capsule-wardrobe-architect

Use when the closet is full but "nothing to wear", before a clothes-shopping trip, or when building a travel/capsule wardrobe — cost-per-wear amortization, outfit combinatorics with a compatibility matrix, laundry-cycle sufficiency math, and lifestyle-allocation gap analysis that tells you exactly which 2-3 items to buy and which never to buy again.

Overview

The average adult owns 100+ garments, wears ~20% of them regularly, and still faces "nothing to wear" mornings. The failure isn't taste — it's structure: closets accumulate single items that pair with nothing, while the working core (tops × bottoms that all interchange) stays tiny. A capsule works because of combinatorics: 8 interchangeable tops and 5 bottoms that all pair produce 40 base outfits; 8 mismatched tops and 5 bottoms can produce as few as 8.

This skill is a quantitative wardrobe instrument: it computes cost-per-wear (the only honest price of clothing), counts real outfits through a compatibility matrix rather than naive multiplication, checks the closet against the laundry cycle (enough work shirts to survive until wash day with one in the wash), and compares what you own against the lifestyle allocation your calendar actually shows (work 45%, gym 15%, home 25%, dress-up 5%…) — producing a buy-list of at most 2–3 items and a donate-list of everything below a CPW threshold.

When to Use

• "I have a full closet but nothing to wear" — run the outfit count and gaps audit first
• Before a shopping trip — get the exact buy-list so impulse buys have to beat real items on CPW
• Building a travel capsule or work uniform — right-size the count for trip length × laundry access
• After weight change / new job / new climate — reallocate the closet to the new life percentages
• Decluttering — donate/keep verdicts priced by cost-per-wear, not by "might need someday"

Don't use for: children's clothing (sizing churn dominates — see hand-me-down logic instead), or specialty gear (ski, formalwear) where need is episodic — count those separately.

Quick Start

bash

# What does that $90 sweater actually cost? (worn 9 times, expects 60 lifetime wears)
python3 scripts/capsule.py cpw --price 90 --worn 9 --lifetime 60

# How many REAL outfits does the closet make? (compatibility = fraction of pairs that work)
python3 scripts/capsule.py outfits --tops 14 --bottoms 8 --layers 3 --compatible 0.45

# Do I survive 7 days between laundry with 5 work shirts?
python3 scripts/capsule.py laundry --items 5 --wears-per-item 1 --cycle-days 7 --role work

# What should I actually buy? (closet counts vs how I actually spend my days)
python3 scripts/capsule.py gaps --work 0.45 --casual 0.30 --active 0.15 --dressup 0.05 --home 0.05 \
    --work-items 6 --casual-items 9 --active-items 1 --dressup-items 2 --home-items 8

The Four Instruments

1. Cost-per-wear (the honest price tag)

CPW = price ÷ expected lifetime wears. A $250 coat worn 150×/yr for 5 years = $0.33/wear. A $25 trendy top worn twice = $12.50/wear — 38× more expensive. Rule of thumb: anything with CPW > $3 (frequently-worn categories) or destined for <10 wears is a rental/borrow candidate, not a purchase. The cpw command prices past purchases two ways: realized CPW (price ÷ wears so far — the honest post-mortem) and projected CPW (price ÷ lifetime — the shopping decision number).

2. Outfit combinatorics with compatibility

Naive count tops × bottoms lies: the real number is tops × bottoms × compatible-fraction, plus layer multipliers (each layer that works over most tops adds a distinct look for ~60–80% of combos). Verdict bands: <14 distinct outfits for daily rotation = wardrobe poverty (you repeat weekly and it feels like it); 20–40 = functional core; >60 = diminishing returns — more items add clutter, not looks. The fix is rarely "more clothes": going from 40% to 80% compatibility by replacing 3 odd items can double outfits while shrinking the closet.

3. Laundry-cycle sufficiency

Clothing needs are a queueing problem, not a style problem: items needed = wears per cycle + 1 in the wash + buffer. Work shirts worn once between weekly laundry = 8–9 needed (7 wears + 1 in the wash + 1 spill buffer). Jeans at 3 wears each across a 7-day cycle need only 3. The laundry command computes sufficiency per role and names the exact shortfall — the most common cause of "I'm behind on laundry" is owning 5 of something that mathematically requires 8.

4. Lifestyle-allocation gaps

Sort what you own by role, then compare against the share of waking hours each role actually occupies. A closet that is 40% dress-up while life is 5% dress-up is a mispriced portfolio. The gaps command outputs each role's surplus/deficit in items and a maximum-3-item buy list ranked by (deficit × outfit leverage) — an item that completes many pairs beats an item that pairs with one thing, always.

Common Pitfalls

1. Counting items instead of outfits. 40 items that make 12 outfits lose to 15 items that make 30. Optimize pairs, not pieces.
2. Buying into a gap that's actually a compatibility problem. A new top that pairs with only one bottom adds 1 outfit; a neutral basic can add 5+.
3. Ignoring the laundry cycle — the right number of work shirts is a queueing answer (wears + 1 + buffer), not a style answer.
4. CPW on past purchases used to justify future ones ("the $200 boots were worth it") without checking the realized CPW of the last three "investment" pieces.
5. One-color-pillar closets with zero contrast items — a 100%-neutral capsule produces technically many outfits that all look the same; reserve ~20% statement/contrast pieces that work with ≥70% of the base.
6. Decluttering by KonMari joy alone — keep the boring high-CPW core (plain tees, dark bottoms); joy-based purges evict exactly the interchangeable base and keep the oddball singles.

Verification Checklist

• Cost-per-wear computed for the last 5 purchases (realized vs projected both recorded)
• Real outfit count = tops × bottoms × compatibility + layer contribution — not the naive product
• Laundry sufficiency checked per role (work / active / home) against the real wash-day interval
• Lifestyle allocation table filled from an actual week, not an aspirational one
• Buy list capped at 3 items, each scored by outfit leverage; donate list priced by CPW threshold
• Re-run outfits after changes — target ≥20 distinct daily outfits from the core

Example Session

text

$ python3 scripts/capsule.py outfits --tops 14 --bottoms 8 --layers 3 --compatible 0.45
OUTFIT MATH — 14 tops x 8 bottoms x 3 layers
  base pairs:                112
  compatible (~45%):         ~50 real base outfits
  + layers (70% coverage):   +105 looks  ->  ~155 total combinations
  distinct daily outfits:    ~50 (layers repeat looks, they don't create new ones)
VERDICT: FUNCTIONAL CORE — volume is fine. The closet's problem (if any) is
  allocation or laundry, NOT item count. Do not shop.

$ python3 scripts/capsule.py gaps --work 0.45 --casual 0.30 --active 0.15 --dressup 0.05 --home 0.05 \
    --work-items 6 --casual-items 9 --active-items 1 --dressup-items 2 --home-items 8
LIFESTYLE vs CLOSET (26 daily-rotation items)
  work      45.0% of life   6/26 items (23.1%)  -> DEFICIT +22 pts  ** biggest gap
  active    15.0% of life   1/26 items ( 3.8%)  -> DEFICIT +11 pts
  home       5.0% of life   8/26 items (30.8%)  -> SURPLUS -26 pts  donate candidates
  casual    30.0% of life   9/26 items (34.6%)  -> surplus -5 pts   about right
  dressup    5.0% of life   2/26 items ( 7.7%)  -> about right
BUY LIST (max 3 roles): 6 work item(s); 3 active item(s) — choose
  NEUTRAL basics pairing with >=4 existing pieces (leverage = outfits
  added). DONATE: 7x home; 1x casual duplicates past CPW threshold.