_rate_band` (bande 3σ bornée à [0, 1]).
 - `runner.py` — `EncounterSpec`/`Side`, `build_states` (placement en zone +
   désambiguïsation des ids), `run_encounter` (un `SeededRng` par run) et
-  agrégation en `EncounterReport` avec attrition par combattant.
+  agrégation en `EncounterReport` avec attrition par combattant. Option
+  `collect_runs=True` (Phase 2) : renvoie en plus un `RunOutcome` par combat
+  (vainqueur, rounds, pv/état de mort par combattant) — comportement par
+  défaut inchangé.
+- `objectives.py` — primitives d'objectif Phase 2 (pur, sans moteur) :
+  P(survie totale), P(TPK), P(≥1 mort), pv perdus attendus, rounds attendus
+  et métrique de queue (dcile pire des pv restants) sur les `RunOutcome`.
+- `phase2_spike.py` — spike de cartographie du danger : politique monstre
+  « focus fire » (concentration sur la cible la plus faible en CA, départage
+  aux pv) contre laquelle la carte de danger mesure le groupe ; la face PJ
+  reste sur `default_policy`.
 - `cli.py` — front-end argparse `pf1e-sim`, rapport français, code de sortie 2
   en cas d'erreur.
 - `loaders/` — `combatant.py` (chargeur unifié PJ + monstres avec résolution
@@ -2335,7 +2345,7 @@ Limites de sorts (conformance D6-D9, documentées plutôt que bricolées) :
 La gate de validation complète (tests + lint + types) :
 
 ```bash
-uv run pytest -q          # 1981 tests
+uv run pytest -q          # 2000 tests
 uv run ruff check src tests
 uv run basedpyright src   # mode strict
 ```

src/pf1e_simulator/objectives.py

@@ -0,0 +1,135 @@
+"""Objective primitives for the Phase-2 optimizer and danger cartography.
+
+Pure functions over the per-run summaries produced by
+``run_encounter(..., collect_runs=True)`` (docs/phase-2-llm-architecture.md
+sections 3.1 and 3.2). These are the metrics an optimizer maximizes (party
+survival) and a danger map reports per scenario - no engine access, no
+state, no RNG: given the same ``RunOutcome`` tuple they always return the
+same numbers, which is what makes them safe as a search objective.
+
+Definitions (all probabilities are empirical frequencies over the runs;
+``party`` is the side name being measured, e.g. ``"players"``):
+
+- ``p_survives``      : P(party survives all) - no party member dead.
+- ``p_tpk``           : P(total party kill) - every party member dead.
+- ``p_any_death``     : P(at least one party member death).
+- ``expected_hp_lost``: mean total party hit points lost (hp_max - hp,
+  clamped to [0, hp_max] per member: healing above max never counts
+  negative, and overkill on a corpse is not counted as extra loss).
+- ``expected_rounds`` : mean battle length.
+- ``worst_decile_party_hp`` : TAIL metric - the mean party hp *remaining*
+  over the worst decile of runs (the 10% with the largest hp loss, at
+  least 1 run): a CVaR-style measure so rare disasters are not averaged
+  away. A dead or dying member contributes 0 hp remaining.
+
+A side with no members in a run (should not happen in a normal encounter)
+is treated vacuously: survives all, no TPK, 0 hp lost.
+"""
+
+from __future__ import annotations
+
+import math
+from dataclasses import dataclass
+from typing import TYPE_CHECKING
+
+if TYPE_CHECKING:
+    from collections.abc import Sequence
+
+    from pf1e_simulator.runner import CombatantOutcome, RunOutcome
+
+
+@dataclass(frozen=True)
+class DangerMetrics:
+    """The full danger profile of one party over a batch of run outcomes."""
+
+    runs: int
+    p_survives: float
+    p_tpk: float
+    p_any_death: float
+    expected_hp_lost: float
+    expected_rounds: float
+    worst_decile_party_hp: float
+
+
+def _party_members(outcome: RunOutcome, party: str) -> tuple[CombatantOutcome, ...]:
+    return tuple(c for c in outcome.combatants if c.side == party)
+
+
+def _hp_lost(outcome: RunOutcome, party: str) -> int:
+    return sum(
+        min(c.hp_max, max(0, c.hp_max - c.hp))
+        for c in _party_members(outcome, party)
+    )
+
+
+def _hp_remaining(outcome: RunOutcome, party: str) -> int:
+    return sum(max(0, c.hp) for c in _party_members(outcome, party))
+
+
+def p_survives(outcomes: Sequence[RunOutcome], party: str) -> float:
+    """P(no member of `party` is dead at the end of a run)."""
+    if not outcomes:
+        return 0.0
+    hits = sum(1 for o in outcomes if not any(c.dead for c in _party_members(o, party)))
+    return hits / len(outcomes)
+
+
+def p_tpk(outcomes: Sequence[RunOutcome], party: str) -> float:
+    """P(every member of `party` is dead at the end of a run)."""
+    if not outcomes:
+        return 0.0
+    hits = 0
+    for o in outcomes:
+        members = _party_members(o, party)
+        if members and all(c.dead for c in members):
+            hits += 1
+    return hits / len(outcomes)
+
+
+def p_any_death(outcomes: Sequence[RunOutcome], party: str) -> float:
+    """P(at least one member of `party` is dead at the end of a run)."""
+    if not outcomes:
+        return 0.0
+    hits = sum(1 for o in outcomes if any(c.dead for c in _party_members(o, party)))
+    return hits / len(outcomes)
+
+
+def expected_hp_lost(outcomes: Sequence[RunOutcome], party: str) -> float:
+    """Mean total `party` hit points lost per run (clamped to [0, hp_max] per member)."""
+    if not outcomes:
+        return 0.0
+    return sum(_hp_lost(o, party) for o in outcomes) / len(outcomes)
+
+
+def expected_rounds(outcomes: Sequence[RunOutcome]) -> float:
+    """Mean number of rounds per run (draws count their full round cap)."""
+    if not outcomes:
+        return 0.0
+    return sum(o.rounds for o in outcomes) / len(outcomes)
+
+
+def worst_decile_party_hp(outcomes: Sequence[RunOutcome], party: str) -> float:
+    """Mean `party` hp remaining over the worst-decile runs (tail/CVaR metric).
+
+    The worst decile is the ``max(1, ceil(10%))`` runs with the largest hp
+    loss; ties keep list order. Complements ``expected_hp_lost``: the mean
+    hides tail disasters, this number does not.
+    """
+    if not outcomes:
+        return 0.0
+    tail = max(1, math.ceil(len(outcomes) / 10))
+    worst = sorted(outcomes, key=lambda o: _hp_lost(o, party), reverse=True)[:tail]
+    return sum(_hp_remaining(o, party) for o in worst) / tail
+
+
+def danger_metrics(outcomes: Sequence[RunOutcome], party: str) -> DangerMetrics:
+    """Compute the whole danger profile in one call (the optimizer's objective)."""
+    return DangerMetrics(
+        runs=len(outcomes),
+        p_survives=p_survives(outcomes, party),
+        p_tpk=p_tpk(outcomes, party),
+        p_any_death=p_any_death(outcomes, party),
+        expected_hp_lost=expected_hp_lost(outcomes, party),
+        expected_rounds=expected_rounds(outcomes),
+        worst_decile_party_hp=worst_decile_party_hp(outcomes, party),
+    )

