Phase "habillage" of the post-0.1.0 plan. Rendering was reviewed on real
screenshots (new tools/screenshot.gd, `make screenshot`), which also
caught and fixed map markers overlapping and truncated titles.
- Global Godot theme (Atkinson Hyperlegible font, cream/green/gold
palette, raised buttons, rounded cards, thick keyboard focus).
- Original vector art: forest/marsh backdrops, Plume the owl, stars,
exercise-type icons, correct/try-again icons, 10 collection items.
- Redesigned world map (markers as cards with icon, title and stars,
responsive layout), profile screens, mission intro, exercise host,
rule/feedback panels, reward screen and collection grid.
- Motion helper (pop-in, fade) honouring an animations setting.
- Settings: animations flag; base window 1152x648 with canvas_items.
Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
World map gets a "Changer de profil" button (saves first). During a
mission, a header button asks for confirmation then leaves without
stars or items; attempts already made stay recorded and are saved.
Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
Phase "score et récompenses" of the post-0.1.0 plan (user feedback:
wants a more game-like experience with scoring and rewards).
- MissionScoring: 1-3 stars from how each exercise was solved (never
speed; a finished mission always gives at least one star).
- Save schema v2: mission_results (best/last stars, completions) with a
v1->v2 migration that keeps existing stars and items.
- Total only grows by the improvement over a mission's best score.
- Data-driven collection (data/rewards, reward_item schema, validated
incl. mission cross-check) unlocked by RewardRules.
- Reward screen, collection screen, stars on the world map.
- Version 0.2.0.
Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
Same directives as the CE1 chapter: 4 rules with a substitution test
each, 8 multiple-choice + 4 sentence corrections + 3 dictées per rule
(draft), 3 missions per rule, Piper audio for the 12 dictées.
21 missions don't fit on one map, so the world map now shows the
missions of the profile's school level (derived from the rule's level,
no data-format change), with a button letting a CE2 profile revisit the
CE1 map. Mission-position guard test now checks each level separately.
Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
Manual test: "La clairière" and "La cabane" overlapped on screen.
Their fractional positions (0.8,0.65) and (0.92,0.78) were too close
given the marker size at the project's default window size — exactly
the risk flagged but unverified in the previous commit.
Repositioned all 9 missions (not just the new ones) onto a regular
3x3 grid with 0.35 spacing, well clear of marker dimensions at the
default resolution. Added a headless regression test
(tests/data/test_mission_positions.gd) that fails if any two
missions are closer than a 0.3 fractional gap on both axes — a
data-level guard, not a substitute for visually checking actual
on-screen layout.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Extends explicitly beyond the §15 prototype scope (3 missions, one
rule) that prompt-lancement.md says not to exceed without flagging
it — confirmed with the user before implementing (decisions.md,
point 25).
Adds the two remaining CE1 rules for the "accords dans le groupe
nominal" chapter listed in prompt-lancement.md, each with the same
minimum content volume already established for regle_accord_adjectif
(8 multiple-choice, 4 sentence corrections, 3 dictées across the 3
difficulty levels) and 3 missions (one per exercise type, matching
the existing pattern), bringing the map to 9 locations.
world_map.gd is purely data-driven already, so no code change was
needed to support more locations — only its stale "trois lieux"
header comment, corrected. Dictation audio generated with the Piper
voice (make generate-dictation-audio).
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Follow-up to the previous commit: testing further showed a missing
initial capital also fails validation, which raised the real
question (CLAUDE.md: ask rather than decide alone on an ambiguous
pedagogical point) — is sentence-initial capitalization and final
punctuation something the audio should convey, or a general writing
convention the child applies regardless of what they hear?
Decided: a general convention, like in a real classroom dictée. So
both stay required, and the terminal-punctuation tolerance added in
the previous commit is reverted (DictationAnalyzer back to comparing
the text as-is).
Since the audio still can't vocalize either rule, the child needs to
be told some other way: added a permanent reminder label to the
dictation scene ("N'oublie pas : une majuscule au début de la phrase
et un point à la fin !"), sourced from data/localization/fr.json.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Manual test: the Piper voice (previous commit) is now intelligible,
but typing exactly what's heard ("Les petits chats dorment", no
period) was rejected. The provisional audio never vocalizes
punctuation, so nothing tells the child to add it — penalizing its
absence punishes information they were never given.
