# zakirullin/cognitive-load

🧠 Cognitive load is what matters

Repository: https://github.com/zakirullin/cognitive-load
Canonical: https://ross.abutalabs.com/products/cognitive-load
License: CC-BY-4.0
License Family: other
Last push: 2026-06-29T17:36:29+00:00

## Health v2 (maintenance only)
Score: 60/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 90, release rhythm 8, longevity 85
- inputs: {"age_days": 1202, "days_push": 65, "days_rel": 662, "gap_med": null, "n_releases_24m": 1}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 12490, forks 300 (observed 2026-08-28T04:10:59.180470+00:00)

## What it is
A widely-read living document arguing that cognitive load is the fundamental metric for evaluating software design practices. It explains intrinsic vs. extraneous cognitive load and critiques overengineered architectures and trendy abstractions.

## Use cases
- learn how to reduce cognitive load in codebases
- understand why clever abstractions hurt readability
- evaluate whether a design practice is actually useful
- guidance for reviewing LLM-generated code
- principles for writing maintainable software
- onboarding material for developers on code readability

## When to choose
- you want a concise, opinionated guide to code simplicity
- you're deciding between 'smart' architecture and plain readable code
- you're training developers or writing engineering guidelines

## When to avoid
- you need a tool or library rather than an essay
- you want rigorous academic treatment of cognitive load theory
- you need language-specific coding standards

## Facets
- artifact type: learning-resource
- maturity: active
- function: developer-tools, documentation
- domain: developer-tools, tutorials
- platform: cross-platform
- tags: cognitive-load, software-design, best-practices, code-readability, living-document

## Member repositories
- zakirullin/cognitive-load (main) score 60

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:10:59.180470+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 2026-08-29T17:14:00.918417+00:00, confidence not recorded.
  - readme: https://github.com/zakirullin/cognitive-load (fetched 2026-08-28T04:10:59.180470+00:00, sha 435c924f4260)
- Data as of 2026-08-30T08:39:29.467469+00:00.