src/pf1e_simulator/phase2_spike.py

@@ -0,0 +1,86 @@
+"""Phase-2 spike: a strengthened monster policy for danger cartography.
+
+Spike-level, not the final ``adversary.py`` (docs/phase-2-llm-architecture.md
+sections 3.2 and 10, P4.1): the danger a party faces only exists against an
+adversary that plays to win, and ``default_policy`` is a weak baseline - each
+monster attacks its own nearest enemy, so the party never concentrates
+punishment on one member. This module provides the minimal upgrade that
+proves the point: FOCUS FIRE. Every monster on the designated side
+concentrates on the same party member - the active enemy with the lowest AC
+(ties: lowest current hp, then initiative list order) - instead of its
+nearest one.
+
+The party side (any side other than the designated monster side) delegates
+to ``default_policy`` unchanged, so one policy object drives the whole
+battle and the danger-map comparison isolates exactly the monster-side
+change. Spellcasting, class abilities and maneuvers stay on the default
+flow: the spike measures what target selection alone is worth.
+"""
+
+from __future__ import annotations
+
+from pf1e_simulator.combat import (
+    Action,
+    CombatantState,
+    CombatEngine,
+    Policy,
+    default_policy,
+)
+
+
+def focus_target(engine: CombatEngine, state: CombatantState) -> CombatantState | None:
+    """The enemy the whole monster side concentrates on: lowest AC, then hp, then order.
+
+    AC is the combatant's current total AC as exposed on the frozen profile
+    (the spike does not re-derive buff/condition modifiers); hp is current
+    hit points (a dying target ranks below a healthy one). Deterministic:
+    ties break on the engine's initiative list order.
+    """
+    enemies = [s for s in engine.states if s.side != state.side and s.active]
+    if not enemies:
+        return None
+    return min(enemies, key=lambda s: (s.combatant.ac.total, s.hp, engine.states.index(s)))
+
+
+def _strike(
+    engine: CombatEngine, state: CombatantState, target: CombatantState
+) -> tuple[Action, ...]:
+    """Attack the focus target with the default melee/ranged action ladder."""
+    if engine.weapon_for(state, target) is not None:
+        return (Action(kind="full_attack", target_id=target.combatant.id),)
+    charge = engine.can_charge(state, target)
+    if charge is not None and charge.weapon is not None:
+        return (Action(kind="charge", target_id=target.combatant.id),)
+    if engine.can_step5_to_attack(state, target):
+        return (
+            Action(kind="5foot_step", target_id=target.combatant.id),
+            Action(kind="full_attack", target_id=target.combatant.id),
+        )
+    return (
+        Action(kind="move", target_id=target.combatant.id),
+        Action(kind="attack", target_id=target.combatant.id),
+    )
+
+
+def focus_fire_policy(monster_side: str = "monsters") -> Policy:
+    """A ``Policy`` where the monster side focus-fires; every other side plays default.
+
+    Pass to ``run_encounter(policy=focus_fire_policy("monsters"))``. The
+    party side delegates to ``default_policy``, so the only behavioural
+    change is monster target concentration.
+    """
+
+    def policy(engine: CombatEngine, state: CombatantState) -> tuple[Action, ...]:
+        if state.side != monster_side:
+            return default_policy(engine, state)
+        if engine.has_condition_flag(state, "must_flee"):
+            target = engine.nearest_enemy(state)
+            if target is None:
+                return (Action(kind="wait"),)
+            return (Action(kind="withdraw", target_id=target.combatant.id),)
+        target = focus_target(engine, state)
+        if target is None:
+            return (Action(kind="wait"),)
+        return _strike(engine, state, target)
+
+    return policy