DictationAnalyzer now strips terminal punctuation (. ! ? …) from both
sides before comparing, in the exact-match/variant check and before
word alignment, without touching punctuation elsewhere in the
sentence. A real error on the last word is still caught (added test).
A scene-level test reproducing the exact reported interaction
(tests/exercises/test_exercise_host_dictation.gd) failed before the
fix and passes after.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Manual testing confirmed the "La clairière de l'écho" dictée mission
was unplayable: no audio file existed yet (decisions.md point 8), so
there was nothing to listen to before transcribing the sentence.
Adds tools/generate_dictation_audio.py (offline eSpeak NG synthesis +
ffmpeg encoding to Ogg Vorbis, exposed as `make
generate-dictation-audio`) and uses it to generate
ce1_accord_adjectif_dictee_01.ogg. A new headless test
(tests/data/test_dictation_audio.gd) guards against future dictées
being added without regenerating their audio.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Manual report: after "Bravo!", clicking Continue seemed to do
nothing. An automated test proved the mission does advance (a new
exercise instance loads, completed_count increments) -- but
mission_02_pont_des_phrases has exactly one sentence_correction
exercise in the data right now, so the "next" exercise is the
identical sentence the child just solved. Nothing was broken; there
was just no visible signal that progress happened.
Added a persistent progress label at the top of exercise_host,
updated on every exercise load. Doesn't address the underlying
content-volume gap (still tracked in decisions.md point 14), but
makes the repetition legible instead of indistinguishable from a
stall.
Rebuilt both exports.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
AnswerValidator.validate_sentence_correction compared the typed
correction to the expected word with raw string equality, with none
of the tolerance already built for dictations: no case folding, no
typographic-apostrophe or whitespace normalization, no decomposed-
accent handling. Tapping "petit" and typing "petits" could fail for
reasons having nothing to do with the grammar point being tested
(e.g. a stray capital from autocapitalization), which violates the
"an ambiguous answer is never auto-marked wrong" invariant.
Found this while chasing a manual bug report: an automated test
reproducing the user's exact click sequence (tap once, type, submit)
did NOT reproduce the failure, which actually pointed at the real
gap -- the logic worked for byte-identical input, but had zero
tolerance for anything else. Now reuses TextNormalizer (built for
dictation analysis) before comparing, case-insensitively, while still
showing the child's raw typed text in the feedback. Three new tests
cover case, incidental whitespace, and decomposed accents.
Rebuilt both exports so the shipped binaries include the fix.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Investigating a manual bug report ("typing petits as the correction
for petit doesn't validate"): both a direct test of
sentence_correction.tscn and a full exercise_host integration test
(mission_02_pont_des_phrases) tap the faulty token, type its exact
expected correction, and submit -- both pass, confirming the
validator and the scene wiring correctly accept "petits" when the
word is tapped once and the correction is typed before pressing
Valider.
Caught along the way: a first draft of the direct-scene test used a
lambda connected to answer_submitted to capture its parameters into
outer local variables -- GDScript closures capture locals by value
at creation time, so reassigning them inside the lambda never
reaches the outer scope. Switched to GUT's
assert_signal_emitted_with_parameters, the supported way to inspect
signal arguments in a test.
No fix applied yet: these tests confirm the intended interaction
works, but don't rule out a real fragility noticed while reading the
code -- toggling a token off deletes its LineEdit (and whatever was
typed in it) immediately, so an accidental second tap on the same
word silently discards the correction. Needs the user's exact click
sequence to confirm before changing behavior.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Wires every autoload up to a real UI: boot -> profile select/create
-> world map (three mission markers, positioned from data, not
hardcoded pixels) -> mission intro (narrative from data/missions/,
a new data type with its own schema) -> rule panel -> exercise host
-> one of the three exercise type scenes -> feedback panel -> reward
screen -> back to the map.
exercise_host is the only piece with real orchestration logic: picks
exercises via ExerciseEngine (now fully implemented, validating at
load like make validate-data does), validates answers through the
pure AnswerValidator/DictationAnalyzer, escalates aid over 3 attempts
via AttemptFlow, feeds DifficultyManager so adaptive difficulty is
actually wired in rather than dead code, and records every attempt
through ProgressManager. Every exercise-type scene (multiple_choice,
sentence_correction, dictation) only emits its answer by signal, per
the architecture invariant.
