16bff634b5
A to-do app that doesn't believe you — an enforcement layer rather than a
neutral ledger.
Architecture ported from Autoreceptives/Frontend/Receptive: stacked MVVM with
the mandatory 4-file screen pattern, one ParentViewModel owning the loading /
network / error overlays and the handleError decision tree, one AppDataManager
gateway, dio comms carrying the three identity headers, secure storage with
random-suffixed keys, and a single-chokepoint Navigator. Package root and Dart
package name are both Grounded; org is nya.
The enforcement engine, one unit per formula in utils/:
- DebtEngine w(class) x severity(d) x decay(t), sublinear severity so old
misses cannot swamp the score; abandonment 2x with 30-day
decay immunity; late complete retains 30%
- StandingEngine Good -> Warned -> Grounded -> Lockdown, derived not set;
Grounded replaces home with the overdue queue
- CapacityEngine blocks over-scheduling against p50 of historically completed
minutes, with a learned per-category estimation multiplier
- IntegrityEngine session integrity, weekly volume, plyometric contact ceiling
and enforced recovery gaps
- ExcuseAnalyser on-device excuse clustering plus the confrontation copy
- GuardrailEngine distress detection and rationed amnesty
- ToneEngine all enforcement copy, so the tone cap lives in one place
CommitmentEvent is append-only and is the source of truth rather than the
status field, which is what makes honest history and excuse analysis possible.
Goals contain commitments via parentId, and a task can be run from a
full-screen runner that derives elapsed time from wall-clock so screen-off
cannot lose time. Backgrounding pauses the clock and is counted. The runner is
mirrored into an ongoing notification, with alarm-class full-screen intents
reserved for non-negotiables.
Design language, fonts, icon and native splash are in place; Mason bricks are
retargeted to this project and verified end-to-end.
flutter analyze lib/ reports no errors.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Mfu2gQLSFN21YRBcU2NrTt
73 lines
2.1 KiB
Dart
73 lines
2.1 KiB
Dart
/// A recurring excuse plus the pattern the app confronts you with, e.g.
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/// "Too tired has appeared 14 times this month, 11 of them on gym days,
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/// 9 of them after 7pm. Consider moving gym to morning."
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class ExcuseCluster {
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String? id;
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String label;
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int occurrences;
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/// Weekday histogram (1 = Monday) — where this excuse concentrates.
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Map<int, int> byWeekday;
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/// Hour-of-day histogram — when it concentrates.
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Map<int, int> byHour;
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/// The category this excuse most often attaches to.
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String dominantCategory;
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/// The confrontation copy rendered to the user.
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String insight;
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ExcuseCluster({
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this.id,
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this.label = "",
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this.occurrences = 0,
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Map<int, int>? byWeekday,
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Map<int, int>? byHour,
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this.dominantCategory = "",
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this.insight = "",
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}) : byWeekday = byWeekday ?? <int, int>{},
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byHour = byHour ?? <int, int>{};
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factory ExcuseCluster.fromJson(Map<String, dynamic> json) {
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final Map<int, int> weekdays = <int, int>{};
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if (json['byWeekday'] != null) {
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(json['byWeekday'] as Map<String, dynamic>).forEach((key, value) {
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weekdays[int.tryParse(key) ?? 1] = value ?? 0;
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});
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}
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final Map<int, int> hours = <int, int>{};
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if (json['byHour'] != null) {
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(json['byHour'] as Map<String, dynamic>).forEach((key, value) {
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hours[int.tryParse(key) ?? 0] = value ?? 0;
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});
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}
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return ExcuseCluster(
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id: json['id'],
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label: json['label'] ?? "",
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occurrences: json['occurrences'] ?? 0,
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byWeekday: weekdays,
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byHour: hours,
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dominantCategory: json['dominantCategory'] ?? "",
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insight: json['insight'] ?? "",
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);
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}
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Map<String, dynamic> toJson() {
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final Map<String, dynamic> data = <String, dynamic>{};
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data['id'] = id;
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data['label'] = label;
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data['occurrences'] = occurrences;
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data['byWeekday'] =
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byWeekday.map((key, value) => MapEntry(key.toString(), value));
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data['byHour'] = byHour.map((key, value) => MapEntry(key.toString(), value));
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data['dominantCategory'] = dominantCategory;
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data['insight'] = insight;
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return data;
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}
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}
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