# iaddis/metalnes

Transistor level NES simulation

Repository: https://github.com/iaddis/metalnes
Canonical: https://ross.abutalabs.com/products/metalnes
Language: JavaScript
License: MIT
License Family: permissive
Last push: 2022-04-14T05:46:13+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 1688, "days_push": 1602, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1947, forks 39 (observed 2026-08-28T04:05:57.863853+00:00)

## What it is
MetalNES is a transistor-level simulation of the Nintendo Entertainment System (NES-001), including support chips, voltage ladders for composite video and audio output. It is built on Visual2C02 and Visual2A03 transistor netlists and currently runs on macOS only.

## Use cases
- simulate NES hardware at the transistor level
- study how the NES 2A03 and 2C02 chips work internally
- run NES software on a cycle-accurate hardware simulation
- learn low-level digital circuit behavior
- explore composite video and audio signal generation

## When to choose
- you want the most accurate possible NES simulation down to individual transistors
- you are researching or teaching retro hardware internals
- you need to observe voltage-level behavior of NES circuitry

## When to avoid
- you just want to play NES games - use a standard emulator instead
- you need MMU support or cross-platform builds
- you need high performance - the project needs lots of optimization

## Facets
- artifact type: application
- maturity: experimental
- function: simulation, graphics, audio-processing, developer-tools
- domain: simulation, hardware, gaming-tools, education
- platform: -
- tags: emulation, nes, transistor-level-simulation, retro-computing, hardware-simulation, macos, desktop, javascript

## Member repositories
- iaddis/metalnes (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:57.863853+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:07:07.189649+00:00, confidence not recorded.
  - readme: https://github.com/iaddis/metalnes (fetched 2026-08-28T04:05:57.863853+00:00, sha 3f4dc13f3114)
- Data as of 2026-08-30T08:39:29.467469+00:00.