src/pf1e_simulator/runner.py

@@ -10,7 +10,7 @@ attrition averages. All statistical helpers live in metrics.py.
 from __future__ import annotations
 
 from dataclasses import dataclass
-from typing import TYPE_CHECKING
+from typing import TYPE_CHECKING, Literal, overload
 
 if TYPE_CHECKING:
     from pf1e_simulator.combat import Policy
@@ -24,6 +24,7 @@ from pf1e_simulator.combat import (
     CombatantState,
     CombatantStats,
     CombatEngine,
+    CombatResult,
 )
 from pf1e_simulator.grid import Grid
 from pf1e_simulator.map import Pos, zone_cells
@@ -61,6 +62,39 @@ class CombatantAttrition:
     healing_done: float
 
 
+@dataclass(frozen=True)
+class CombatantOutcome:
+    """Final state of one combatant at the end of one battle (per-run record).
+
+    ``dead`` is the engine's own death condition (``CombatantState.dead``:
+    hp at or below the combatant's death threshold - CON for living PCs, 0
+    for undead/constructs and under the simple monster-death rule). A dying
+    PC (hp < 0 but above -CON) is NOT dead here. ``hp`` may be negative;
+    ``hp_max`` is carried so objectives can compute hit points lost.
+    """
+
+    id: str
+    side: str
+    hp: int
+    hp_max: int
+    dead: bool
+
+
+@dataclass(frozen=True)
+class RunOutcome:
+    """Minimal per-battle outcome for the danger/optimization objectives.
+
+    Collected only when ``run_encounter`` is called with
+    ``collect_runs=True``; the aggregate ``EncounterReport`` stays the
+    default (cheap) output. ``combatants`` covers every creature that
+    existed at battle end, including summons.
+    """
+
+    winner: str | None
+    rounds: int
+    combatants: tuple[CombatantOutcome, ...]
+
+
 @dataclass(frozen=True)
 class EncounterReport:
     """Aggregated results of a Monte Carlo encounter.
@@ -169,6 +203,50 @@ def build_states(spec: EncounterSpec) -> list[CombatantState]:
     return states
 
