coolguyandClaude Opus 4.7 a899af4d7e Add librarian Stage 1 citation checker with ignore list
scripts/librarian_check_citations.py extracts file:line references from
inline-code spans across docs/**/*.md and verifies each path exists
(and, if cited with a line number, is within range). Skips
docs/archive/ and docs/plans/archive/ which are read-only by policy.

Caught one real drift in docs/research/optimization_sequencing.md: the
note pointed at docs/plans/amp_trainer.md, which had moved into
docs/plans/archive/.

scripts/librarian-ignore.txt holds fnmatch globs for citations that are
intentionally future-tense (planned files described in the plan docs
themselves). Used sparingly so the checker stays useful as a drift
signal.

Updates docs/plans/librarian.md Progress + Next Step. Next concrete
step is a thin scripts/librarian.sh orchestrator over both checkers.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-07 23:22:34 +09:00
2026-05-07 20:41:27 +09:00
2026-05-07 15:42:30 +09:00

coolrl-lost-cities

Focused Lost Cities extraction from the legacy coolrl repository.

The current implementation starts with the classic two-player card game:

  • classic 5-expedition rules by default
  • Python/Cython game engine
  • env wrapper
  • random, passive-discard, and safe-heuristic bots
  • core rule, scoring, mask, env, canonical-state, bot, and GUI smoke tests

Training code, Deep CFR, learned-policy evaluation, GUI, and web client are intentionally outside the first port.

Development

uv run pytest tests/games/classic
uv run lost-cities-classic

For future GUI work, install the optional GUI dependencies:

uv sync --extra gui

Run the classic pygame GUI:

uv run lost-cities-classic-gui --mode pvc --bot safe-heuristic

The GUI uses the in-process Cython game engine.

Basic Usage

from coolrl_lost_cities.games.classic import GameState, build_bot, classic_config

state = GameState.new_game(classic_config(seed=1))
bot = build_bot("random", seed=1)

while not state.terminal:
    state.apply_action(bot.act(state))

print(state.total_score(0), state.total_score(1))

See classic port notes for the current direction.

S
Description
Lost Cities
Readme
7.7 MiB
Languages
Python 73.3%
Cython 21.7%
Julia 4.8%
Shell 0.2%