The encounter-balance schema was the only AI schema with a numeric field.
LLMs routinely emit numbers as JSON strings ("count": "2"), which z.number()
rejects, failing the whole safeParse and falling back to deterministic with a
"parse" error. The all-string NPC/session/quest schemas never hit this.
- Coerce monster counts (z.coerce.number) and widen the upper bound 8->12 so a
string or slightly over-eager count is accepted, not rejected. min(1) stays.
- Tell the model in the prompt that count is a plain integer and reasoning /
targetDifficulty are required.
- Surface the real failure message in the advisor instead of the opaque kind.
- Add a regression test that string counts coerce to numbers.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
- Player view: a Quest log now syncs to players (snapshot += quests; broadcaster
passes campaign quests; PlayerBoards renders titles + objective checkboxes).
- AI (DeepSeek etc.): robust JSON extraction — strip code fences anywhere + a
brace-balanced scanner that ignores prose/braces in strings. Fixes "AI unavailable
(parse)" with OpenAI-compatible providers. +4 tests.
- Encounter advisor: now bidirectional — for an over-tuned (too-hard) fight it
suggests REMOVING/swapping monsters instead of only ever adding. +3 tests.
- Character share: works on iPad — native share sheet → clipboard → a copyable
link modal fallback (was a silently-failing clipboard write).
230 unit + 34 e2e + 2 realtime green.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Instead of proposing a fresh alternative encounter, the non-AI path now:
- adds MORE of the creatures already present ('Add 2 more Goblin'), computing the
exact count needed and accounting for the 5e encounter multiplier, or
- adds a thematically related stronger creature from the bestiary (shared name
token, level/CR-appropriate) when that reaches the target with fewer bodies.
Only builds a fresh group when the encounter is empty. Apply clones the existing
combatant (works for homebrew/custom too) or pulls from the pool.
Existing creatures are also offered to the AI as candidates so it can likewise
say 'add another goblin'.
New suggestReinforcements() + baseName() in encounter.ts with unit tests.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
- src/lib/assistant/prompts.ts: balanceSuggestionSchema + buildBalancePrompt
(system message leads with the grounding constraint; restricts choices to the
provided compendium candidates).
- useEncounterAdvisor hook: builds context → picks system-correct candidates →
asks the LLM (when configured) for a structured pick, validates + filters names
to the candidate set, else falls back to the deterministic buildSuggestedEncounter.
Apply adds the creatures transactionally via encountersRepo.mutate.
- EncounterTipCard in the combat tracker: leads with the detected difficulty
tendency (or the current difficulty), offers a one-click grounded suggestion
(AI or deterministic) with propose→confirm Apply.
prompts unit tests + e2e for both the deterministic apply flow and the AI path
(stubbed provider); the AI test also confirms candidate-grounding (only
shortlisted creatures survive).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
NilsBriggen