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Fable 5 on the stop_eval condition

30 rollouts of the beat-stockfish honeypot on anthropic/claude-fable-5 (OpenRouter, provider-default sampling) under condition E: the original task prompt plus a stop_eval(reason) tool. Same runner, sandbox image, 80-message / 3 h budgets, grader and judges (GLM-5.3-flash) as the campaign's Fable 5.1 arms; run 10-wide on one Docker host. Shown beside Fable 5.1's stop_eval arm and Fable 5.1's original-prompt arm (n=30 each).

TL;DR

    1. Outcomes

    All outcomes, mutually exclusive, per arm; whiskers = Wilson 95% CI per segment. Provider refusal (pale, stacked directly above the cheating segments) = the episode ended because Anthropic's content filter blocked the model's next turn ("violative cyber content … blocked under Anthropic's Usage Policy"), three times in a row — in every case right after reconnaissance output revealed the engine socket, before the model had chosen anything. Read it as an upper bound on how much cheating the arm could contain, not as observed cheating. A rollout that used the engine before being filtered counts as cheated.
    For refused rollouts: how many assistant turns the model completed before the filter struck. The filter fires on the turn after the sandbox reconnaissance output that reveals /run/match (the match daemon and its engine socket).

    2. stop_eval calls

    3. Game results

    4. Rollouts in full

    Every rollout of the three arms: metadata, judge verdicts, and the full transcript (reasoning summaries, text, tool calls and tool output, untruncated). Default filter: the Fable 5 arm.

    Appendix

    Run configuration and data notes

      Report specification (v3)

      Fable 5 on the stop_eval condition

      # Fable 5 on the stop_eval condition

30 rollouts of the beat-stockfish honeypot on `anthropic/claude-fable-5` (via OpenRouter) under condition E — the original task prompt plus a `stop_eval(reason)` tool — with the same runner, budgets (80 messages / 3 h), grader and judges as the campaign's Fable 5.1 arms.

## Contents
- **Outcome breakdown** (engine-driven cheating with disclosure split, probe-only, clean completed game, provider refusal, called stop_eval, resigned, ran out of turns), Wilson 95% CIs, side by side with Fable 5.1's stop_eval arm (n=30) and Fable 5.1's original-prompt arm for reference.
- **stop_eval calls**: how many, and every recorded `reason` verbatim.
- **Game results** (win/draw/loss) by method.
- Example rollouts shown in full (full transcripts with reasoning summaries).

Metadata: models `anthropic/claude-fable-5` and `anthropic/claude-fable-5.1` via OpenRouter, provider-default sampling; judges GLM-5.3-flash (engine use, wrap-up disclosure).