c00cfe78c3
Two findings, both from measurement rather than the public guides. 1. The public STS2 meta is not usable as evidence. Deck-size targets disagree by 3x across five sources (12-18 to 25-35), and one tier list names Demon Form, Barricade, Limit Break and Body Slam as STS2 Ironclad cards -- those are Slay the Spire 1 cards, so that page is an STS1 list retitled. Only Offering and Break appear on more than one list. 2. Our own run files are far better evidence, and they contain 1052 labelled decisions. They show the bot is NOT bloating (249 picks from 1087 offers = 23% per card, ~69% per reward), that 81% of runs die in Act 1, and that 43% die to an Act 1 boss with `THE_KIN_BOSS` alone killing 9. The binding constraint is combat defence, not deck composition: those Kin fights ran 5-10 turns and cost 44-80 HP with block cards in hand the whole time.
244 lines
7.9 KiB
Markdown
244 lines
7.9 KiB
Markdown
# 08 — What actually wins (and why the web meta is not usable)
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Status: **current**. Supersedes the assumption in `06-decision-architecture.md`
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that deck composition is the primary lever.
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## Question
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Before tuning decision quality, establish what actually decides a run in STS2:
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deck archetype, deck size ("lean weight"), card rarity, or something else.
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## Finding 1 — the public STS2 "meta" is not usable as evidence
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Searched for deck archetypes, tier lists and Act 1 advice. The sources
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contradict each other badly, and at least one is a copy of a Slay the Spire 1
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list relabelled.
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Deck size target, by source:
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| Source | Deck size target |
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|---|---|
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| metabot.gg | 12–18 |
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| gamestrategyhub | 15–20 |
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| games.gg | ~22 |
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| slashskill | 25–30 |
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| sts2guides | 25–35 |
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That is a 3x range. A real meta does not disagree with itself by 3x.
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Ironclad S-tier, by source:
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| Source | S-tier |
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|---|---|
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| slaythespire2.space | Demon Form, Barricade, Dark Embrace, Limit Break, Body Slam, Whirlwind |
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| spireforge | Barricade, Cruelty, Dark Embrace |
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| stratgg | Offering, Pyre, Battle Trance |
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| metabot.gg | Apotheosis, Secret Weapon, Mad Science, Folly, Tank |
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| nat1gaming | Offering, Break, Feed |
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**`slaythespire2.space` lists Demon Form, Barricade, Limit Break, Body Slam and
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Whirlwind as STS2 Ironclad cards. Those are Slay the Spire 1 cards.** That page
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is an STS1 tier list with the title changed.
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Only two cards — **Offering** and **Break** — appear on more than one list.
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Conclusion: these are AI-generated SEO pages. Do not build a scoring model on
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them. The one idea they agree on is qualitative and obvious ("commit to one
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archetype, keep the deck lean"), which we cannot operationalise without numbers.
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## Finding 2 — our own run history is far better evidence
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37 runs on disk, all reachable and machine-readable:
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```
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~/Library/Application Support/SlayTheSpire2/steam/<id>/modded/profile1/saves/history/*.run
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```
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Each file records `killed_by_encounter`, `win`, the full deck, relics, and
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`map_point_history` — a per-map-point log that includes **every card offered
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with a `was_picked` flag**, plus per-fight `damage_taken`, `potion_used`,
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`rest_site_choices` and `upgraded_cards`.
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That is a labelled dataset of our own drafting and combat outcomes.
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### Outcome distribution
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```
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runs=37 wins=0 max_pts=33
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act1 deaths: 30/37 (81%)
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act2 deaths: 4/37
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act3 deaths: 3/37
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```
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| Killed by | Count |
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|---|---|
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| `THE_KIN_BOSS` | **9** |
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| `VANTOM_BOSS` | 5 |
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| `CEREMONIAL_BEAST_BOSS` | 2 |
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| Act 1 normals/elites | 21 |
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**43% of runs die to an Act 1 boss. `THE_KIN_BOSS` alone kills 9 of 37.** That
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is the single largest lever in the dataset.
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### The bot is not bloating
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```
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total offers=1087 total picks=249 overall pick rate=23%
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rewards=323 rewards where a card was taken=249 -> 77% taken, 23% skipped
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```
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**Descriptive, not a benchmark.** The per-card rate (23%) is mechanically
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diluted by offer size — 280 of 323 rewards offered 3 cards, some offered up to 7
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— so it cannot diagnose skip policy on its own. The metric that can is the share
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of rewards taken (77%) and, below it, cards added per map point. We have no
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reference for what a good skip rate is in STS2, so this says what the bot does,
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not whether it is right.
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The "deck bloat" hypothesis is **not supported**: 23% of rewards were skipped,
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one card was taken per reward at most, and 81% of runs never reach the point
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where deck composition matters.