All child-facing text now comes from data/localization/fr.json via
UIText, not hardcoded in scripts or scenes. Getting that right
required extending SchemaValidator to support "additionalProperties"
as a schema (dynamic keys), which also closed a real gap: save.skills
was previously unvalidated against SkillState's actual shape.
16 new headless tests, including two integration tests that instance
exercise_host.tscn directly and drive it by emitting child-scene
signals, stopping short of the final scene transition (which would
tear down the test runner's own tree). Everything that needs a
screen -- layout at different sizes, touch, virtual keyboard, actual
audio playback (no .ogg files exist yet) -- is listed in the new
docs/testing/manual-checklist.md instead of claimed as verified.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
scripts/profiles/: SaveIO handles real file I/O in user://saves (one
file per profile_id, atomic write via temp-file-then-rename, backup
copy before each overwrite, corrupted-main falls back to backup,
schema-invalid content is rejected like corruption). SaveMigration
and SaveFactory are pure; SaveMigration refuses a schema_version it
doesn't recognize (older or newer) rather than guessing. ProgressUpdates
is pure and wires ReviewScheduler/DifficultyManager onto a save's
skills dict, including per-session overdue-review marking.
The three autoloads (SaveManager, ProfileManager, ProgressManager)
stay thin: in-memory current-profile state and orchestration only,
no logic of their own, so the actual behavior lives in the tested
pure/file-IO modules above rather than in untestable glue.
26 new headless tests, including the failure modes called out in the
launch prompt: a truncated .tmp file never corrupts the readable
save, a corrupted main file falls back to its backup, two profiles
never mix (down through the real autoload layer, not just SaveIO),
and an unknown future schema_version is rejected outright.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
scripts/correction/: AnswerValidator (multiple choice, sentence
correction via tap-the-faulty-word + retype) and DictationAnalyzer
build the CorrectionResult structure from cahier des charges §6.
Dictation analysis aligns words with WordAligner (Wagner-Fischer edit
distance) before any character comparison, so an omitted or added
word doesn't cascade into false errors on every following word.
TextNormalizer handles non-breaking spaces, typographic apostrophes,
and decomposed-vs-composed French accented characters via an
explicit table (GDScript has no built-in NFC/NFD normalization).
Error classification follows the data annotations only (rule_id
present -> grammatical, absent -> unclassified), never a runtime
linguistic guess.
scripts/pedagogy/: DifficultyManager (per-skill difficulty from
recent results), AttemptFlow (3-attempt graduated aid: hint, then
explanation, then reveal, matching exercise-lifecycle.md's second
gap), and ReviewScheduler (the five mastery states from §9, with
session-counted spaced review intervals [1, 3, 6, 12] rather than
wall-clock dates, since a family device's clock isn't trustworthy).
All of it is pure: no scene tree, no clock or RNG read directly,
every effectful input (session number, attempt outcome) is a
parameter. 65 headless tests across both layers, including the
word-omission-doesn't-cascade regression and the full
decouverte -> acquise -> a_reviser -> acquise path.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Introduces a generic JSON-Schema-subset validator in GDScript
(scripts/data/schema_validator.gd) used both by `make validate-data`
and, later, by ExerciseEngine at load time, plus semantic_checks.gd
for cross-field constraints a schema can't express (answer index
bounds, at least one faulty token in sentence correction, word count
matching between a dictation's target_text and its annotations).
Schemas cover rule, exercise (dispatched per type: multiple_choice,
sentence_correction), dictation, curriculum, and save (save.schema.json
is not yet wired into validate-data; saves live in user://, handled
at the Profiles/Saves step).
First draft content for the CE1 "accord_adjectif" rule (one rule, two
multiple-choice exercises, one sentence correction, one dictation,
one curriculum entry) exercises the full pipeline end to end and
seeds docs/review/content-review.md, regenerated by the new
tools/generate_content_review.py (`make content-review`).
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Pins Godot 4.6.3-stable and GUT 9.6.0 (9.6.1+ reference
AccessibilityServer, unavailable in 4.6.3) via tools/setup.sh. Wires
make check (gdlint + gdformat config for 4-space indent, headless
GUT run, and a JSON well-formedness check ahead of real schema
validation). Seven autoload stubs match the architecture in the
cahier des charges; real logic lands with the following steps.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Denis Defolie