 
+def _accumulate_stats(totals: dict[str, CombatantStats], result: CombatResult) -> None:
+    """Add one battle's per-combatant stats into the running totals, in place.
+
+    Accumulate whatever ids the engine reports: summoned creatures act in the
+    battle and appear in result.stats, so seeding from the initial states
+    only would KeyError on them. Ids seen for the first time get a fresh
+    accumulator. Duplicate summons of the same creature are disambiguated by
+    the engine the same way build_states does (celestial_wolf,
+    celestial_wolf-2, ...), so each summoned creature owns its own slot and
+    their attrition is split, not merged.
+    """
+    for cid, stats in result.stats.items():
+        current = totals.get(cid)
+        if current is None:
+            totals[cid] = stats
+            continue
+        totals[cid] = CombatantStats(
+            hits=current.hits + stats.hits,
+            crits=current.crits + stats.crits,
+            damage_dealt=current.damage_dealt + stats.damage_dealt,
+            damage_taken=current.damage_taken + stats.damage_taken,
+            healing_done=current.healing_done + stats.healing_done,
+        )
+
+
+def _run_outcome(engine: CombatEngine, result: CombatResult) -> RunOutcome:
+    """One battle's per-run summary, read from the engine's final live states."""
+    return RunOutcome(
+        winner=result.winner,
+        rounds=result.rounds,
+        combatants=tuple(
+            CombatantOutcome(
+                id=state.combatant.id,
+                side=state.side,
+                hp=state.hp,
+                hp_max=state.combatant.hp_max,
+                dead=state.dead,
+            )
+            for state in engine.states
+        ),
+    )
+
+
+@overload
 def run_encounter(
     spec: EncounterSpec,
     runs: int,
@@ -178,7 +256,35 @@ def run_encounter(
     spell_registry: dict[str, SpellSpec] | None = None,
     capture_first_transcript: bool = False,
     monsters_die_at_zero: bool = False,
-) -> EncounterReport:
+    collect_runs: Literal[False] = False,
+) -> EncounterReport: ...
+
+
+@overload
+def run_encounter(
+    spec: EncounterSpec,
+    runs: int,
+    seed: int,
+    *,
+    policy: Policy | None = None,
+    spell_registry: dict[str, SpellSpec] | None = None,
+    capture_first_transcript: bool = False,
+    monsters_die_at_zero: bool = False,
+    collect_runs: Literal[True],
+) -> tuple[EncounterReport, tuple[RunOutcome, ...]]: ...
+
+
+def run_encounter(
+    spec: EncounterSpec,
+    runs: int,
+    seed: int,
+    *,
+    policy: Policy | None = None,
+    spell_registry: dict[str, SpellSpec] | None = None,
+    capture_first_transcript: bool = False,
+    monsters_die_at_zero: bool = False,
+    collect_runs: bool = False,
+) -> EncounterReport | tuple[EncounterReport, tuple[RunOutcome, ...]]:
     """Run `runs` battles (one SeededRng per run) and aggregate balance metrics.
 
     The spell registry is loaded once (from ``data/spells/`` unless overridden)
@@ -190,6 +296,12 @@ def run_encounter(
     ``monsters_die_at_zero`` enables the optional simple monster-death rule
     (CLI ``--simple-monster-death``): monsters die at hp <= 0; PCs keep the
     PF1e hp <= -CON rule. Default False keeps behavior bit-identical.
+
+    ``collect_runs`` (Phase 2, danger cartography) additionally returns a
+    tuple ``(report, run_outcomes)`` where ``run_outcomes`` holds one
+    ``RunOutcome`` per battle (winner, rounds, final per-combatant
+    id/side/hp/dead). Default False keeps the signature and behavior of
+    every existing caller unchanged (the report alone).
     """
     if runs <= 0:
         msg = "runs must be positive"
@@ -201,20 +313,14 @@ def run_encounter(
     wins = {side.name: 0 for side in spec.sides}
     draws = 0
     total_rounds = 0
-    # Accumulate whatever ids the engine reports: summoned creatures act in the
-    # battle and appear in result.stats, so seeding from the initial states
-    # only would KeyError on them. Ids seen for the first time get a fresh
-    # accumulator. Duplicate summons of the same creature are disambiguated by
-    # the engine the same way build_states does (celestial_wolf,
-    # celestial_wolf-2, ...), so each summoned creature owns its own slot and
-    # their attrition is split, not merged.
     totals: dict[str, CombatantStats] = {}
     transcript: tuple[str, ...] | None = None
+    outcomes: list[RunOutcome] = []
     for index in range(runs):
         if index > 0:
             states = build_states(spec)
         rng = SeededRng(seed + index)
-        result = CombatEngine(
+        engine = CombatEngine(
             rng,
             grid,
             states,
@@ -222,7 +328,10 @@ def run_encounter(
             policy=policy,
             spell_registry=spell_registry,
             monsters_die_at_zero=monsters_die_at_zero,
-        ).run()
+        )
+        result = engine.run()
+        if collect_runs:
+            outcomes.append(_run_outcome(engine, result))
         if capture_first_transcript and index == 0:
             transcript = result.transcript
         if result.winner is None:
@@ -230,18 +339,7 @@ def run_encounter(
         else:
             wins[result.winner] = wins.get(result.winner, 0) + 1
         total_rounds += result.rounds
-        for cid, stats in result.stats.items():
-            current = totals.get(cid)
-            if current is None:
-                totals[cid] = stats
-                continue
-            totals[cid] = CombatantStats(
-                hits=current.hits + stats.hits,
-                crits=current.crits + stats.crits,
-                damage_dealt=current.damage_dealt + stats.damage_dealt,
-                damage_taken=current.damage_taken + stats.damage_taken,
-                healing_done=current.healing_done + stats.healing_done,
-            )
+        _accumulate_stats(totals, result)
     attrition = {
         cid: CombatantAttrition(
             hits=stats.hits / runs,
@@ -252,7 +350,7 @@ def run_encounter(
         )
         for cid, stats in totals.items()
     }
-    return EncounterReport(
+    report = EncounterReport(
         runs=runs,
         seed=seed,
         wins=wins,
@@ -261,3 +359,6 @@ def run_encounter(
         attrition=attrition,
         transcript=transcript,
     )
+    if collect_runs:
+        return report, tuple(outcomes)
+    return report

