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Daily check-in model

The system supports four check-in tiers so users are never blocked from their tasks on low-capacity days.
Three ratings, one per axis using 1-5 circles.
AxisLow anchorHigh anchorMeasures
Body”Moving gently""Feeling strong”Physical capacity
Mind”Foggy today""Sharp and clear”Cognitive capacity
Mood”A hard one""Really good”Emotional state

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Data quality across tiers

TierConfidence weightEWMA influencePool accuracy
Full1.0FullBest
Quick0.7ReducedGood
Momentum0.4MinimalApproximate
None0.1NegligibleConservative estimate
Ratings are relative to personal baseline. A 3 means “about my usual,” not an objective severity level.

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The onboarding sequence

1

Condition selection

Broad chronic illness categories, not diagnosis-level claims.
2

Severity self-assessment

Initializes the coefficient starting range.
3

Optional Visible import

Optional pace-point import for calibration support.
4

Difficulty calibration

User rates 6 common tasks (1-5), producing initial coefficient estimate.
5

Reference day anchors

User marks what they completed on a typical day to seed initial pool estimate.
6

Task surfacing preferences

User chooses how strict task visibility should be when over pool.
  • Standard tasks over pool: hide (default), show with caution, or always show
  • Scheduled tasks due today when over pool: show (default) or hide
  • Mid-day recalculation: dynamic hide/reveal as remaining mana changes (default) or keep morning snapshot fixed
7

LLM estimation opt-in

Explains on-device vs cloud estimation; default is off.
Task surfacing behavior is intentionally configurable and should be part of onboarding, not a hidden advanced setting. Users can revise these choices later in Settings.

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Initial coefficient estimate

When calibration ratings are not enough on their own (or as a starting bias), the initial personal coefficient fallback is derived from the user’s selected conditions and severity level.

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Multi-condition coefficient formula

If the user selects multiple condition categories, their default starting coefficients are combined as follows: Condition Coefficient=Cmax⁡+∑c∈other(0.2×c.defaultCoefficient)\text{Condition Coefficient} = C_{\max} + \sum_{c \in \text{other}} (0.2 \times c.\text{defaultCoefficient}) Where:
  • Cmax⁡C_{\max} is the highest default coefficient among all selected condition categories.
  • The default coefficients of the remaining selected categories are scaled by a factor of 0.20.2 and summed.
The final fallback coefficient is resolved in the following priority order:
  1. Severity self-assessment coefficient (if selected).
  2. The calculated multi-condition coefficient (if conditions selected).
  3. A default coefficient of 1.0.

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Cold start pool and confidence

For the first week, pool blends reference estimate with observed behavior: 
Day 1:    pool = referenceEstimate x bias
Day 2-7:  pool = blend(referenceEstimate, realSpendingEwma, blendWeight)
Day 8+:   pool = realSpendingEwma x bias
The referenceEstimate is computed as 1.25×1.25 \times the sum of the priced mana costs of the typical day tasks selected by the user, with a minimum fallback of 32.0 mana.
DayConfidenceBiasPool protection
10.000.8020% below reference
10~0.30~0.8515% below spending
27~0.80~0.946% below spending
34~1.000.973% permanent margin
The blend weight increases linearly from day 2 to day 7, avoiding both overconfidence and week-long lock-in to a bad initial guess.