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17 projects
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Mirror Theory
MT
Mirror theory / personal case study
Radial symmetry beyond Messiaen and Slonimsky
What I built
Custom Mirror Theory app with generated graph artifacts, formula families, and math validation scripts.
theory graph
Mirror
symmetry
Radial
generated data
Math checks
content files
128+
Stack
Next.js 16
React 19
TypeScript
Contentlayer
Tailwind CSS
Framer Motion
Biome
Runtime
App Router pages expose Mirror Theory concepts, intervals, chords, harmony, rhythm, scales, set theory, radial symmetry, tables, glossary, formula lab, track catalog, and unification views.
`unified:index` builds the graph, formulas, address space, formula math checks, deep math checks, formula ML features, feature indexes, concept indexes, and final validation.
Visualization components render interval matrices, chord taxonomy, circle of fifths, inversion wheels, prime-form clocks, and temperament comparison.
Data model
Mirror Theory concepts, learning paths, track catalog, datasets, formulas, formula families, address-space features, and artifacts compile into a unified graph.
Canonical data and content live in source files while generated unified artifacts are rebuilt locally and intentionally kept out of git.
Set-theory data includes Forte classes, geometry, transformations, interval vectors, radial symmetry, Slonimsky-derived material, and Messiaen-style generated data.
Techniques
Generated graph pipeline separates canonical content from derived artifacts so math and content can be checked before the UI consumes them.
Formula-address and deep-math checks catch data debt in generated formula families.
Content catalog was extracted from the music app so the builder no longer depends on another app tree.
Typed query and graph layers keep learning paths, related concepts, artifacts, and formulas aligned.
Verification
`bun run unified:index` rebuilds all major generated graph artifacts and then validates the unified output.
`bun run check` runs content build, data integrity checks, TypeScript, and production Next build.
Formula and address-space checks were used to catch Slonimsky, Messiaen, and radial-symmetry data debt.
The app demonstrates technical breadth beyond SaaS: custom music theory, generated math artifacts, and interactive educational tooling.