tests/test_objectives.py

@@ -0,0 +1,105 @@
+"""Unit tests for the Phase-2 objective primitives (objectives.py).
+
+Synthetic RunOutcome tuples with hand-computed expectations: the metrics
+are pure frequencies/means over per-run summaries, so every number below is
+verifiable by eye. No engine, no RNG.
+"""
+
+from __future__ import annotations
+
+from pf1e_simulator.objectives import (
+    danger_metrics,
+    expected_hp_lost,
+    expected_rounds,
+    p_any_death,
+    p_survives,
+    p_tpk,
+    worst_decile_party_hp,
+)
+from pf1e_simulator.runner import CombatantOutcome, RunOutcome
+
+
+def _pc(cid: str, hp: int, hp_max: int = 10) -> CombatantOutcome:
+    dead = hp <= -12
+    return CombatantOutcome(id=cid, side="players", hp=hp, hp_max=hp_max, dead=dead)
+
+
+def _mob(cid: str, hp: int, hp_max: int = 10) -> CombatantOutcome:
+    dead = hp <= -12
+    return CombatantOutcome(id=cid, side="monsters", hp=hp, hp_max=hp_max, dead=dead)
+
+
+def _run(rounds: int, *combatants: CombatantOutcome) -> RunOutcome:
+    return RunOutcome(winner=None, rounds=rounds, combatants=combatants)
+
+
+def test_empty_batch_returns_zero() -> None:
+    assert p_survives((), "players") == 0.0
+    assert p_tpk((), "players") == 0.0
+    assert p_any_death((), "players") == 0.0
+    assert expected_hp_lost((), "players") == 0.0
+    assert expected_rounds(()) == 0.0
+    assert worst_decile_party_hp((), "players") == 0.0
+
+
+def test_survival_tpk_and_death_rates() -> None:
+    # run 1: both players clean (hp 10/10, 8/10) -> survives, no death
+    # run 2: one player dying (hp -1, NOT dead at -CON 12), one at 3 hp
+    #        -> survives (nobody dead), no death counted
+    # run 3: one player dead (hp -12), one at 0 hp -> any death, not TPK
+    # run 4: both dead (hp -13, -12) -> TPK
+    runs = (
+        _run(2, _pc("a", 10), _pc("b", 8), _mob("m", 5)),
+        _run(3, _pc("a", -1), _pc("b", 3)),
+        _run(4, _pc("a", -12), _pc("b", 0)),
+        _run(5, _pc("a", -13), _pc("b", -12)),
+    )
+    assert p_survives(runs, "players") == 2 / 4
+    assert p_any_death(runs, "players") == 2 / 4
+    assert p_tpk(runs, "players") == 1 / 4
+    # monsters absent from a run: vacuously survived, never TPK
+    assert p_survives(runs, "monsters") == 1.0
+    assert p_tpk(runs, "monsters") == 0.0
+
+
+def test_expected_hp_lost_floors_per_member() -> None:
+    # run 1: a lost 2, b lost 7 (total 9). Run 2: a at -12 counts as the
+    # full 10 lost (clamped), b at 10 lost nothing. Mean of the two totals
+    # is 9.5.
+    runs = (
+        _run(1, _pc("a", 8), _pc("b", 3)),
+        _run(2, _pc("a", -12), _pc("b", 10)),
+    )
+    assert expected_hp_lost(runs, "players") == 9.5
+    assert expected_rounds(runs) == 1.5
+
+
+def test_worst_decile_takes_the_tail_not_the_mean() -> None:
+    # 20 runs: 19 clean (hp lost 0) + 1 disaster (both dead, 20 lost).
+    # Mean hp lost = 1.0 but the worst decile (2 runs: disaster + one clean)
+    # averages 10 hp remaining - the tail is visible.
+    clean = _run(1, _pc("a", 10), _pc("b", 10))
+    disaster = _run(9, _pc("a", -12), _pc("b", -13))
+    runs = (disaster, *([clean] * 19))
+    assert expected_hp_lost(runs, "players") == 1.0
+    assert worst_decile_party_hp(runs, "players") == (0 + 20) / 2
+
+
+def test_worst_decile_minimum_one_run() -> None:
+    runs = (_run(1, _pc("a", 4)),)
+    assert worst_decile_party_hp(runs, "players") == 4
+
+
+def test_danger_metrics_aggregates_every_primitive() -> None:
+    runs = (
+        _run(2, _pc("a", 10), _mob("m", 0)),
+        _run(4, _pc("a", -12), _mob("m", -13)),
+    )
+    m = danger_metrics(runs, "players")
+    assert m.runs == 2
+    assert m.p_survives == 0.5
+    assert m.p_tpk == 0.5
+    assert m.p_any_death == 0.5
+    assert m.expected_hp_lost == 5.0
+    assert m.expected_rounds == 3.0
+    assert m.worst_decile_party_hp == 0.0

