Files

T

karti-ai a56f097f28 wordle-five: the engine, the reward, the solver and the probe that checks them

The Python is the source of truth; src/demos/wordle/engine.ts will be a port of
it, and CI gates the two against a SHA-256 over all 21.2M (guess, answer)
pattern pairs rather than a hand-picked vector file — a vector file only ever
catches the cases somebody thought of.

The reward is three weighted components, and the third one is the reason this
demo is worth building. `solved` and `economy` pull toward winning. `consistency`
pulls against them, because a player maximising information deliberately guesses
words that cannot win — a word that splits the remaining candidates evenly
teaches more than a word that might happen to be right. That is good play, and
it costs consistency.

The probe ladder proves the tension is real rather than asserted:

  inaction        0.0000   crude       0.0111   plausible  0.1224
  candidate_only  0.8925   exhaustive  0.9031   oracle     0.9458

The two good policies are 0.05 apart and neither dominates — the entropy oracle
takes 1.00 economy and 0.73 consistency, the candidate-only player takes 0.75
and 1.00. Which one wins is a decision about what you want, which is the whole
argument the site exists to make. probe.py fails CI if either starts dominating.

Two traps found by building it. `consistency` is scored over turns SPENT, not
guesses accepted: counting only legal guesses hands a free 1.0 to a policy that
plays one word and then jams the parser five times — one guess, no
contradictions, perfect score. And `economy`'s denominator is the depth the
SHIPPED solver reaches, not a depth-optimal search: entropy-greedy is not
depth-optimal, so grading it against an exact optimum would make the oracle
rung fail its own assertion on some seeds.

The word lists are built from Wordnik (MIT) intersected with SCOWL, never from
the original game's 2,315 answers. 4,603 answers makes this materially harder
than the original, so the published SALET/3.4212 results are cited as belonging
to that list and our own reference player's TARES/3.72 is measured here.

verifiers is an optional extra. The engine, reward, solver and probe all run —
and gate — without an RL stack resolvable.

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

2026-08-28 15:39:03 -07:00

2.4 KiB

Raw Blame History

Where these words came from

Both lists are built by build_words.py from the two source files committed beside it. Nothing here is copied from the original game.

Guesses — `guesses.json`, 11,846 words

From wordnik/wordlist, snapshot wordlist-20210729.txt, MIT licensed, filtered to five-letter lowercase ASCII. Wordnik publishes this list for word-game developers, which is exactly what it is being used for.

Answers — `answers.json`, 4,603 words

The intersection of the guess list with SCOWL's common-American tier (wamerican 2020.12.07, as shipped in /usr/share/dict/american-english), minus a short hand-curated block list.

The intersection is the point. A word is a possible answer if it is a real headword (Wordnik) and common enough that a non-specialist has plausibly met it (SCOWL). That rule is stated, reproducible, and ours — as opposed to copying somebody else's editorial selection of which words are fair.

SCOWL is distributed under a permissive licence requiring attribution, which NOTICE carries.

What we deliberately did not use

The original game's 2,315-word answer list. It is the product of a deliberate human curation pass, which is the strongest selection-originality argument of any list in this space and has never been litigated. We do not need it, so we do not ship it.

We verified separately that the Wordnik list contains all 2,315 of those words — that is a statement about Wordnik's coverage, not a reason to redistribute the selection.

Consequences worth stating plainly, since they affect every number on the site:

Our answer pool is 4,603, roughly twice the original's. This game is harder than the original, and our measured solver averages are not comparable to published figures for it.
The famous results — SALET as the optimal opener, a 3.4212-guess mean, a proven worst case of five — are proven for the original list. They are cited on the site as exactly that, never as our own ceiling. Our own reference player opens TARES and averages 3.72, and that number is computed by solver.optimal_depth_report() rather than quoted.

Rebuilding

uv run python envs/wordle_five/words/build_words.py

Deterministic and offline. The output must be byte-identical; if it is not, CONFORMANCE.txt changes too and the TypeScript port has to be re-verified.

2.4 KiB Raw Blame History