MindMetrics
Personal psychometric platform. Ten instruments on a plugin engine, procedurally generated cognitive tests, practice effects modelled instead of ignored.

TL;DR
- Procedural generation with solver-verified unique answers — unlimited retakes without item memorization.
- Percentiles only against named published norms; everything else explicitly within-person.
- Practice effects modelled, plus Reliable Change Index badges instead of raw score deltas.
- Forecasts gated at n≥5, horizon-capped, with widening confidence bands.
- Per-instrument licensing stated up front; no proprietary instrument used.
Screens
Ten instruments, each with its licence
Every card carries what the test is, what it is not, and who owns it: CC BY-NC-SA for OEJTS, public domain for the IPIP inventories, original procedural content for the matrices. The caveats are on the card, not buried — the ICAR sample is called a spot-check rather than an IQ estimate, and the IPIP percentiles are labelled an internet convenience sample.
Cadence advice that never blocks
The right column says, per instrument, whether retaking now would mean anything — “outside the advisory window, ready when you are” against “not taken yet”. It advises and never refuses, which is the point: procedurally generated tests can be retaken freely, and the static questionnaires get guidance instead of a lockout.
Problem
Psychometric tests are built to be taken once. Retake one and you are measuring memory of the items, not the trait — so the consumer apps either block retakes or quietly sell you your own practice effect as growth. What I wanted was the opposite: test whenever I like, as often as I like, and get numbers that stay honest under repetition.
Approach
Ten instruments on a plugin engine behind one accessible test player. The cognitive tests are procedurally generated from seeded RNG — matrices from a Carpenter-taxonomy rule engine with solver-verified unique answers, plus series, digit span, reaction time and fluency — so no item ever repeats while parallel forms hold difficulty composition constant. Norms appear only where real published ones exist, always with the population named; generated tests are labelled within-person. Practice is modelled rather than ignored, via a log(sessionIndex) term, a practice-adjusted trend view, and Reliable Change Index badges that separate real movement from measurement noise. Forecasts unlock only at five sessions, are horizon-capped, and are drawn dashed with widening 95% bands.
Outcome
Code-complete beta on Next.js 16 with Drizzle over SQLite, multi-user data model ready for Postgres. Proprietary instruments (MBTI®, CliftonStrengths®, WAIS) are deliberately absent — open equivalents are substituted and every instrument carries its licence in writing. Next up is psychometric hardening: simulated-respondent checks and IRT calibration of the matrix difficulty model from accumulated responses.
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