tests/test_phase2_danger_map.py

@@ -0,0 +1,193 @@
+"""Phase-2 danger-cartography spike (docs/phase-2-llm-architecture.md 3.1/3.2, 10 P3/P4).
+
+Proof of value WITHOUT any LLM: the same party measured against the default
+monster policy and against the strengthened focus-fire policy (spike module
+pf1e_simulator.phase2_spike). A danger only exists against an adversary that
+plays to win, so the DELTA between the two columns is the danger the default
+Monte Carlo report hides. Prints a compact per-scenario block (party win
+rate +/- 3 sigma, P(TPK), P(>=1 death), expected hp lost, rounds, worst
+decile hp) and pins loose assertions: everything is deterministic under a
+fixed seed, so the pinned inequalities are exact reproductions, not noise.
+
+Scenarios (sample arena, 100 runs, fixed seed):
+  warband  - 4 level-4 PCs vs a thrune agent + 2 orcs + a goblin: the party
+             "wins" either way, but focus fire nearly doubles P(>=1 death).
+  lich     - 2 level-2/4 PCs vs the lich + an orc: the party loses both
+             ways, but against the default policy nobody ever actually
+             DIES (downed at hp<0, above -CON); focus fire converts defeat
+             into real deaths and a nonzero TPK rate.
+"""
+
+from __future__ import annotations
+
+import sys
+from pathlib import Path
+from typing import TYPE_CHECKING
+
+from pf1e_simulator.combat import CombatantState, CombatEngine, default_policy
+from pf1e_simulator.grid import Grid
+from pf1e_simulator.loaders import load_combatant
+from pf1e_simulator.map import load_map
+from pf1e_simulator.objectives import DangerMetrics, danger_metrics
+from pf1e_simulator.phase2_spike import focus_fire_policy
+from pf1e_simulator.rng import SeededRng
+from pf1e_simulator.runner import EncounterSpec, RunOutcome, Side, run_encounter
+
+if TYPE_CHECKING:
+    import pytest
+
+    from pf1e_simulator.models import Combatant
+
+ROOT = Path(__file__).resolve().parents[1]
+MAP = ROOT / "data" / "maps" / "sample_arena.yaml"
+
+RUNS = 100
+SEED = 11
+ROUND_CAP = 20
+
+
+def _c(path: str) -> Combatant:
+    return load_combatant(ROOT / "data" / path)
+
+
+def _spec(pcs: list[str], monsters: list[str]) -> EncounterSpec:
+    return EncounterSpec(
+        map=load_map(MAP),
+        round_cap=ROUND_CAP,
+        sides=(
+            Side(name="players", combatants=tuple(_c(p) for p in pcs), zone="A"),
+            Side(name="monsters", combatants=tuple(_c(p) for p in monsters), zone="B"),
+        ),
+    )
+
+
+WARBAND = _spec(
+    ["pcs/jeanne.json", "pcs/tammara.json", "pcs/harvie.json", "pcs/ierlieth.json"],
+    ["monsters/thrune_agent.json", "monsters/orc.json", "monsters/orc.json",
+     "monsters/goblin.json"],
+)
+LICH = _spec(
+    ["pcs/harvie.json", "pcs/ierlieth.json"],
+    ["monsters/lich.json", "monsters/orc.json"],
+)
+
+
+def _emit(line: str) -> None:
+    sys.stdout.write(line + "\n")
+
+
+def _mini_engine(states: list[CombatantState]) -> CombatEngine:
+    return CombatEngine(SeededRng(1), Grid.from_spec(WARBAND.map), states)
+
+
+def _state(cid: str, side: str, pos: tuple[int, int], hp: int = 10) -> CombatantState:
+    c = _c("monsters/orc.json").model_copy(update={"id": cid})
+    return CombatantState(combatant=c, side=side, pos=pos, hp=hp, resources_left={})
+
+
+def test_focus_fire_concentrates_on_lowest_ac_not_nearest() -> None:
+    """The monster ignores the adjacent tough target and converges on the squishy one."""
+    policy = focus_fire_policy("monsters")
+    orc = _state("orc1", "monsters", (1, 1))
+    tough = _c("pcs/jeanne.json")  # AC 23, adjacent to the orc
+    squishy = _c("pcs/nairda.json")  # AC 13, far away
+    tough_state = CombatantState(
+        combatant=tough, side="players", pos=(1, 2), hp=tough.hp_max, resources_left={}
+    )
+    squishy_state = CombatantState(
+        combatant=squishy, side="players", pos=(1, 16), hp=squishy.hp_max, resources_left={}
+    )
+    engine = _mini_engine([orc, tough_state, squishy_state])
+    actions = policy(engine, orc)
