G2.5-FL repeatedly initiates TCs after depleting money through overbidding

Entities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.

• G2.5-FL overbid rate=1.20%, highest among all agentsfinding0.791
  highest overbid frequency observed
• G2.5-FL bid aggressiveness 2.07 early and 2.08 late (no adaptation)finding0.789
  Failure to adapt bidding to game phase.
• G2.5-FL initiates a trade challenge for a goose with zero money cards, offering 0-value blufffinding0.776
  In one trace, G2.5-FL depleted money through overbidding and launched a TC with no resources, failing to condition action on resource state.
• G3-F conditions TC offers on opponent wealth and game context, e.g., 0-value bluffs against bankrupt opponentsfinding0.772
  sophisticated bluff calibration
• Overbid frequency, self-bidding rate, bankrupt-initiation patterns, and context-dependent offer calibration are failure modes invisible to both static evaluations and aggregate rankings like Eloclaim0.747
  key claim about the benchmark's unique diagnostic value
• G2.5-FL self-bid rate=78.5%finding0.730
  highest self-bid rate among all agents
• G2.5-FL cost per quartet 1,193 coinsfinding0.728
  Much higher cost per quartet due to waste.
• Two heuristic code agents outperform most tested LLMs, and behavioural traces surface recurring LLM failure modes including overbidding, self-bidding, bankrupt TC initiation, and weak opponent-state adaptation.quote0.725
  Abstract sentence summarising performance and failures.