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

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.

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

• 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 drill

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

Once a month:- take one drillatrophy drill --ai-on

withyour AI tools. Those scores are tracked separately, so the dashboard can show the gap between you-with-AI and you-alone.

$ 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.

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.

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.

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 LancetG&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.

Requires Node.js ≥ 22, plus Python 3 on PATH

if you want the Python exercises.

npm install -g atrophy
atrophy baseline

atrophy stats

atrophy serve

127.0.0.1:4646

atrophy export -o out.json

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.

• 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 isthe 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.

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/<skill>/

, 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.

MIT © 2026 Ashutosh Rath