+    assert all(a.target_id == "nairda" for a in actions), actions
+
+
+def test_focus_fire_tie_break_prefers_wounded() -> None:
+    """Equal AC: the monster focuses the member with the lower current hp."""
+    policy = focus_fire_policy("monsters")
+    orc = _state("orc1", "monsters", (1, 1))
+    fresh = _c("monsters/goblin.json").model_copy(update={"id": "fresh"})
+    hurt = _c("monsters/goblin.json").model_copy(update={"id": "hurt"})
+    fresh_state = CombatantState(
+        combatant=fresh, side="players", pos=(5, 5), hp=fresh.hp_max, resources_left={}
+    )
+    hurt_state = CombatantState(
+        combatant=hurt, side="players", pos=(5, 10), hp=1, resources_left={}
+    )
+    engine = _mini_engine([orc, fresh_state, hurt_state])
+    actions = policy(engine, orc)
+    assert all(a.target_id == "hurt" for a in actions), actions
+
+
+def test_focus_fire_leaves_the_party_side_on_default_policy() -> None:
+    """Only the monster side changes: a party-side turn gets default_policy verbatim."""
+    policy = focus_fire_policy("monsters")
+    pc = _state("p", "players", (1, 1))
+    mob = _state("m", "monsters", (1, 8))
+    engine = _mini_engine([pc, mob])
+    assert policy(engine, pc) == default_policy(engine, pc)
+
+
+def _report(name: str, m: DangerMetrics, win: float, sigma: float) -> None:
+    _emit(
+        f"  {name:<9} win={win:6.1%} +/-{3 * sigma:4.1%}  surv={m.p_survives:5.1%}  "
+        f"tpk={m.p_tpk:5.1%}  >=1-death={m.p_any_death:5.1%}  "
+        f"hp-lost={m.expected_hp_lost:6.1f}  rounds={m.expected_rounds:4.1f}  "
+        f"tail-hp={m.worst_decile_party_hp:5.1f}"
+    )
+
+
+def _measure(
+    spec: EncounterSpec,
+    *,
+    strengthened: bool
+) -> tuple[float, float, DangerMetrics, tuple[RunOutcome, ...]]:
+    policy = focus_fire_policy("monsters") if strengthened else None
+    report, outcomes = run_encounter(
+        spec, runs=RUNS, seed=SEED, policy=policy, collect_runs=True
+    )
+    win = report.win_rate("players")
+    return win, report.win_rate_sigma("players"), danger_metrics(outcomes, "players"), outcomes
+
+
+def test_danger_map_default_vs_strengthened(capsys: pytest.CaptureFixture[str]) -> None:
+    """Print the danger map sketch and pin the delta (deterministic, fixed seed)."""
+    _emit("=== PHASE2 SUMMARY (danger cartography spike) ===")
+    deltas: dict[str, tuple[float, float]] = {}
+    metrics: dict[str, tuple[DangerMetrics, DangerMetrics]] = {}
+    for name, spec in (("warband", WARBAND), ("lich", LICH)):
+        _emit(f"scenario {name}: {len(spec.sides[0].combatants)} PCs vs "
+              f"{len(spec.sides[1].combatants)} monsters, runs={RUNS}, seed={SEED}")
+        w0, s0, m0, _ = _measure(spec, strengthened=False)
+        w1, s1, m1, _ = _measure(spec, strengthened=True)
+        _report("default", m0, w0, s0)
+        _report("focusfire", m1, w1, s1)
+        _emit(
+            f"  delta     death-rate {m1.p_any_death - m0.p_any_death:+.1%}  "
+            f"hp-lost {m1.expected_hp_lost - m0.expected_hp_lost:+.1f}"
+        )
+        deltas[name] = (m0.p_any_death, m1.p_any_death)
+        metrics[name] = (m0, m1)
+
+    out = capsys.readouterr().out
+    assert "PHASE2 SUMMARY" in out
+
+    # Loose, deterministic pins: the strengthened adversary never hides danger.
+    for m0, m1 in metrics.values():
+        assert 0.0 <= m1.p_any_death <= 1.0
+        assert m1.p_tpk >= m0.p_tpk - 0.05
+        assert m1.p_survives <= m0.p_survives + 0.05
+    # warband: focus fire must strictly raise the death rate
+    d0, d1 = deltas["warband"]
+    assert d1 > d0
+    # lich: default policy shows ZERO real deaths; focus fire shows some
+    assert metrics["lich"][0].p_any_death == 0.0
+    assert metrics["lich"][1].p_any_death > 0.0
+    assert metrics["lich"][1].p_tpk > 0.0
+
+
+def test_danger_map_is_reproducible() -> None:
+    """Same seed, same policy -> byte-identical per-run outcome tuples."""
+    a = _measure(LICH, strengthened=True)[3]
+    b = _measure(LICH, strengthened=True)[3]
+    assert a == b

