# letsgetrandy/DICSS

Directly injected CSS

Repository: https://github.com/letsgetrandy/DICSS
Canonical: https://ross.abutalabs.com/products/dicss
Homepage: http://letsgetrandy.github.io/DICSS/
Language: JavaScript
License: MIT
License Family: permissive
Last push: 2015-12-18T17:39:22+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": 4188, "days_push": 3911, "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 1347, forks 73 (observed 2026-08-28T04:04:27.688752+00:00)

## What it is
DICSS is a small JavaScript library for injecting CSS styles directly from JavaScript, accepting JSON objects as style definitions. It lets developers write styles and scripts in one language without a separate CSS build process.

## Use cases
- inject css styles from javascript
- write styles in  objects instead of css files
- dynamically add and remove css rules at runtime
- avoid separate css build and minification steps
- deliver styles to the client via a rest service

## When to choose
- you want to define styles programmatically in JavaScript with no build tooling
- you need to add or remove CSS rules dynamically at runtime
- you want a tiny dependency-free style injection helper

## When to avoid
- you need a maintained, production-ready CSS-in-JS solution
- you want Sass/LESS features like variables, mixins, or preprocessing
- your project relies on modern tooling and active community support

## Facets
- artifact type: library
- maturity: abandoned
- function: css-framework, ui-components
- domain: web-development, frontend
- platform: browser
- tags: css-in-js, style-injection, javascript, novelty, nodejs

## Member repositories
- letsgetrandy/DICSS (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:27.688752+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 2026-08-30T04:42:37.303782+00:00, confidence not recorded.
  - readme: https://github.com/letsgetrandy/DICSS (fetched 2026-08-28T04:04:27.688752+00:00, sha bae2a291a9e9)
  - homepage: http://letsgetrandy.github.io/DICSS/ (fetched 2026-08-29T12:01:57.063139+00:00, sha 35930d1689bb)
- Data as of 2026-08-30T08:39:29.467469+00:00.