Show HN: Atrophy – measure whether AI is eroding your unaided coding skill

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Are you getting worse at coding without AI? Atrophy tells you - with a number.

Atrophy is a command-line app that regularly hands you a small coding exercise to solve without any AI help - no Copilot, no chat, just you and your editor. It grades your solution automatically, keeps a skill rating for you (like a chess Elo), and charts how that rating moves over the weeks. If AI assistance is quietly eroding your ability to code unaided, the chart shows you - before an interview, an outage, or a day without wifi does.

How it works

atrophy baseline - once, ~25 minutes. Solve one exercise for each of five skills, AI off. This sets your starting ratings.

atrophy drill - 5-10 minutes, two or three times a week. One exercise, automatically picked from the skill you've neglected longest. Pass and your rating rises; fail and it falls.

atrophy serve - your dashboard. One curve per skill, plus the chart this tool exists for (more below).

Once a month: atrophy drill --ai-on - take one drill with your AI tools. Those scores are tracked separately, so the dashboard can show the gap between you-with-AI and you-alone.

What a drill looks like

$ atrophy drill

Binary search misses the edges [debugging · python · tier 2] ──────────────────────────────────────────────────────────── binary_search(items, target) should return the index of target in the sorted list items, or -1 if absent. It mysteriously fails for some values that are clearly in the list. Find and fix the bug. ──────────────────────────────────────────────────────────── Edit: /tmp/atrophy-k3XoP1/solution.py

AI off. Soft limit 7 min - timer started.

[Enter] submit · [q] abandon >

✓ 6/6 tests passed in 214s

Score 1.00 · debugging rating 1222 → 1241 (+19)

The exercise opens in your own editor ($EDITOR). Grading runs your code against hidden tests in a sandboxed subprocess. There's a soft time limit - going over shrinks your score gradually, nothing explodes. If tests fail you can keep fixing and resubmit; the clock just keeps running.

Not every skill is "write code against tests" - see the table below.

The five skills

Skill The drill Graded by

Syntax recall Write a small function from a spec Hidden tests

Debugging Working-looking code has one planted bug - find and fix it Hidden tests

Code reading Read a snippet, type exactly what it prints Compared to the snippet's real output

API memory Fill in the blanked-out stdlib call Answer match

Decomposition Outline a design (rate limiter, folder sync…) in bullets You score yourself against a revealed rubric

Exercises come in Python and JavaScript across three difficulty tiers - a hand-written static bank plus generator families that render endless fresh variants (randomized data, names, and twists; same seed always reproduces the same exercise). Difficulty targets you: each drill picks the tier where your predicted success is closest to ~65%, the point where a rep carries the most information. Comfortable wins teach the rating nothing.

The dashboard

atrophy serve # http://127.0.0.1:4646

Try the live demo → (synthetic data)

How to read it:

The line is your skill rating. It only moves when you actually take a drill - no evidence, no movement.

The shaded band around the line is confidence. Skip practicing for a few weeks and the band visibly widens: the tool isn't claiming you got worse, it's admitting it no longer knows you're still good. One drill snaps it tight again.

"Unaided vs AI-assisted" plots every drill score in two colors: your solo reps in blue, your monthly with-AI reps in green. If the blue line sinks while the green line stays perfect, that growing gap is your dependence, measured. This chart is the reason the tool exists.

Why take this seriously

The pattern is documented across professions, and it comes with no internal warning signal - people consistently feel fine while measurably declining:

Doctors' unaided polyp-detection rates fell 28% → 22% within months of routine AI assistance (The Lancet G&H, 2025)

Students with GPT-4 scored 17% worse than peers once it was taken away (PNAS, 2025)

Experienced developers using AI were 19% slower - while believing they were 20% faster (METR RCT, 2025)

Engineers who used AI to write code scored 17% lower on understanding that same code - debugging suffered most (Anthropic, 2026)

Full citations and an honest discussion of what this tool can and can't measure: docs/research.md.

Install

Requires Node.js ≥ 22, plus Python 3 on PATH if you want the Python exercises.

npm install -g atrophy atrophy baseline

Command reference

Command What it does

atrophy baseline First session: one drill per skill (~25 min)

atrophy drill One drill on your most-neglected skill

atrophy drill --axis debugging Drill a specific skill (syntax-recall, debugging, code-reading, api-memory, decomposition)

atrophy drill --lang python Only Python (or javascript) exercises

atrophy drill --ai-on Monthly comparison rep with AI allowed

atrophy publish --handle you Opt in to the public leaderboard; afterwards every drill syncs automatically (--stop opts out)

atrophy stats Ratings table and week streak in the terminal

atrophy serve Dashboard at 127.0.0.1:4646

atrophy export -o out.json Dump all your data as JSON

Your data

One SQLite file at ~/.atrophy/atrophy.db, owned by you. No account, no sync, no telemetry, nothing leaves your machine. ATROPHY_DB overrides the location if you want it in a dotfiles repo or synced folder.

Honest limitations

Ten-minute drills are a proxy for real-world skill, not a clinical measurement - treat trends, not absolute numbers, as the signal.

Drilling makes you better at drills. That's fine - the drill is the maintenance - but it's another reason the interesting number is the unaided-vs-AI gap, not your raw rating.

"AI off" is an honor system, actively assisted: starting an unaided drill while a known AI assistant is running (Copilot, Cursor, Claude, Windsurf, Codeium, Tabnine, Ollama, LM Studio, ChatGPT, Aider) prints a warning that names it. Warned, never blocked - you'd only be cheating your own chart.

Contributing & development

git clone https://github.com/ashutosh-rath02/atrophy.git cd atrophy && npm install npm run dev -- drill # CLI from source npm test # 70 tests, incl. real grading subprocesses

New exercises are the most welcome contribution: one JSON file under bank/exercises//, validated by bank/schema.ts. CI proves every planted bug actually fails a test and every code-reading snippet runs deterministically, so a broken exercise can't merge.

Roadmap: LLM-judged decomposition drills, more languages, spaced-repetition scheduling (FSRS), per-axis leaderboards.

License

MIT © 2026 Ashutosh Rath

About

Measure what your brain is losing while AI does your work - unaided-skill baselines, decay curves, reliance drills

Topics

cli

typescript

ai

deliberate-practice

developer-tools

local-first

skill-decay

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License

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v0.4.0 - honest drills, week streaks

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Jul 7, 2026

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