All four arms captured: the number moves from 0/8 to 4/8

32 recorded rollouts, 8 seeds x 4 agents, every one replaying through the Python
engine to a delta of exactly 0.

  arm          solved   economy  consistency    total
  base-off       0/8      0.000        0.122   0.0244
  base-on        4/8      0.469        0.479   0.4865
  cautious       8/8      0.944        1.000   0.9831
  solver         8/8      1.000        0.719   0.9437

Thinking-off solves none of eight. The same model on the same seeds, sampled
with thinking on, solves four. That is the headline, it is ours, and it needed
no training — which is also why the run is labelled an intervention and names
what was done to it, so a sampling change can never read as a training result.

`cautious` is new and it exists to make the reward editor honest. Until now the
page invited you to move a slider and watch the ranking change, and no slider
changed anything, because the solver dominated a model that solved nothing. A
candidate-only player — most informative guess among words that could still win
— takes consistency outright and pays for it in turns. Now:

  only speed matters      solver 0.9859  cautious 0.9606  -> solver
  shipped weights         solver 0.9437  cautious 0.9831  -> cautious
  punish contradictions   solver 0.8312  cautious 0.9972  -> cautious

The ranking really does flip, on recorded data, with one slider. The first
version of this arm picked the alphabetically-first candidate and opened on
'abaci', which made the policy the counterweight exists to reward look like a
straw man.

190 contract checks pass.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_019mt6sHQHEnEYrJZvoMCJSB

public/traces/wordle/cautious-s7.json

@@ -0,0 +1,83 @@
+{
+  "runId": "cautious-s7",
+  "seed": 7,
+  "model": "candidate-only-solver",
+  "capturedAt": "2026-08-28",
+  "rewards": {
+    "solved": 1.0,
+    "economy": 0.75,
+    "consistency": 1.0
+  },
+  "metrics": {
+    "guesses_used": 4.0,
+    "rejected_replies": 0.0,
+    "reference_depth": 3.0,
+    "turns_granted": 6.0,
+    "inconsistent_guesses": 0.0
+  },
+  "truncated": false,
+  "outcome": "solved",
+  "answer": "clews",
+  "turns": [
+    {
+      "reply": "[tares]",
+      "reasoning": null,
+      "call": {
+        "promptTokens": null,
+        "completionTokens": null,
+        "reasoningTokens": null,
+        "durationMs": null,
+        "finishReason": "generated"
+      },
+      "info": {
+        "guess": "tares",
+        "observation": "T A R E S\nX X X Y G\n\nYou have 5 guesses left."
+      }
+    },
+    {
+      "reply": "[sleds]",
+      "reasoning": null,
+      "call": {
+        "promptTokens": null,
+        "completionTokens": null,
+        "reasoningTokens": null,
+        "durationMs": null,
+        "finishReason": "generated"
+      },
+      "info": {
+        "guess": "sleds",
+        "observation": "S L E D S\nX G G X G\n\nYou have 4 guesses left."
+      }
+    },
+    {
+      "reply": "[clefs]",
+      "reasoning": null,
+      "call": {
+        "promptTokens": null,
+        "completionTokens": null,
+        "reasoningTokens": null,
+        "durationMs": null,
+        "finishReason": "generated"
+      },
+      "info": {
+        "guess": "clefs",
+        "observation": "C L E F S\nG G G X G\n\nYou have 3 guesses left."
+      }
+    },
+    {
+      "reply": "[clews]",
+      "reasoning": null,
+      "call": {
+        "promptTokens": null,
+        "completionTokens": null,
+        "reasoningTokens": null,
+        "durationMs": null,
+        "finishReason": "generated"
+      },
+      "info": {
+        "guess": "clews",
+        "observation": "C L E W S\nG G G G G\n\nYou have 2 guesses left."
+      }
+    }
+  ]
+}