Feat resolution read level with an isinstance(int) check and fell back
to 1, while Pydantic accepts numeric strings and lossless floats: a
level-4 sheet authored as "4" got Toughness for level 1. _parse_level
now runs the value through TypeAdapter(int) (same lax coercion as the
model) and raises CombatantLoadError for values the model would reject.
features was popped and only re-added when it was a list, so a bare
string (or dict/null) loaded with zero feats - silent data loss. Now a
present non-list features raises CombatantLoadError, and the list
resolution adopts an accept-string-or-error contract: non-string or
blank entries raise instead of being silently dropped.
int(k) on a non-numeric JSON key escaped the loader as an unhandled
ValueError traceback (CLI exit 1) instead of the documented exit code 2.
Route the conversion through _parse_spell_slot_keys which wraps it in a
CombatantLoadError with a clear message. Audited the other loader-side
int()/conversions: foundry.py guards every int() with isinstance/isdigit
checks and combatant.py has no other unguarded conversion.
- SpellSpec.components (frozenset of V/S/M/F/DF, JSON key accepting the RAW
string notation "V, S, M/DF" or a token list; slash = alternative; unknown
token is a data error). Default empty = not encoded yet -> no failure.
- Combatant.armor_spell_failure (0-100 percent, authored on the JSON - the
model has no equipment) and arcane_caster (divine casters never incur ASF);
both load directly through load_combatant.
- _cast_spell: after the start-of-casting gates and before delivery, two
conditional d100 rolls (convention mirrors the concealment roll, <=):
deafened + V component spoils the spell on <=20 (SRD cast-a-spell.md);
arcane_caster + S component + armor_spell_failure > 0 fails the spell on
<= the ASF percent (SRD arcane-spells-and-armor.md). The slot stays spent
(mirrors the concentration fizzle). No condition -> no roll: the RNG
stream is bit-identical for every current combat (registry encodes no
components yet - full encoding is a follow-up task).
- Observation: spell summary gains "components" (sorted tuple), combatant
snapshot gains "armor_spell_failure"/"arcane_caster"; README documents
the keys and the two former out-of-scope bullets now describe the modeled
rule with its data-encoding follow-up.
- Data smoke test: lich arcane_caster true / ASF 0, oni arcane_caster false.
- tests/test_spell_failure.py: 21 tests (parsing, thresholds <=20 / <=ASF,
divine/no-ASF/no-component never roll, roll order, slot stays spent,
observation keys). Golden transcripts unchanged.
Adds the PF1e two-axis alignment code (LG/NG/CG/LN/N/CN/LE/NE/CE,
default N) to the Combatant model with a strict validator, derived
is_lawful/is_chaotic/is_good/is_evil properties, exposure in the
observation snapshot, and alignment values for all monsters and PCs
sourced from the bestiary KB and the Foundry sheets.
SRD Surprise: when some but not all combatants are aware of their
opponents, a surprise round precedes round 1. Aware combatants take a
single standard OR move action plus free actions (swift and full-round
are dropped, full_attack collapses to one standard attack, withdraw
survives as the Restricted Withdraw standard); unaware combatants skip
their turn. New Combatant.aware flag (default true, parsed at the JSON
boundary) keeps every existing encounter bit-identical, exposed in the
observation snapshot. Unaware combatants are not flagged flat-footed
(documented simplification).
Ultraworked with [Sisyphus](https://github.com/code-yeongyu/oh-my-openagent)
Co-authored-by: Sisyphus <clio-agent@sisyphuslabs.ai>
Rename monster.py → combatant.py with _KNOWN_FEATS lookup table
that resolves feat name strings to AbilitySpec constants (Power Attack,
Iron Will, Toughness, Weapon Focus, etc.). Unknown feats produce
minimal AbilitySpec (data preserved for future implementation).
Migrate all 8 PC JSONs (data/pcs/) with complete feat/spell lists
extracted from Foundry sheets — including traits, racial abilities,
and all spells. Monsters (goblin, orc) unchanged (no feats/spells).
Update all imports, add backward-compatible aliases (load_monster,
MonsterLoadError), update CLI to use load_combatant.
Gate: 377 tests, ruff clean, basedpyright clean.
ctan