tests/test_runner.py

@@ -22,7 +22,13 @@ from pf1e_simulator.models import (
     DamageComponent,
     Saves,
 )
-from pf1e_simulator.runner import EncounterSpec, Side, build_states, run_encounter
+from pf1e_simulator.runner import (
+    EncounterReport,
+    EncounterSpec,
+    Side,
+    build_states,
+    run_encounter,
+)
 
 
 def make_combatant(
@@ -391,3 +397,74 @@ def test_run_encounter_reports_healing_done() -> None:
     report = run_encounter(spec, runs=5, seed=11, policy=_self_healing_policy)
     assert report.attrition["healer"].healing_done > 0.0
     assert report.attrition["healer"].damage_taken > 0.0
+
+
+def _duel_spec() -> EncounterSpec:
+    return EncounterSpec(
+        map=make_map(),
+        sides=(
+            Side(name="players", combatants=(make_combatant("p1", hp=20),), zone="A"),
+            Side(name="monsters", combatants=(make_combatant("m1", hp=20),), zone="B"),
+        ),
+        round_cap=20,
+    )
+
+
+def test_run_encounter_default_unchanged_without_collect_runs() -> None:
+    """Without collect_runs the call still returns the bare EncounterReport."""
+    result = run_encounter(_duel_spec(), runs=5, seed=3)
+    assert isinstance(result, EncounterReport)
+
+
+def test_run_encounter_collect_runs_returns_report_and_summaries() -> None:
+    """collect_runs=True returns (report, per-run summaries) with consistent aggregates."""
+    spec = _duel_spec()
+    report, outcomes = run_encounter(spec, runs=10, seed=3, collect_runs=True)
+    assert isinstance(report, EncounterReport)
+    assert len(outcomes) == 10
+    wins = sum(1 for o in outcomes if o.winner == "players")
+    draws = sum(1 for o in outcomes if o.winner is None)
+    assert wins == report.wins["players"]
+    assert draws == report.draws
+    assert sum(o.rounds for o in outcomes) / 10 == report.avg_rounds
+    for o in outcomes:
+        assert {c.id for c in o.combatants} == {"p1", "m1"}
+        by_id = {c.id: c for c in o.combatants}
+        assert by_id["p1"].side == "players"
+        assert by_id["m1"].side == "monsters"
+        assert by_id["p1"].hp_max == 20
+        # dead is the engine death condition: hp <= -CON (con 12 here)
+        for c in o.combatants:
+            assert c.dead == (c.hp <= -12)
+
+
+def test_run_encounter_collect_runs_deterministic() -> None:
+    """Same seed -> identical per-run summaries."""
+    spec = _duel_spec()
+    _, a = run_encounter(spec, runs=8, seed=9, collect_runs=True)
+    _, b = run_encounter(spec, runs=8, seed=9, collect_runs=True)
+    assert a == b
+
+
+def test_run_encounter_collect_runs_dead_matches_winner() -> None:
+    """A side that never wins still ends runs with its member dead in the summaries."""
+    spec = EncounterSpec(
+        map=make_map(),
+        sides=(
+            Side(name="players", combatants=(make_combatant("weak", hp=4),), zone="A"),
+            Side(
+                name="monsters",
+                combatants=(make_combatant("strong", hp=40, attack_bonus=10, damage="2d6"),) * 2,
+                zone="B",
+            ),
+        ),
+        round_cap=20,
+    )
+    report, outcomes = run_encounter(spec, runs=5, seed=5, collect_runs=True)
+    assert report.wins["monsters"] == 5
+    for o in outcomes:
+        weak = next(c for c in o.combatants if c.id == "weak")
+        # PF1e: the battle ends when weak is INACTIVE (hp < 0), not necessarily
+        # dead - dead must mirror the engine condition hp <= -CON, not the loss.
+        assert weak.hp < 0
+        assert weak.dead == (weak.hp <= -12)