Ladder Tournament
A ladder is a ranked list of opponents, weakest first. One model (the "climber") plays them one rung at a time and keeps going until it fails to advance. Its score is how high it climbs.
Two commands
Build the ladder once — ranks the human bots by round-robin:
uv run codeclash ladder make configs/ladder/make_battlesnake.yaml
Then send a model up it:
uv run codeclash ladder run configs/ladder/battlesnake__opus_4_8.yaml
Resume an interrupted climb from its log dir (needs push: True):
uv run codeclash ladder run configs/ladder/battlesnake__opus_4_8.yaml -r logs/<user>/LadderTournament...
Options: -c/--cleanup, -o/--output-dir, -s/--suffix, -k/--keep-containers, -r/--resume.
Minimal run config
tournament:
rounds: 5
ladder_rules: !include ladder/ladder_rules.yaml
game:
name: RobotRumble
sims_per_round: 250
player:
agent: mini
name: claude-sonnet-4-5
branch_init: human/anton/anton3000
config:
agent: !include mini/default.yaml
model:
model_name: anthropic/claude-sonnet-4-5-20250929
push: True
prompts: !include ladder/ladder_prompt.yaml
ladder: !include ladder/rungs/robotrumble.yaml
ladder is the ranked opponent list; player is the climber.
Advancement settings (ladder_rules)
These live in configs/ladder/ladder_rules.yaml and decide what it takes to clear a rung.
min_round_wins (required)
How many rounds the climber must win to move up a rung.
Round 0, before any edits, doesn't count.
win_last_k (required)
Also require winning the last k rounds — 1 means just the final round.
Set to 0 to turn this off.
early_clinch (optional)
Stop a rung early the moment the climber has already won min_round_wins rounds.
Saves time, and the outcome is identical to playing every round.
Only allowed when win_last_k is 0.
fast_forward (optional)
Skip a rung entirely if the climber already crushes it before making any edits.
It plays only round 0; if the climber wins at least min_sim_win_rate of the sims, the rung clears.
Copy-paste examples
Win 2+ of n rounds:
min_round_wins: 2
win_last_k: 0
Win 2+ rounds, and the final round must be one of them:
min_round_wins: 2
win_last_k: 1
Fastest eval:
min_round_wins: 2
win_last_k: 0
early_clinch: true
fast_forward:
enabled: true
min_sim_win_rate: 0.9
- Win 2+ of
nrounds early_clinch: If the model wins 2 rounds before playing alln, skip remaining roundsfast_forward: If the model's current solution beats the next opponent, skip playing that opponent all together.
