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declutter-pilot

通过本地 Python CLI 记录物品体积与决策难度,按体积/难度排序生成20分钟分拣计划,统计垃圾袋、箱与车容量,并提供决策规则及出售、捐赠、丢弃清单。状态保存在单个本地 JSON 文件。

voronindenis5
voronindenis5
热度 7.65
最近更新 2026-09-27 23:28:03
分类:生活依赖:代码执行 / 读写文件应用场景:任务管理 / 工作流 / 个人理财

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add declutter-pilot
Metadata
name
declutter-pilot
description
Use when your home/office/garage has accumulated more stuff than it can hold and every past cleanup attempt stalled after 20 minutes. Physics-based decluttering: item registry with volume estimates, container/trash bag math (how many bags/bins this will actually fill), a fill-first greedy packing order that front-loads visible wins (the first bag out is 80% of the psychological battle), a 20-minute sortie planner with a room+category target list so sessions never stall at 'where do I start', keep/toss decision rules with sunk-cost counters (what the indecision itself costs in money and space), and a donation/receipt/sell batch manifest. Fighting the two real enemies: decision fatigue and the invisible cost of storing junk you'll never use.
version
1.0.0
author
Denis Voronin
license
MIT
tags
["decluttering","minimalism","moving","garage","basement","storage","organization","cleaning"]

Declutter Pilot — Physics-Based Decluttering Planner

Overview

Decluttering fails the same way every time: not from lack of will, but from decision fatigue. Each object demands a micro-decision ("might need it someday", "was expensive", "a gift"), and after 20–30 decisions the brain refuses to make more. The pile stays half-sorted, now worse than before because it's been touched and abandoned.

Meanwhile every store decision has a real carrying cost: a typical cluttered home stores $2,000–6,000 of never-used items at $10–40/mo per m² of storage value, and moving companies charge by volume — decluttering before a move literally saves hundreds in truck space.

This skill inverts the problem: do the physics first, decide second.

  1. Volume accounting — items logged with volume estimates; the tool computes how many trash bags / boxes / car-loads the declutter will actually produce. Seeing "23 bags, 4 donation boxes, 1 trailer run" turns a vague dread into a bounded project.
  2. Fill-first greedy order — ranks items by volume ÷ decision-difficulty. The first sortie should remove the most cubic meters with the fewest agonizing decisions. Visible win in 20 minutes = the project survives.
  3. Sortie planner — each session is a 20-minute run with a named room, category, container count, and exit condition. Never "clean the garage"; always "garage / sports gear / fill 2 bags".
  4. Decision rules — the standard tests (12-month rule, replacement-cost rule, sunk-cost counter) applied consistently, plus the "sunk cost of indecision": what keeping-it costs per year in space and attention.
  5. Disposition manifest — sell / donate / recycle / trash batches with donation value estimates, sell-price suggestions (rule of thirds), and a printable drop-off manifest.

One local declutter.json; no cloud, no account.

When to Use

  • Chronic clutter: garage/basement/attic/closets at or past capacity
  • Pre-move purge (volume = money: fewer boxes, smaller truck)
  • Post-breakup / post-bereavement clearing where emotional load makes decisions hard
  • Seasonal resets (spring cleaning that actually finishes)
  • Helping someone else declutter (estate light, hoarding-adjacent — gentle mode)
  • Don't use for: actual hoarding disorder (a clinical situation needing professional support — this tool can help structure work alongside that, never instead of it), or digital decluttering (different physics entirely).

How It Works

  1. item add "Old monitor" --room office --volume 30 --difficulty 2 --value 0 --decision toss — volume in liters, difficulty 1 (easy toss) to 5 (emotional heirloom).
  2. plan — greedy order: biggest volume-per-difficulty first; prints sortie list: which items, how many bags, est. minutes.
  3. sortie start / done — runs the 20-minute session; done marks items out, logs bags filled, shows cumulative stats and remaining volume.
  4. bags — container math: liters → 60L trash bags / 60L boxes / car-loads.
  5. decide "Old monitor" — runs the decision rules and prints the verdict + sunk-cost-of-keeping math.
  6. manifest — disposition batches with donation value, sell prices (rule-of-thirds), drop-off manifest.

Commands

# Log items (volume liters, difficulty 1-5)
python3 scripts/declutter.py item add "Broken desk chair" --room office --volume 80 --difficulty 1 --decision toss
python3 scripts/declutter.py item add "Jeans size 32" --room bedroom --volume 4 --difficulty 2 --decision donate
python3 scripts/declutter.py item add "University textbooks" --room office --volume 45 --difficulty 3 --decision sell --value 60

# The plan: biggest-bang-first sortie order
python3 scripts/declutter.py plan
# → SORTIE 1: office / furniture — 2 items, 160L ≈ 3 bags, ~15 min, easy decisions

# Run a session
python3 scripts/declutter.py sortie start
python3 scripts/declutter.py sortie done --bags 3

# Reality math
python3 scripts/declutter.py bags          # 400L ≈ 7 trash bags or 1 car-load

# One hard decision, decomposed
python3 scripts/declutter.py decide "University textbooks"

# Where it all goes
python3 scripts/declutter.py manifest

The Decision Rules (applied in decide)

Test Question Fail →
12-month Used in the last 12 months? (seasonal items: last 2 cycles) toss/donate
Replacement Can it be replaced in <30 min for <$30? toss
Sunk cost "I paid a lot" — that money is gone either way keeping ≠ refund
Cost of keeping space rent + attention + guilt, per year often exceeds item value
Active vs passive Does it serve a current project/life, or a hypothetical one? hypothetical = donate

Common Pitfalls

  1. Starting with the hardest box. Sentiment boxes (photos, kid stuff, heirlooms) are difficulty 5 — starting there kills the project in 15 minutes. The planner front-loads difficulty 1–2 volume; save the 5s for when momentum exists.
  2. The "maybe" pile. A maybe pile is a decision deferred with extra steps. Rule: maybe = keep for one cycle (30 days), then auto-toss — the tool flags aging maybes.
  3. Buying storage to solve clutter. New bins organize the problem; they don't remove it. Container math shows the bin cost vs the space freed.
  4. Selling everything. Listing 40 items at $8 each is a part-time job. Rule of thirds: sell only items worth ≥3× the effort; donate the rest. The manifest applies it automatically.
  5. No exit condition. "Clean the garage" cannot be finished; "2 bags out of the garage sports corner" can. Sorties always have a target.
  6. One heroic weekend. Eight-hour sessions create burnout and re-cluttering (the middle-of-room pile). 20-minute sorties, 3–4×/week, clear more volume in a month with zero drama.
  7. Ignoring the volume reality. 20 bags doesn't fit in a hatchback. The bags/car-load math prevents the Saturday night driveway-full-of-staff surprise.

Verification Checklist

  • item add records volume, difficulty, decision; volume required (physics first)
  • plan sorts by volume÷difficulty descending and groups into ≤20-min sorties
  • sortie done updates state, prints cumulative freed liters and % complete
  • bags converts liters to 60L bags / boxes / car-loads correctly
  • decide applies all five tests and prints annual cost-of-keeping
  • manifest batches by disposition with donation values and sell-price suggestions
  • All state local, one JSON file

References

  • references/decision-science.md — decision fatigue research notes, the space-cost model, donation value tables, runbook for a full house purge