Pattern Lock Tutor — Motor-Sequence Trainer

Overview

A pattern lock, a keyboard shortcut chain, a piano riff, a game controller combo, a keypad PIN you must enter without looking — these are motor sequences: the fingers learn them, not the eyes. People fail to learn (or re-learn) them for three predictable reasons:

1. Untrained transpositions — you can enter the pattern starting from its first node, but a rotated start (the "same" pattern begun from a different point) feels alien, and real-world retrieval never guarantees the trained entry point.
2. Interference — changing an old pattern to a new one produces alternation errors: under speed, the old habit wins. The fix is interleaved old-vs-new drills until the new one is faster, not just correct.
3. Speed before accuracy — practicing fast embeds errors. Accuracy must reach threshold at a comfortable tempo before tempo increases.

This skill runs the standard motor-learning playbook as a command-line trainer:

• Sequence definition — a pattern as a node list (3×3 grid indices, keypad digits, piano keys, arbitrary tokens)
• Spaced repetition — recall sessions scheduled with an expanding interval (Ebbinghaus-style); a failed recall resets the interval
• Transposition drills — the same sequence practiced from every rotated starting point
• Interference drills — old sequence and new sequence interleaved; tracks which one wins under alternation
• Session protocol — 4–6 blocks of 8–12 reps, accuracy ≥95% required before speed work; per-block error log
• Progress model — per-transposition accuracy, mean recall latency, interference win-rate, readiness verdict

When to Use

• Setting a new phone/computer unlock pattern and wanting it fluently yours within days, not weeks
• Changing a pattern (new phone, security rotation) — the interference drills are the whole game
• Learning a shortcut chain (IDE macros, editor combos) so it survives without looking
• Any short motor sequence you must execute blind: keypad entries, safe combinations, instrument riffs, controller combos
• Don't use for: declarative memory (facts → flashcard-forge), long procedural knowledge (algorithms → concept-cartographer), or security auditing of patterns (different domain).

How It Works

1. Define the sequence — seq add phone-old 1,5,9,3 (grid indices / digits / tokens).
2. Baseline test — test phone-old --reps 8 measures accuracy and seconds-per-rep per transposition.
3. Train — train phone-new --minutes 1.5 runs the block protocol: each block picks the weakest transposition, demands accuracy before speed, logs every error.
4. Interference — interfere phone-old phone-new alternates old/new prompts; scores which sequence dominates when you must switch — the number that predicts real-world failure.
5. Schedule — due lists sequences due for recall today with the current interval; successful recall expands the interval (1d → 3d → 7d → 16d → 35d), failure resets it.
6. Readiness — ready phone-new prints the verdict: every transposition ≥95% accuracy AND interference win-rate ≥80% AND latency ≤1.2× the first-session baseline.

Commands

# Define sequences (nodes = grid indices, digits, or any tokens)
python3 scripts/pattern_tutor.py seq add phone-old 1,5,9,3
python3 scripts/pattern_tutor.py seq add phone-new 2,6,4,8,5

# Baseline + training
python3 scripts/pattern_tutor.py test phone-new --reps 8
python3 scripts/pattern_tutor.py train phone-new --minutes 1.5

# The retraining killer feature: old vs new under alternation
python3 scripts/pattern_tutor.py interfere phone-old phone-new --reps 20

# Spaced repetition schedule
python3 scripts/pattern_tutor.py due
python3 scripts/pattern_tutor.py recall phone-new --passed
python3 scripts/pattern_tutor.py ready phone-new

# Progress
python3 scripts/pattern_tutor.py stats phone-new

Storage: pattern_tutor.json in cwd. Terminal-based, no dependencies — the point is micro-sessions everywhere (SSH, phone terminal, break room).

Session Protocol (what train enforces)

A block that fails its pass condition repeats once; two failures end the session (motor learning consolidates in sleep — cramming past failure embeds errors).

Common Pitfalls

1. Only practicing from the native start. Rotated-entry failure is the top real-world failure mode. test measures every transposition from day one.
2. Dropping the old pattern cold. When changing patterns, old habit interferes for 1–2 weeks. Run interfere until the new sequence wins ≥80% of alternations.
3. Training tired or interrupted. Motor consolidation happens during sleep; two clean micro-sessions a day beat one long grind. due keeps the cadence.
4. Chasing speed early. Errors practiced at speed become permanent. The block protocol refuses speed work below 95% accuracy.
5. Sharing your real pattern. Practice on a training pattern that you discard, or on tokens that resemble but don't match the real one. Never store the real unlock sequence in the JSON — seq add warns and asks for confirmation.

Verification Checklist

• Training sequence defined (not the real unlock pattern)
• Baseline test recorded for every transposition
• train blocks passed with ≥95% accuracy before speed work
• interfere win-rate ≥80% for the new sequence (if replacing an old one)
• due shows expanding intervals (no resets in the last 3 sessions)
• ready prints READY across all three criteria