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### Drafting profile (offers / picks)
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| Card | Seen | Took | Pick rate |
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|---|---|---|---|
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| `PERFECTED_STRIKE` | 17 | 17 | 100% |
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| `EVIL_EYE` | 19 | 12 | 63% |
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| `POMMEL_STRIKE` | 26 | 14 | 54% |
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| `SHRUG_IT_OFF` | 30 | 16 | 53% |
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| `ARMAMENTS` | 39 | 19 | 49% |
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| `TREMBLE` | 45 | **0** | **0%** |
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| `RUPTURE` | 18 | 0 | 0% |
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| `FIGHT_ME` | 17 | 0 | 0% |
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| `SWORD_BOOMERANG` | 16 | 0 | 0% |
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`TREMBLE` is the most-offered card in the game and the bot has never once taken
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it. Worth auditing, but it is not the binding constraint.
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## Finding 3 — the binding constraint is combat defense, not deck building
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Every `THE_KIN_BOSS` fight, from the run files:
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```
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damage taken: [44, 50, 50, 53, 63, 64, 70, 75, 80]
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potions used: [3, 3, 2, 1, 3, 3, 2, 3, 2]
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turns: [6, 9, 10, 6, 6, 10, 9, 7, 5]
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deck size: [17, 18, 19, 19, 20, 20, 21, 22, 23]
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```
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The bot enters at ~74–80 HP and dies. Fights last **5–10 turns** and it takes
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**44–80 damage**, i.e. **~10–13 per turn, almost entirely unblocked**. It spends
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1–3 potions and still loses.
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Every one of those decks contained block cards:
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```
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DEFEND_IRONCLAD 9/9
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BASH 9/9
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STRIKE_IRONCLAD 9/9
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```
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So the cards are there. The bot does not play them.
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### Root cause A — the fallback treats a boss's main attack as "chip damage"
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`facts.py`:
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```python
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THREAT_CHIP = "chip" # <= 15% of max HP
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THREAT_HEAVY = "heavy" # <= 40% of max HP
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HP_HEALTHY = "healthy" # > 60%
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```
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At `max_hp = 80` that gives `CHIP <= 12`, and `HEALTHY` for `hp > 48`.
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`brain.py::_fallback_combat`:
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```python
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must_respect = (
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f.threat in (F.THREAT_HEAVY, F.THREAT_SEVERE, F.THREAT_LETHAL)
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or f.hp_bucket in (F.HP_WOUNDED, F.HP_CRITICAL)
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)
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```
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So at 74/80 HP, any hit of **12 or less is ignored**. Measured, reproduced:
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```
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hp incoming threat hp_bucket fallback play
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74 12 chip healthy Bash (dmg) <- takes the full 12
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74 13 heavy healthy Defend (block)
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60 12 chip healthy Bash (dmg) <- still attacking
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45 12 chip wounded Defend (block) <- too late, 29 HP gone
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```
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The boss's main attack lands exactly on the `CHIP`/`HEAVY` boundary, so the bot
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attacks and eats it. It only starts blocking once HP drops below 48 — after
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donating ~29 HP.
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The model is **myopic**: it asks "is this turn's hit big?" when the correct
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question is "will the total damage over the remaining fight kill me?".
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### Root cause B — `should_defend` is asked and then discarded
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`brain.py::_jev_combat` builds this question:
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```python
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questions["should_defend"] = noul(
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"Given `combat.incoming_threat` and `combat.your_health`, "
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"is preventing damage more valuable than dealing damage this turn?"
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)
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```
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It appears **exactly once in the entire codebase** — at the line where it is
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created. It is never read.
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```
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$ grep -rn 'should_defend' *.py
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brain.py:278: questions["should_defend"] = noul(
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```
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So it costs latency in every combat turn and does nothing.
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### Root cause C — the surviving question is damage-biased
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Defense is therefore delegated entirely to:
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```python
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questions["best_play"] = choice(
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"Which single play best advances winning this fight?", options)
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```
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"Advances winning" biases toward damage, and a `Choice` over 5–8 cards is the
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question shape measured in `02-system-one-jev.md` as **diluting with option
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count**.
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Measured directly against the Kin state (74/80 HP, 12 incoming, turn 6):
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```
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$ python3 -c "... brain._jev_combat(f, jev.JevClient()) ..."
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play_card {'card_index': 4, 'target': 'kin'} | jev chose Bash | conf: 0.42
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-> Bash DAMAGE
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```
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Jev picks **Bash** at confidence **0.42**. That is below the 0.45 gate, so
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`_jev_combat` bails to `_fallback_combat`, which also picks damage. **Both
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paths agree on the wrong answer.**
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## Conclusion
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The bot has no defense policy. In boss fights it attacks until it dies, and the
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data shows exactly that: 5–10 turn fights, 10–13 unblocked damage per turn,
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44–80 damage taken, 9 runs ended by one boss.
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Priority order for the next work:
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1. **Make defense a first-class, code-computed decision.** Not a Jev preference.
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The quantity that matters is total incoming damage over the expected
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remaining fight, not this turn's hit.
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2. **Fix or delete `should_defend`.** A dead question that costs latency is
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worse than no question.
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3. **Only then** revisit deck composition. 81% of runs never reach the point
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where it matters.
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Deck size, rarity and archetype are real concerns in Slay the Spire, but they
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are not what is killing this bot right now.
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